var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"jsonp\":\"1\",\"host\":\"bibbase.org\"},\n      data: [{\"title\":\"Modelling land-use decisions under conditions of uncertainty\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling\",\"pages\":\"461-476\",\"volume\":\"31\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\",\"month\":\"7\",\"id\":\"436883e2-d0c0-3ff3-9a43-47ea1496df8e\",\"created\":\"2015-04-11T15:16:23.000Z\",\"accessed\":\"2015-03-18\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.\",\"bibtype\":\"article\",\"author\":\"Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry\",\"doi\":\"10.1016/j.compenvurbsys.2007.02.002\",\"journal\":\"Computers, Environment and Urban Systems\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Modelling land-use decisions under conditions of uncertainty},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},\\n pages = {461-476},\\n volume = {31},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},\\n month = {7},\\n id = {436883e2-d0c0-3ff3-9a43-47ea1496df8e},\\n created = {2015-04-11T15:16:23.000Z},\\n accessed = {2015-03-18},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},\\n bibtype = {article},\\n author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},\\n doi = {10.1016/j.compenvurbsys.2007.02.002},\\n journal = {Computers, Environment and Urban Systems},\\n number = {4}\\n}\",\"author_short\":[\"Ma,  L.\",\"Arentze,  T.\",\"Borgers,  A.\",\"Timmermans,  H.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Decision making under uncertainty\",\"Decision networks\",\"Land-use planning\",\"Planning support systems\",\"Sampling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Belief network models of land manager decisions and land use change\",\"type\":\"article\",\"year\":\"2002\",\"keywords\":\"conflict resolution, conservation, decision models\",\"pages\":\"1-23\",\"volume\":\"65\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\",\"month\":\"5\",\"id\":\"644a8604-5091-3090-9bf5-2d5e8e303042\",\"created\":\"2015-04-11T15:16:23.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.\",\"bibtype\":\"article\",\"author\":\"Bacon, P.J. and Cain, J.D. and Howard, D.C.\",\"doi\":\"10.1006/jema.2001.0507\",\"journal\":\"Journal of Environmental Management\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Belief network models of land manager decisions and land use change},\\n type = {article},\\n year = {2002},\\n keywords = {conflict resolution, conservation, decision models},\\n pages = {1-23},\\n volume = {65},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},\\n month = {5},\\n id = {644a8604-5091-3090-9bf5-2d5e8e303042},\\n created = {2015-04-11T15:16:23.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},\\n bibtype = {article},\\n author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},\\n doi = {10.1006/jema.2001.0507},\\n journal = {Journal of Environmental Management},\\n number = {1}\\n}\",\"author_short\":[\"Bacon,  P.\",\"Cain,  J.\",\"Howard,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\",\"role\":\"author\",\"keyword\":[\"conflict resolution\",\"conservation\",\"decision models\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluating acceptability of groundwater protection measures under different agricultural policies\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction\",\"pages\":\"54-66\",\"volume\":\"147\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\",\"month\":\"1\",\"id\":\"305c6eb9-3c9b-3b2d-a33e-c97dffec1133\",\"created\":\"2015-04-11T15:16:23.000Z\",\"accessed\":\"2015-01-27\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\",\"bibtype\":\"article\",\"author\":\"Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele\",\"doi\":\"10.1016/j.agwat.2014.07.023\",\"journal\":\"Agricultural Water Management\",\"bibtex\":\"@article{\\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\\n pages = {54-66},\\n volume = {147},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\\n month = {1},\\n id = {305c6eb9-3c9b-3b2d-a33e-c97dffec1133},\\n created = {2015-04-11T15:16:23.000Z},\\n accessed = {2015-01-27},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\\n bibtype = {article},\\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\\n doi = {10.1016/j.agwat.2014.07.023},\\n journal = {Agricultural Water Management}\\n}\",\"author_short\":[\"Giordano,  R.\",\"D’Agostino,  D.\",\"Apollonio,  C.\",\"Scardigno,  A.\",\"Pagano,  A.\",\"Portoghese,  I.\",\"Lamaddalena,  N.\",\"Piccinni,  A., F.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"CAP reform\",\"Conflict assessment\",\"Groundwater protection policy\",\"Policies interaction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluating acceptability of groundwater protection measures under different agricultural policies\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction\",\"pages\":\"54-66\",\"volume\":\"147\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\",\"month\":\"1\",\"id\":\"99b5d3a4-66ef-3453-83db-36352710606f\",\"created\":\"2015-04-11T15:16:24.000Z\",\"accessed\":\"2015-01-27\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\",\"bibtype\":\"article\",\"author\":\"Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele\",\"doi\":\"10.1016/j.agwat.2014.07.023\",\"journal\":\"Agricultural Water Management\",\"bibtex\":\"@article{\\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\\n pages = {54-66},\\n volume = {147},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\\n month = {1},\\n id = {99b5d3a4-66ef-3453-83db-36352710606f},\\n created = {2015-04-11T15:16:24.000Z},\\n accessed = {2015-01-27},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\\n bibtype = {article},\\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\\n doi = {10.1016/j.agwat.2014.07.023},\\n journal = {Agricultural Water Management}\\n}\",\"author_short\":[\"Giordano,  R.\",\"D’Agostino,  D.\",\"Apollonio,  C.\",\"Scardigno,  A.\",\"Pagano,  A.\",\"Portoghese,  I.\",\"Lamaddalena,  N.\",\"Piccinni,  A., F.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"CAP reform\",\"Conflict assessment\",\"Groundwater protection policy\",\"Policies interaction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty\",\"pages\":\"64-78\",\"volume\":\"299\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\",\"month\":\"3\",\"id\":\"c5616b49-da10-3235-865a-d74393655fca\",\"created\":\"2015-04-11T15:30:36.000Z\",\"accessed\":\"2015-01-06\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\",\"bibtype\":\"article\",\"author\":\"Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.\",\"doi\":\"10.1016/j.ecolmodel.2014.12.004\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\\n pages = {64-78},\\n volume = {299},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\\n month = {3},\\n id = {c5616b49-da10-3235-865a-d74393655fca},\\n created = {2015-04-11T15:30:36.000Z},\\n accessed = {2015-01-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\\n bibtype = {article},\\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\\n doi = {10.1016/j.ecolmodel.2014.12.004},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Hamilton,  S., H.\",\"Pollino,  C., A.\",\"Jakeman,  A., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Ecological modeling\",\"Endangered species\",\"Model validation\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian belief network,Diadema antillarum,Dictyota spp.,Grazing pressure,Macroalgal dynamics,Nutrients,Scaridae\",\"pages\":\"1305-1314\",\"volume\":\"220\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380009001525\",\"month\":\"5\",\"id\":\"7cf595bd-9144-3165-be59-04863302f07c\",\"created\":\"2015-04-11T15:45:45.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.\",\"bibtype\":\"article\",\"author\":\"Renken, Henk and Mumby, Peter J.\",\"doi\":\"10.1016/j.ecolmodel.2009.02.022\",\"journal\":\"Ecological Modelling\",\"number\":\"9-10\",\"bibtex\":\"@article{\\n title = {Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian belief network,Diadema antillarum,Dictyota spp.,Grazing pressure,Macroalgal dynamics,Nutrients,Scaridae},\\n pages = {1305-1314},\\n volume = {220},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009001525},\\n month = {5},\\n id = {7cf595bd-9144-3165-be59-04863302f07c},\\n created = {2015-04-11T15:45:45.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.},\\n bibtype = {article},\\n author = {Renken, Henk and Mumby, Peter J.},\\n doi = {10.1016/j.ecolmodel.2009.02.022},\\n journal = {Ecological Modelling},\\n number = {9-10}\\n}\",\"author_short\":[\"Renken,  H.\",\"Mumby,  P., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380009001525\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"Diadema antillarum\",\"Dictyota spp.\",\"Grazing pressure\",\"Macroalgal dynamics\",\"Nutrients\",\"Scaridae\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty\",\"pages\":\"64-78\",\"volume\":\"299\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\",\"month\":\"3\",\"id\":\"b02b5d31-9b7f-3d35-a559-3c76e87b962e\",\"created\":\"2015-04-11T15:45:45.000Z\",\"accessed\":\"2015-01-06\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\",\"bibtype\":\"article\",\"author\":\"Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.\",\"doi\":\"10.1016/j.ecolmodel.2014.12.004\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\\n pages = {64-78},\\n volume = {299},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\\n month = {3},\\n id = {b02b5d31-9b7f-3d35-a559-3c76e87b962e},\\n created = {2015-04-11T15:45:45.000Z},\\n accessed = {2015-01-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\\n bibtype = {article},\\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\\n doi = {10.1016/j.ecolmodel.2014.12.004},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Hamilton,  S., H.\",\"Pollino,  C., A.\",\"Jakeman,  A., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Ecological modeling\",\"Endangered species\",\"Model validation\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Bayesian belief network,Geographic information system,Probabilistic inference,Swaziland,Wildfire\",\"pages\":\"199-208\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002035\",\"month\":\"2\",\"id\":\"777ffc68-b80c-3b09-b39c-50d6de96dc04\",\"created\":\"2015-04-11T15:45:45.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001–2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.\",\"bibtype\":\"article\",\"author\":\"Dlamini, Wisdom M.\",\"doi\":\"10.1016/j.envsoft.2009.08.002\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland},\\n type = {article},\\n year = {2010},\\n keywords = {Bayesian belief network,Geographic information system,Probabilistic inference,Swaziland,Wildfire},\\n pages = {199-208},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002035},\\n month = {2},\\n id = {777ffc68-b80c-3b09-b39c-50d6de96dc04},\\n created = {2015-04-11T15:45:45.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001–2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.},\\n bibtype = {article},\\n author = {Dlamini, Wisdom M.},\\n doi = {10.1016/j.envsoft.2009.08.002},\\n journal = {Environmental Modelling & Software},\\n number = {2}\\n}\",\"author_short\":[\"Dlamini,  W., M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002035\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"Geographic information system\",\"Probabilistic inference\",\"Swaziland\",\"Wildfire\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian belief modeling of climate change impacts for informing regional adaptation options\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs\",\"pages\":\"113-121\",\"volume\":\"44\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\",\"month\":\"6\",\"id\":\"a54c3232-2de1-345c-9420-c718b2f27607\",\"created\":\"2015-04-11T15:45:45.000Z\",\"accessed\":\"2015-02-24\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.\",\"bibtype\":\"article\",\"author\":\"Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.\",\"doi\":\"10.1016/j.envsoft.2012.07.008\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},\\n type = {article},\\n year = {2013},\\n keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},\\n pages = {113-121},\\n volume = {44},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},\\n month = {6},\\n id = {a54c3232-2de1-345c-9420-c718b2f27607},\\n created = {2015-04-11T15:45:45.000Z},\\n accessed = {2015-02-24},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},\\n bibtype = {article},\\n author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},\\n doi = {10.1016/j.envsoft.2012.07.008},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Richards,  R.\",\"Sanó,  M.\",\"Roiko,  A.\",\"Carter,  R.\",\"Bussey,  M.\",\"Matthews,  J.\",\"Smith,  T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\",\"role\":\"author\",\"keyword\":[\"Adaptation\",\"Bayesian Belief Networks\",\"Climate change\",\"Group-model building\",\"Stakeholder beliefs\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement\",\"pages\":\"90-103\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\",\"month\":\"8\",\"id\":\"ecee1c33-4441-35b5-b2e5-d008f50d97d0\",\"created\":\"2015-04-11T15:45:45.000Z\",\"accessed\":\"2015-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.\",\"bibtype\":\"article\",\"author\":\"Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele\",\"doi\":\"10.1016/j.envsoft.2013.03.001\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},\\n pages = {90-103},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},\\n month = {8},\\n id = {ecee1c33-4441-35b5-b2e5-d008f50d97d0},\\n created = {2015-04-11T15:45:45.000Z},\\n accessed = {2015-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},\\n bibtype = {article},\\n author = {Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},\\n doi = {10.1016/j.envsoft.2013.03.001},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Portoghese,  I.\",\"D'Agostino,  D.\",\"Giordano,  R.\",\"Scardigno,  A.\",\"Apollonio,  C.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Networks\",\"Conflict mitigation\",\"Groundwater protection policy\",\"Stakeholder involvement\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A review of Bayesian belief networks in ecosystem service modelling\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models\",\"pages\":\"1-11\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\",\"month\":\"8\",\"id\":\"cde4bf8d-fd72-3d55-bba7-f0059de57b6a\",\"created\":\"2015-04-11T15:50:45.000Z\",\"accessed\":\"2015-02-10\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.\",\"bibtype\":\"article\",\"author\":\"Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.\",\"doi\":\"10.1016/j.envsoft.2013.03.011\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A review of Bayesian belief networks in ecosystem service modelling},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},\\n pages = {1-11},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},\\n month = {8},\\n id = {cde4bf8d-fd72-3d55-bba7-f0059de57b6a},\\n created = {2015-04-11T15:50:45.000Z},\\n accessed = {2015-02-10},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},\\n bibtype = {article},\\n author = {Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},\\n doi = {10.1016/j.envsoft.2013.03.011},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Landuyt,  D.\",\"Broekx,  S.\",\"D'hondt,  R.\",\"Engelen,  G.\",\"Aertsens,  J.\",\"Goethals,  P., L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Ecosystem services\",\"Expert based systems\",\"Graphical models\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Encyclopedia of Ecology\",\"type\":\"book\",\"year\":\"2008\",\"source\":\"Encyclopedia of Ecology\",\"keywords\":\"Artificial intelligence,Bayesian networks,Belief networks,Causal analysis,Causality,Graphical models,Hierarchical Bayes,Inference,Influence diagrams,Learning,Prediction,Probability networks\",\"pages\":\"307-317\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/B9780080454054001440\",\"publisher\":\"Elsevier\",\"id\":\"af635c49-de74-3eb9-ae1c-c6a1593ce15f\",\"created\":\"2015-04-11T15:50:45.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"By succinctly and effectively translating causal assertions between variables into patterns of probabilistic dependence, Bayesian networks (BNs) facilitate logical and holistic reasoning under uncertainty in complex systems. Such reasoning is necessary for accurate analysis, synthesis, prediction, diagnosis, and decision making. A definition of BNs is first provided and a simple ecological example is introduced that will be used throughout the remainder of the article to illustrate basic concepts. Methods for constructing BNs are next described, including specification of model structure and conditional probabilities, both deliberately and automatically from case data. This is followed by a description of how BNs can be used for prediction, inference, explanation, intervention, and decision. Finally, some special cases of BNs are presented including hierarchical, dynamic, and integrated models. These show how BNs can be used to integrate across scales, disciplines, and levels of complexity.\",\"bibtype\":\"book\",\"author\":\"Borsuk, M.E.\",\"doi\":\"10.1016/B978-008045405-4.00144-0\",\"bibtex\":\"@book{\\n title = {Encyclopedia of Ecology},\\n type = {book},\\n year = {2008},\\n source = {Encyclopedia of Ecology},\\n keywords = {Artificial intelligence,Bayesian networks,Belief networks,Causal analysis,Causality,Graphical models,Hierarchical Bayes,Inference,Influence diagrams,Learning,Prediction,Probability networks},\\n pages = {307-317},\\n websites = {http://www.sciencedirect.com/science/article/pii/B9780080454054001440},\\n publisher = {Elsevier},\\n id = {af635c49-de74-3eb9-ae1c-c6a1593ce15f},\\n created = {2015-04-11T15:50:45.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {By succinctly and effectively translating causal assertions between variables into patterns of probabilistic dependence, Bayesian networks (BNs) facilitate logical and holistic reasoning under uncertainty in complex systems. Such reasoning is necessary for accurate analysis, synthesis, prediction, diagnosis, and decision making. A definition of BNs is first provided and a simple ecological example is introduced that will be used throughout the remainder of the article to illustrate basic concepts. Methods for constructing BNs are next described, including specification of model structure and conditional probabilities, both deliberately and automatically from case data. This is followed by a description of how BNs can be used for prediction, inference, explanation, intervention, and decision. Finally, some special cases of BNs are presented including hierarchical, dynamic, and integrated models. These show how BNs can be used to integrate across scales, disciplines, and levels of complexity.},\\n bibtype = {book},\\n author = {Borsuk, M.E.},\\n doi = {10.1016/B978-008045405-4.00144-0}\\n}\",\"author_short\":[\"Borsuk,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/B9780080454054001440\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"borsuk-encyclopediaofecology-2008\",\"role\":\"author\",\"keyword\":[\"Artificial intelligence\",\"Bayesian networks\",\"Belief networks\",\"Causal analysis\",\"Causality\",\"Graphical models\",\"Hierarchical Bayes\",\"Inference\",\"Influence diagrams\",\"Learning\",\"Prediction\",\"Probability networks\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling land-use decisions under conditions of uncertainty\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling\",\"pages\":\"461-476\",\"volume\":\"31\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\",\"month\":\"7\",\"id\":\"60cdd308-554e-3906-bbf0-382586eb071c\",\"created\":\"2015-04-11T17:37:59.000Z\",\"accessed\":\"2015-03-18\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.\",\"bibtype\":\"article\",\"author\":\"Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry\",\"doi\":\"10.1016/j.compenvurbsys.2007.02.002\",\"journal\":\"Computers, Environment and Urban Systems\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Modelling land-use decisions under conditions of uncertainty},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},\\n pages = {461-476},\\n volume = {31},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},\\n month = {7},\\n id = {60cdd308-554e-3906-bbf0-382586eb071c},\\n created = {2015-04-11T17:37:59.000Z},\\n accessed = {2015-03-18},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},\\n bibtype = {article},\\n author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},\\n doi = {10.1016/j.compenvurbsys.2007.02.002},\\n journal = {Computers, Environment and Urban Systems},\\n number = {4}\\n}\",\"author_short\":[\"Ma,  L.\",\"Arentze,  T.\",\"Borgers,  A.\",\"Timmermans,  H.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Decision making under uncertainty\",\"Decision networks\",\"Land-use planning\",\"Planning support systems\",\"Sampling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluating acceptability of groundwater protection measures under different agricultural policies\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction\",\"pages\":\"54-66\",\"volume\":\"147\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\",\"month\":\"1\",\"id\":\"811f579b-70c3-3d8f-99a4-0247f35ac0f5\",\"created\":\"2015-04-11T17:37:59.000Z\",\"accessed\":\"2015-01-27\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\",\"bibtype\":\"article\",\"author\":\"Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele\",\"doi\":\"10.1016/j.agwat.2014.07.023\",\"journal\":\"Agricultural Water Management\",\"bibtex\":\"@article{\\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\\n pages = {54-66},\\n volume = {147},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\\n month = {1},\\n id = {811f579b-70c3-3d8f-99a4-0247f35ac0f5},\\n created = {2015-04-11T17:37:59.000Z},\\n accessed = {2015-01-27},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\\n bibtype = {article},\\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\\n doi = {10.1016/j.agwat.2014.07.023},\\n journal = {Agricultural Water Management}\\n}\",\"author_short\":[\"Giordano,  R.\",\"D’Agostino,  D.\",\"Apollonio,  C.\",\"Scardigno,  A.\",\"Pagano,  A.\",\"Portoghese,  I.\",\"Lamaddalena,  N.\",\"Piccinni,  A., F.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"CAP reform\",\"Conflict assessment\",\"Groundwater protection policy\",\"Policies interaction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty\",\"pages\":\"64-78\",\"volume\":\"299\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\",\"month\":\"3\",\"id\":\"5ff020c8-12b9-33e0-b574-0d4c42063017\",\"created\":\"2015-04-11T17:43:54.000Z\",\"accessed\":\"2015-01-06\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\",\"bibtype\":\"article\",\"author\":\"Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.\",\"doi\":\"10.1016/j.ecolmodel.2014.12.004\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\\n pages = {64-78},\\n volume = {299},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\\n month = {3},\\n id = {5ff020c8-12b9-33e0-b574-0d4c42063017},\\n created = {2015-04-11T17:43:54.000Z},\\n accessed = {2015-01-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\\n bibtype = {article},\\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\\n doi = {10.1016/j.ecolmodel.2014.12.004},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Hamilton,  S., H.\",\"Pollino,  C., A.\",\"Jakeman,  A., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Ecological modeling\",\"Endangered species\",\"Model validation\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis.\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayes Theorem,Ecosystem,Empirical Research,Fresh Water,Fresh Water: chemistry,Nitrogen,Nitrogen: analysis,Wetlands\",\"pages\":\"91-9\",\"volume\":\"124\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479713002016\",\"month\":\"7\",\"day\":\"30\",\"id\":\"c5517933-9eb6-37af-a3d4-a2d37a79f7f2\",\"created\":\"2015-04-11T17:43:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Increased nitrogen (N) inputs to freshwater wetlands potentially affect the interaction between nitrous oxide (N2O) emissions and outflow water quality. The purpose of this study is to evaluate the influence of N inputs on N removal, as well as the interaction between N2O emissions and outflow water quality, using a Bayesian Belief Network (BBN). The BBN was developed by linking wetland classification, biogeochemical processes, and environmental factors. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was implemented using 30 wetlands (88% of the case file) and evaluated using a single test file containing 4 wetlands (12% of the case file). The BBN implies it is not average annual total N load entering the wetland, but the N removal efficiency that influences the interactions between N2O emissions and outflow water quality. Even though the network has a very low error rate indicating a high predictive accuracy, additional testing and larger training and testing datasets would increase confidence in the model's ability to provide robust predictions and to reduce the uncertainty resulting from an incomplete dataset and knowledge gaps regarding the interactions between N2O emissions and outflow water quality.\",\"bibtype\":\"article\",\"author\":\"Spence, Porché L and Jordan, Stephen J\",\"doi\":\"10.1016/j.jenvman.2013.03.029\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis.},\\n type = {article},\\n year = {2013},\\n keywords = {Bayes Theorem,Ecosystem,Empirical Research,Fresh Water,Fresh Water: chemistry,Nitrogen,Nitrogen: analysis,Wetlands},\\n pages = {91-9},\\n volume = {124},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713002016},\\n month = {7},\\n day = {30},\\n id = {c5517933-9eb6-37af-a3d4-a2d37a79f7f2},\\n created = {2015-04-11T17:43:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Increased nitrogen (N) inputs to freshwater wetlands potentially affect the interaction between nitrous oxide (N2O) emissions and outflow water quality. The purpose of this study is to evaluate the influence of N inputs on N removal, as well as the interaction between N2O emissions and outflow water quality, using a Bayesian Belief Network (BBN). The BBN was developed by linking wetland classification, biogeochemical processes, and environmental factors. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was implemented using 30 wetlands (88% of the case file) and evaluated using a single test file containing 4 wetlands (12% of the case file). The BBN implies it is not average annual total N load entering the wetland, but the N removal efficiency that influences the interactions between N2O emissions and outflow water quality. Even though the network has a very low error rate indicating a high predictive accuracy, additional testing and larger training and testing datasets would increase confidence in the model's ability to provide robust predictions and to reduce the uncertainty resulting from an incomplete dataset and knowledge gaps regarding the interactions between N2O emissions and outflow water quality.},\\n bibtype = {article},\\n author = {Spence, Porché L and Jordan, Stephen J},\\n doi = {10.1016/j.jenvman.2013.03.029},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Spence,  P., L.\",\"Jordan,  S., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479713002016\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Ecosystem\",\"Empirical Research\",\"Fresh Water\",\"Fresh Water: chemistry\",\"Nitrogen\",\"Nitrogen: analysis\",\"Wetlands\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayesian belief network,conditional probability,knowledge,moss greening produce,preference,texture analysis\",\"pages\":\"45-50\",\"volume\":\"1\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1881836608800018\",\"id\":\"56b90f2e-e48c-3fe7-b9aa-39d9e2f838fb\",\"created\":\"2015-04-11T17:43:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.\",\"bibtype\":\"article\",\"author\":\"Ushada, Mirwan and Murase, Haruhiko\",\"doi\":\"10.1016/S1881-8366(08)80001-8\",\"journal\":\"Engineering in Agriculture, Environment and Food\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis},\\n type = {article},\\n year = {2008},\\n keywords = {Bayesian belief network,conditional probability,knowledge,moss greening produce,preference,texture analysis},\\n pages = {45-50},\\n volume = {1},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1881836608800018},\\n id = {56b90f2e-e48c-3fe7-b9aa-39d9e2f838fb},\\n created = {2015-04-11T17:43:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.},\\n bibtype = {article},\\n author = {Ushada, Mirwan and Murase, Haruhiko},\\n doi = {10.1016/S1881-8366(08)80001-8},\\n journal = {Engineering in Agriculture, Environment and Food},\\n number = {2}\\n}\",\"author_short\":[\"Ushada,  M.\",\"Murase,  H.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1881836608800018\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"conditional probability\",\"knowledge\",\"moss greening produce\",\"preference\",\"texture analysis\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip\",\"type\":\"article\",\"year\":\"2004\",\"keywords\":\"Bayesian belief networks,Desalination,Gaza Strip,Optimization,Reverse osmosis,Uncertainty\",\"pages\":\"191-201\",\"volume\":\"161\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0011916404900549\",\"month\":\"2\",\"id\":\"6bb987ae-3066-32eb-afbb-2564d7beae75\",\"created\":\"2015-04-11T17:43:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In the Gaza Strip, the available freshwater sources are severely polluted and overused. Desalination of seawater through reverse osmosis (RO) has become the most realistic option to meet a rapidly growing water demand. It is estimated that the Gaza Strip will need to develop a seawater desalination capacity of about 120,000 m3/d by the year 2008, and an additional 30,000 m3/d by the year 2016 in order to maintain a fresh water balance in the coastal aquifer and to fulfill the water demand for different uses in a sustainable manner. Cost and reliability of a large RO facility are still subject to much uncertainty. The cost of seawater desalination by RO systems varies with facility size and lifetime, financing conditions, intake type and pre-treatment requirements, power requirements, recovery rate, chemicals cost, spare parts cost, and membrane replacement cost. The permeate salinity is a function of feed water temperature, recovery rate, and permeate flux. The quantity of water produced depends mainly on plant size, recovery rate, and operating load factor. Many of these parameters are subject to a great deal of uncertainty. The objective of this work is to develop a probabilistic model for the simulation of seawater reverse osmosis processes using a Bayesian belief network (BBN) approach. This model represents a new application of probabilistic modeling tools to a large-scale complex system. The model is used to: (1) characterize the different uncertainties involved in the RO process; (2) optimize the RO process reliability and cost; and (3) study how uncertainty in unit capital cost, unit operation and maintenance (O&M) cost, and permeate quality is related to different input variables. The model utilizes information from journal articles, books, expert opinions, and technical reports related to the study area, and can be used to support operators and decision makers in the design of RO systems and formulation of operational policies. The structure of the model is not specific to the Gaza Strip and can be easily populated with data from any large-scale RO plant in any part of the world.\",\"bibtype\":\"article\",\"author\":\"Ghabayen, Said and McKee, Mac and Kemblowski, Mariush\",\"doi\":\"10.1016/S0011-9164(04)90054-9\",\"journal\":\"Desalination\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip},\\n type = {article},\\n year = {2004},\\n keywords = {Bayesian belief networks,Desalination,Gaza Strip,Optimization,Reverse osmosis,Uncertainty},\\n pages = {191-201},\\n volume = {161},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0011916404900549},\\n month = {2},\\n id = {6bb987ae-3066-32eb-afbb-2564d7beae75},\\n created = {2015-04-11T17:43:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In the Gaza Strip, the available freshwater sources are severely polluted and overused. Desalination of seawater through reverse osmosis (RO) has become the most realistic option to meet a rapidly growing water demand. It is estimated that the Gaza Strip will need to develop a seawater desalination capacity of about 120,000 m3/d by the year 2008, and an additional 30,000 m3/d by the year 2016 in order to maintain a fresh water balance in the coastal aquifer and to fulfill the water demand for different uses in a sustainable manner. Cost and reliability of a large RO facility are still subject to much uncertainty. The cost of seawater desalination by RO systems varies with facility size and lifetime, financing conditions, intake type and pre-treatment requirements, power requirements, recovery rate, chemicals cost, spare parts cost, and membrane replacement cost. The permeate salinity is a function of feed water temperature, recovery rate, and permeate flux. The quantity of water produced depends mainly on plant size, recovery rate, and operating load factor. Many of these parameters are subject to a great deal of uncertainty. The objective of this work is to develop a probabilistic model for the simulation of seawater reverse osmosis processes using a Bayesian belief network (BBN) approach. This model represents a new application of probabilistic modeling tools to a large-scale complex system. The model is used to: (1) characterize the different uncertainties involved in the RO process; (2) optimize the RO process reliability and cost; and (3) study how uncertainty in unit capital cost, unit operation and maintenance (O&M) cost, and permeate quality is related to different input variables. The model utilizes information from journal articles, books, expert opinions, and technical reports related to the study area, and can be used to support operators and decision makers in the design of RO systems and formulation of operational policies. The structure of the model is not specific to the Gaza Strip and can be easily populated with data from any large-scale RO plant in any part of the world.},\\n bibtype = {article},\\n author = {Ghabayen, Said and McKee, Mac and Kemblowski, Mariush},\\n doi = {10.1016/S0011-9164(04)90054-9},\\n journal = {Desalination},\\n number = {2}\\n}\",\"author_short\":[\"Ghabayen,  S.\",\"McKee,  M.\",\"Kemblowski,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0011916404900549\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Desalination\",\"Gaza Strip\",\"Optimization\",\"Reverse osmosis\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin\",\"type\":\"article\",\"year\":\"2001\",\"keywords\":\"Aquatic habitat,Bayesian belief network,Columbia River basin,Fish,Salmon,Trout\",\"pages\":\"43-62\",\"volume\":\"153\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004534\",\"month\":\"10\",\"id\":\"30411cd0-977e-336b-92a0-7fd355045e17\",\"created\":\"2015-04-11T17:55:09.000Z\",\"accessed\":\"2015-03-24\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Aquatic species throughout the interior Columbia River basin are at risk. Evaluation of the potential effects of federal land management on aquatic ecosystems across this region is an important but challenging task. Issues include the size and complexity of the systems, uncertainty in important processes and existing states, flexibility and consistency in the analytical framework, and an ability to quantify results. We focused on salmonid fishes and their habitats as indicators of conditions in aquatic ecosystems and used Bayesian belief networks as a formal, quantitative framework to address the issues in our evaluation of land management alternatives proposed for the interior Columbia River basin. Because empirical information is limited at the scales relevant to our analysis, an ability to combine both empirical and more subjective information was key to the analysis. The representation of linkages through conditional probabilities made uncertainty explicit. We constructed two general networks. One represented the influence of landscape characteristics and existing and predicted management activities on aquatic habitats. A second represented the influence of habitat, existing biotic conditions, and for two anadromous species, ocean and migratory conditions, on the status of six widely distributed salmonid fishes. In the long term (100 years) all three land management alternatives were expected to produce positive changes in the status and distribution of the salmonids and their habitats. Trends were stronger for habitat than for the status of salmonids because of greater uncertainty in linking the fish and habitat networks and constraints outside spawning and rearing habitat on federal lands in the study area. Trends were stronger for resident salmonids than anadromous forms because of additional effects of the migratory corridor assumed for the latter. Alternative S2, which approached ecosystem restoration more conservatively, generally produced the strongest positive changes, and alternative S3, designed to promote more aggressive restoration, the weakest. Averaged across the basin, differences among the alternatives were small. Differences were greater at finer temporal and spatial scales. In the short term (10 years) alternative S3 was expected to lead to further degradation in some areas. By formalizing our understanding and assumptions in these networks, we provided a framework for exploring differences in the management alternatives that is more quantifiable, spatially explicit, and flexible than previous approaches.\",\"bibtype\":\"article\",\"author\":\"Rieman, Bruce and Peterson, James T and Clayton, James and Howell, Philip and Thurow, Russell and Thompson, William and Lee, Danny\",\"doi\":\"10.1016/S0378-1127(01)00453-4\",\"journal\":\"Forest Ecology and Management\",\"number\":\"1-3\",\"bibtex\":\"@article{\\n title = {Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin},\\n type = {article},\\n year = {2001},\\n keywords = {Aquatic habitat,Bayesian belief network,Columbia River basin,Fish,Salmon,Trout},\\n pages = {43-62},\\n volume = {153},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004534},\\n month = {10},\\n id = {30411cd0-977e-336b-92a0-7fd355045e17},\\n created = {2015-04-11T17:55:09.000Z},\\n accessed = {2015-03-24},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Aquatic species throughout the interior Columbia River basin are at risk. Evaluation of the potential effects of federal land management on aquatic ecosystems across this region is an important but challenging task. Issues include the size and complexity of the systems, uncertainty in important processes and existing states, flexibility and consistency in the analytical framework, and an ability to quantify results. We focused on salmonid fishes and their habitats as indicators of conditions in aquatic ecosystems and used Bayesian belief networks as a formal, quantitative framework to address the issues in our evaluation of land management alternatives proposed for the interior Columbia River basin. Because empirical information is limited at the scales relevant to our analysis, an ability to combine both empirical and more subjective information was key to the analysis. The representation of linkages through conditional probabilities made uncertainty explicit. We constructed two general networks. One represented the influence of landscape characteristics and existing and predicted management activities on aquatic habitats. A second represented the influence of habitat, existing biotic conditions, and for two anadromous species, ocean and migratory conditions, on the status of six widely distributed salmonid fishes. In the long term (100 years) all three land management alternatives were expected to produce positive changes in the status and distribution of the salmonids and their habitats. Trends were stronger for habitat than for the status of salmonids because of greater uncertainty in linking the fish and habitat networks and constraints outside spawning and rearing habitat on federal lands in the study area. Trends were stronger for resident salmonids than anadromous forms because of additional effects of the migratory corridor assumed for the latter. Alternative S2, which approached ecosystem restoration more conservatively, generally produced the strongest positive changes, and alternative S3, designed to promote more aggressive restoration, the weakest. Averaged across the basin, differences among the alternatives were small. Differences were greater at finer temporal and spatial scales. In the short term (10 years) alternative S3 was expected to lead to further degradation in some areas. By formalizing our understanding and assumptions in these networks, we provided a framework for exploring differences in the management alternatives that is more quantifiable, spatially explicit, and flexible than previous approaches.},\\n bibtype = {article},\\n author = {Rieman, Bruce and Peterson, James T and Clayton, James and Howell, Philip and Thurow, Russell and Thompson, William and Lee, Danny},\\n doi = {10.1016/S0378-1127(01)00453-4},\\n journal = {Forest Ecology and Management},\\n number = {1-3}\\n}\",\"author_short\":[\"Rieman,  B.\",\"Peterson,  J., T.\",\"Clayton,  J.\",\"Howell,  P.\",\"Thurow,  R.\",\"Thompson,  W.\",\"Lee,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004534\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001\",\"role\":\"author\",\"keyword\":[\"Aquatic habitat\",\"Bayesian belief network\",\"Columbia River basin\",\"Fish\",\"Salmon\",\"Trout\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"The construction of causal networks to estimate coral bleaching intensity\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"AGRRA,Atlantic and Gulf Rapid Reef Assessment,BN,BNPC,BSST,Bayesian network,Bayesian networks,Belief Network Power Constructor,CI,CPT,Coral bleaching,Coral reef,DAG,EM,Environmental variability,K490,MEI,MaxSST,PCA,PPT,Remote sensing,SST,SSTAc5d,South Atlantic coral reefs,U,V,best sea surface temperature,conditional independence,conditional probabilities table,diffuse light attenuation coefficient at 490 nm,directed acyclic graph,expectation–maximization,maximum sea surface temperature,mean surface wind fields,meridional wind,multivariate El Niño index,principal component analysis,rain precipitation,sea surface temperature,sea surface temperature accumulated in five days,zonal wind,|W|\",\"pages\":\"157-167\",\"volume\":\"42\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000121\",\"month\":\"4\",\"id\":\"4a097128-e62a-3c7b-ad37-6b51838d86f0\",\"created\":\"2015-04-11T17:55:10.000Z\",\"accessed\":\"2015-02-27\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Current metrics for predicting bleaching episodes, e.g. NOAA's Coral Reef Watch Program, do not seem to apply well to Brazil's marginal reefs located in Bahia state and alternative predictive approaches must be sought for effective long term management. Bleaching occurrences at Abrolhos have been observed since the 1990s but with a much lower frequency/extent than for other reef systems worldwide. We constructed a Bayesian Belief Network (BN) to back-predict the intensity of bleaching events and learn how local and regional scale forcing factors interact to enhance or alleviate coral bleaching specific to Abrolhos. Bleaching intensity data were collected for several reef sites across Bahia state coast (∼12°–20°S; 37°–40°W) during the austral summer 1994–2005 and compared to environmental data: sea surface temperature (SST), diffuse light attenuation coefficient at 490 nm (K490), rain precipitation, wind velocities, and El Niño Southern Oscillation (ENSO) proxies. Conditional independence tests were calculated to produce four specialized BNs, each with specific factors that likely regulate bleaching intensity. All specialized BNs identified that a five-day accumulated SST proxy (SSTAc5d) was the exclusive parent node for coral bleaching producing a total predictive rate of 88% based on SSTAc5d state. When SSTAc5d was simulated as unknown, the Thermal-Eolic Resultant BN kept the total predictive rate of 88%. Our approach has produced initial means to predict beaching intensity at Abrolhos. However, the robustness of the model required for management purposes must be further (and regularly) operationally tested with new in situ and remote sensing data.\",\"bibtype\":\"article\",\"author\":\"Krug, Lilian Anne and Gherardi, Douglas Francisco Marcolino and Stech, José Luís and Leão, Zelinda Margarida Andrade Nery and Kikuchi, Ruy Kenji Papa and Hruschka, Estevam Rafael and Suggett, David John\",\"doi\":\"10.1016/j.envsoft.2013.01.003\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {The construction of causal networks to estimate coral bleaching intensity},\\n type = {article},\\n year = {2013},\\n keywords = {AGRRA,Atlantic and Gulf Rapid Reef Assessment,BN,BNPC,BSST,Bayesian network,Bayesian networks,Belief Network Power Constructor,CI,CPT,Coral bleaching,Coral reef,DAG,EM,Environmental variability,K490,MEI,MaxSST,PCA,PPT,Remote sensing,SST,SSTAc5d,South Atlantic coral reefs,U,V,best sea surface temperature,conditional independence,conditional probabilities table,diffuse light attenuation coefficient at 490 nm,directed acyclic graph,expectation–maximization,maximum sea surface temperature,mean surface wind fields,meridional wind,multivariate El Niño index,principal component analysis,rain precipitation,sea surface temperature,sea surface temperature accumulated in five days,zonal wind,|W|},\\n pages = {157-167},\\n volume = {42},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000121},\\n month = {4},\\n id = {4a097128-e62a-3c7b-ad37-6b51838d86f0},\\n created = {2015-04-11T17:55:10.000Z},\\n accessed = {2015-02-27},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Current metrics for predicting bleaching episodes, e.g. NOAA's Coral Reef Watch Program, do not seem to apply well to Brazil's marginal reefs located in Bahia state and alternative predictive approaches must be sought for effective long term management. Bleaching occurrences at Abrolhos have been observed since the 1990s but with a much lower frequency/extent than for other reef systems worldwide. We constructed a Bayesian Belief Network (BN) to back-predict the intensity of bleaching events and learn how local and regional scale forcing factors interact to enhance or alleviate coral bleaching specific to Abrolhos. Bleaching intensity data were collected for several reef sites across Bahia state coast (∼12°–20°S; 37°–40°W) during the austral summer 1994–2005 and compared to environmental data: sea surface temperature (SST), diffuse light attenuation coefficient at 490 nm (K490), rain precipitation, wind velocities, and El Niño Southern Oscillation (ENSO) proxies. Conditional independence tests were calculated to produce four specialized BNs, each with specific factors that likely regulate bleaching intensity. All specialized BNs identified that a five-day accumulated SST proxy (SSTAc5d) was the exclusive parent node for coral bleaching producing a total predictive rate of 88% based on SSTAc5d state. When SSTAc5d was simulated as unknown, the Thermal-Eolic Resultant BN kept the total predictive rate of 88%. Our approach has produced initial means to predict beaching intensity at Abrolhos. However, the robustness of the model required for management purposes must be further (and regularly) operationally tested with new in situ and remote sensing data.},\\n bibtype = {article},\\n author = {Krug, Lilian Anne and Gherardi, Douglas Francisco Marcolino and Stech, José Luís and Leão, Zelinda Margarida Andrade Nery and Kikuchi, Ruy Kenji Papa and Hruschka, Estevam Rafael and Suggett, David John},\\n doi = {10.1016/j.envsoft.2013.01.003},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Krug,  L., A.\",\"Gherardi,  D., F., M.\",\"Stech,  J., L.\",\"Leão,  Z., M., A., N.\",\"Kikuchi,  R., K., P.\",\"Hruschka,  E., R.\",\"Suggett,  D., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000121\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013\",\"role\":\"author\",\"keyword\":[\"AGRRA\",\"Atlantic and Gulf Rapid Reef Assessment\",\"BN\",\"BNPC\",\"BSST\",\"Bayesian network\",\"Bayesian networks\",\"Belief Network Power Constructor\",\"CI\",\"CPT\",\"Coral bleaching\",\"Coral reef\",\"DAG\",\"EM\",\"Environmental variability\",\"K490\",\"MEI\",\"MaxSST\",\"PCA\",\"PPT\",\"Remote sensing\",\"SST\",\"SSTAc5d\",\"South Atlantic coral reefs\",\"U\",\"V\",\"best sea surface temperature\",\"conditional independence\",\"conditional probabilities table\",\"diffuse light attenuation coefficient at 490 nm\",\"directed acyclic graph\",\"expectation–maximization\",\"maximum sea surface temperature\",\"mean surface wind fields\",\"meridional wind\",\"multivariate El Niño index\",\"principal component analysis\",\"rain precipitation\",\"sea surface temperature\",\"sea surface temperature accumulated in five days\",\"zonal wind\",\"|W|\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Belief network models of land manager decisions and land use change\",\"type\":\"article\",\"year\":\"2002\",\"keywords\":\"conflict resolution, conservation, decision models\",\"pages\":\"1-23\",\"volume\":\"65\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\",\"month\":\"5\",\"id\":\"b0ff7057-ddd3-325a-b3b4-c0b07cdab630\",\"created\":\"2015-04-11T17:55:11.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.\",\"bibtype\":\"article\",\"author\":\"Bacon, P.J. and Cain, J.D. and Howard, D.C.\",\"doi\":\"10.1006/jema.2001.0507\",\"journal\":\"Journal of Environmental Management\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Belief network models of land manager decisions and land use change},\\n type = {article},\\n year = {2002},\\n keywords = {conflict resolution, conservation, decision models},\\n pages = {1-23},\\n volume = {65},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},\\n month = {5},\\n id = {b0ff7057-ddd3-325a-b3b4-c0b07cdab630},\\n created = {2015-04-11T17:55:11.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},\\n bibtype = {article},\\n author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},\\n doi = {10.1006/jema.2001.0507},\\n journal = {Journal of Environmental Management},\\n number = {1}\\n}\",\"author_short\":[\"Bacon,  P.\",\"Cain,  J.\",\"Howard,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\",\"role\":\"author\",\"keyword\":[\"conflict resolution\",\"conservation\",\"decision models\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A belief network approach to optimization and parameter estimation: application to resource and environmental management\",\"type\":\"article\",\"year\":\"1998\",\"keywords\":\"Bayesian methods,Belief networks,Environmental policies,Hybrid models,Optimization,Parameter estimation,Probabilistic models,Resource management,Water quality\",\"pages\":\"135-163\",\"volume\":\"101\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0004370298000101\",\"month\":\"5\",\"id\":\"a8d856d9-f8bc-359d-8fb6-63d912a186ee\",\"created\":\"2015-04-11T18:33:33.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"An approach to use Bayesian belief networks in optimization is presented, with an illustration on resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of that model. The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various policy options. Also multiobjective optimization is possible. The approach is illustrated with an example on cost-effective management of river water quality.\",\"bibtype\":\"article\",\"author\":\"Vans, Olli\",\"doi\":\"10.1016/S0004-3702(98)00010-1\",\"journal\":\"Artificial Intelligence\",\"number\":\"1-2\",\"bibtex\":\"@article{\\n title = {A belief network approach to optimization and parameter estimation: application to resource and environmental management},\\n type = {article},\\n year = {1998},\\n keywords = {Bayesian methods,Belief networks,Environmental policies,Hybrid models,Optimization,Parameter estimation,Probabilistic models,Resource management,Water quality},\\n pages = {135-163},\\n volume = {101},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0004370298000101},\\n month = {5},\\n id = {a8d856d9-f8bc-359d-8fb6-63d912a186ee},\\n created = {2015-04-11T18:33:33.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {An approach to use Bayesian belief networks in optimization is presented, with an illustration on resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of that model. The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various policy options. Also multiobjective optimization is possible. The approach is illustrated with an example on cost-effective management of river water quality.},\\n bibtype = {article},\\n author = {Vans, Olli},\\n doi = {10.1016/S0004-3702(98)00010-1},\\n journal = {Artificial Intelligence},\\n number = {1-2}\\n}\",\"author_short\":[\"Vans,  O.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0004370298000101\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998\",\"role\":\"author\",\"keyword\":[\"Bayesian methods\",\"Belief networks\",\"Environmental policies\",\"Hybrid models\",\"Optimization\",\"Parameter estimation\",\"Probabilistic models\",\"Resource management\",\"Water quality\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Reflections on the use of Bayesian belief networks for adaptive management.\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayes Theorem,European Union,Water Supply\",\"pages\":\"1025-36\",\"volume\":\"88\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479707001922\",\"month\":\"9\",\"id\":\"40d1bc21-002a-3bc1-a529-ccbcbef80351\",\"created\":\"2015-04-11T18:33:33.000Z\",\"accessed\":\"2015-03-20\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers' experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.\",\"bibtype\":\"article\",\"author\":\"Henriksen, Hans Jørgen and Barlebo, Heidi Christiansen\",\"doi\":\"10.1016/j.jenvman.2007.05.009\",\"journal\":\"Journal of environmental management\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Reflections on the use of Bayesian belief networks for adaptive management.},\\n type = {article},\\n year = {2008},\\n keywords = {Bayes Theorem,European Union,Water Supply},\\n pages = {1025-36},\\n volume = {88},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479707001922},\\n month = {9},\\n id = {40d1bc21-002a-3bc1-a529-ccbcbef80351},\\n created = {2015-04-11T18:33:33.000Z},\\n accessed = {2015-03-20},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers' experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.},\\n bibtype = {article},\\n author = {Henriksen, Hans Jørgen and Barlebo, Heidi Christiansen},\\n doi = {10.1016/j.jenvman.2007.05.009},\\n journal = {Journal of environmental management},\\n number = {4}\\n}\",\"author_short\":[\"Henriksen,  H., J.\",\"Barlebo,  H., C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479707001922\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"European Union\",\"Water Supply\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement\",\"pages\":\"90-103\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\",\"month\":\"8\",\"id\":\"aad23f85-469d-3656-8244-34b843ea5b87\",\"created\":\"2015-04-11T18:33:34.000Z\",\"accessed\":\"2015-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.\",\"bibtype\":\"article\",\"author\":\"Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele\",\"doi\":\"10.1016/j.envsoft.2013.03.001\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},\\n pages = {90-103},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},\\n month = {8},\\n id = {aad23f85-469d-3656-8244-34b843ea5b87},\\n created = {2015-04-11T18:33:34.000Z},\\n accessed = {2015-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},\\n bibtype = {article},\\n author = {Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},\\n doi = {10.1016/j.envsoft.2013.03.001},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Portoghese,  I.\",\"D'Agostino,  D.\",\"Giordano,  R.\",\"Scardigno,  A.\",\"Apollonio,  C.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Networks\",\"Conflict mitigation\",\"Groundwater protection policy\",\"Stakeholder involvement\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Adaptive management,Bayesian belief network,Decision support,Queensland,Rangeland management,State and transition model\",\"pages\":\"23-34\",\"volume\":\"99\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0308521X08000966\",\"month\":\"12\",\"id\":\"60306c81-7a67-3eae-b843-225b6347b7c0\",\"created\":\"2015-04-11T18:33:34.000Z\",\"accessed\":\"2015-04-01\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"State and transition models provide a simple and versatile way of describing vegetation dynamics in rangelands. However, state and transition models are traditionally descriptive, which has limited their practical application to rangeland management decision support. This paper demonstrates an approach to rangeland management decision support that combines a state and transition model with a Bayesian belief network to provide a relatively simple and updatable rangeland dynamics model that can accommodate uncertainty and be used for scenario, diagnostic, and sensitivity analysis. A state and transition model, developed by the authors for subtropical grassland in south-east Queensland, Australia, is used as an example. From the state and transition model, an influence diagram was built to show the possible transitions among states and the factors influencing each transition. The influence diagram was populated with probabilities to produce a predictive model in the form of a Bayesian belief network. The behaviour of the model was tested using scenario and sensitivity analysis, revealing that selective grazing, grazing pressure, and soil nutrition were believed to influence most transitions, while fire frequency and the frequency of good wet seasons were also important in some transitions. Overall, the integration of a state and transition model with a Bayesian belief network provided a useful way to utilise the knowledge embedded in a state and transition model for predictive purposes. Using a Bayesian belief network in the modelling approach allowed uncertainty and variability to be explicitly accommodated in the modelling process, and expert knowledge to be utilised in model development. The methods used also supported learning from monitoring data, thereby supporting adaptive rangeland management.\",\"bibtype\":\"article\",\"author\":\"Bashari, H. and Smith, C. and Bosch, O.J.H.\",\"doi\":\"10.1016/j.agsy.2008.09.003\",\"journal\":\"Agricultural Systems\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks},\\n type = {article},\\n year = {2008},\\n keywords = {Adaptive management,Bayesian belief network,Decision support,Queensland,Rangeland management,State and transition model},\\n pages = {23-34},\\n volume = {99},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X08000966},\\n month = {12},\\n id = {60306c81-7a67-3eae-b843-225b6347b7c0},\\n created = {2015-04-11T18:33:34.000Z},\\n accessed = {2015-04-01},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {State and transition models provide a simple and versatile way of describing vegetation dynamics in rangelands. However, state and transition models are traditionally descriptive, which has limited their practical application to rangeland management decision support. This paper demonstrates an approach to rangeland management decision support that combines a state and transition model with a Bayesian belief network to provide a relatively simple and updatable rangeland dynamics model that can accommodate uncertainty and be used for scenario, diagnostic, and sensitivity analysis. A state and transition model, developed by the authors for subtropical grassland in south-east Queensland, Australia, is used as an example. From the state and transition model, an influence diagram was built to show the possible transitions among states and the factors influencing each transition. The influence diagram was populated with probabilities to produce a predictive model in the form of a Bayesian belief network. The behaviour of the model was tested using scenario and sensitivity analysis, revealing that selective grazing, grazing pressure, and soil nutrition were believed to influence most transitions, while fire frequency and the frequency of good wet seasons were also important in some transitions. Overall, the integration of a state and transition model with a Bayesian belief network provided a useful way to utilise the knowledge embedded in a state and transition model for predictive purposes. Using a Bayesian belief network in the modelling approach allowed uncertainty and variability to be explicitly accommodated in the modelling process, and expert knowledge to be utilised in model development. The methods used also supported learning from monitoring data, thereby supporting adaptive rangeland management.},\\n bibtype = {article},\\n author = {Bashari, H. and Smith, C. and Bosch, O.J.H.},\\n doi = {10.1016/j.agsy.2008.09.003},\\n journal = {Agricultural Systems},\\n number = {1}\\n}\",\"author_short\":[\"Bashari,  H.\",\"Smith,  C.\",\"Bosch,  O.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0308521X08000966\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008\",\"role\":\"author\",\"keyword\":[\"Adaptive management\",\"Bayesian belief network\",\"Decision support\",\"Queensland\",\"Rangeland management\",\"State and transition model\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian belief modeling of climate change impacts for informing regional adaptation options\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs\",\"pages\":\"113-121\",\"volume\":\"44\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\",\"month\":\"6\",\"id\":\"ae659db2-aa4d-3a21-bab2-5227c2e85480\",\"created\":\"2015-04-11T18:33:35.000Z\",\"accessed\":\"2015-02-24\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.\",\"bibtype\":\"article\",\"author\":\"Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.\",\"doi\":\"10.1016/j.envsoft.2012.07.008\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},\\n type = {article},\\n year = {2013},\\n keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},\\n pages = {113-121},\\n volume = {44},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},\\n month = {6},\\n id = {ae659db2-aa4d-3a21-bab2-5227c2e85480},\\n created = {2015-04-11T18:33:35.000Z},\\n accessed = {2015-02-24},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},\\n bibtype = {article},\\n author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},\\n doi = {10.1016/j.envsoft.2012.07.008},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Richards,  R.\",\"Sanó,  M.\",\"Roiko,  A.\",\"Carter,  R.\",\"Bussey,  M.\",\"Matthews,  J.\",\"Smith,  T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\",\"role\":\"author\",\"keyword\":[\"Adaptation\",\"Bayesian Belief Networks\",\"Climate change\",\"Group-model building\",\"Stakeholder beliefs\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Aquifer,Bayesian belief networks,Groundwater modelling,Integrated assessment,Mancha Occidental,Participatory modelling\",\"pages\":\"1439-1449\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481520800220X\",\"month\":\"11\",\"id\":\"27f510ec-0ee6-3836-ba11-331e4c3ce528\",\"created\":\"2015-04-11T18:33:35.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Participatory methods provide an increasingly accepted path to integrated assessment. This paper reflects on the role of two participatory modelling initiatives implemented in a highly conflictive setting: the Mancha Occidental aquifer, Spain. The methodologies are described within the context of the case study, examining their potential relevance to integrated assessment from a conceptual standpoint. The strengths and weaknesses of each approach are analysed in absolute and relative terms, attending to the different stages of the modelling process. The focus then shifts to explore the implications of this work within the context of participatory integrated assessment and scenario analysis. This serves the purpose of establishing the reasons why the tools have been useful in the eyes of stakeholders, and how the case-specific findings of this project may be relevant to other settings.\",\"bibtype\":\"article\",\"author\":\"Martínez-Santos, P. and Henriksen, H.J. and Zorrilla, P. and Martínez-Alfaro, P.E.\",\"doi\":\"10.1016/j.envsoft.2008.11.011\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain},\\n type = {article},\\n year = {2010},\\n keywords = {Aquifer,Bayesian belief networks,Groundwater modelling,Integrated assessment,Mancha Occidental,Participatory modelling},\\n pages = {1439-1449},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481520800220X},\\n month = {11},\\n id = {27f510ec-0ee6-3836-ba11-331e4c3ce528},\\n created = {2015-04-11T18:33:35.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Participatory methods provide an increasingly accepted path to integrated assessment. This paper reflects on the role of two participatory modelling initiatives implemented in a highly conflictive setting: the Mancha Occidental aquifer, Spain. The methodologies are described within the context of the case study, examining their potential relevance to integrated assessment from a conceptual standpoint. The strengths and weaknesses of each approach are analysed in absolute and relative terms, attending to the different stages of the modelling process. The focus then shifts to explore the implications of this work within the context of participatory integrated assessment and scenario analysis. This serves the purpose of establishing the reasons why the tools have been useful in the eyes of stakeholders, and how the case-specific findings of this project may be relevant to other settings.},\\n bibtype = {article},\\n author = {Martínez-Santos, P. and Henriksen, H.J. and Zorrilla, P. and Martínez-Alfaro, P.E.},\\n doi = {10.1016/j.envsoft.2008.11.011},\\n journal = {Environmental Modelling & Software},\\n number = {11}\\n}\",\"author_short\":[\"Martínez-Santos,  P.\",\"Henriksen,  H.\",\"Zorrilla,  P.\",\"Martínez-Alfaro,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481520800220X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010\",\"role\":\"author\",\"keyword\":[\"Aquifer\",\"Bayesian belief networks\",\"Groundwater modelling\",\"Integrated assessment\",\"Mancha Occidental\",\"Participatory modelling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian belief network,Evolutionary optimization,Multi-objective,Uncertainty,Water resources management\",\"pages\":\"303-310\",\"volume\":\"24\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815208001527\",\"month\":\"3\",\"id\":\"a9ab7039-fc72-3b3b-a9fb-d02b3c6fb47d\",\"created\":\"2015-04-11T18:33:35.000Z\",\"accessed\":\"2015-02-19\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.\",\"bibtype\":\"article\",\"author\":\"Farmani, Raziyeh and Henriksen, Hans Jørgen and Savic, Dragan\",\"doi\":\"10.1016/j.envsoft.2008.08.005\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian belief network,Evolutionary optimization,Multi-objective,Uncertainty,Water resources management},\\n pages = {303-310},\\n volume = {24},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001527},\\n month = {3},\\n id = {a9ab7039-fc72-3b3b-a9fb-d02b3c6fb47d},\\n created = {2015-04-11T18:33:35.000Z},\\n accessed = {2015-02-19},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.},\\n bibtype = {article},\\n author = {Farmani, Raziyeh and Henriksen, Hans Jørgen and Savic, Dragan},\\n doi = {10.1016/j.envsoft.2008.08.005},\\n journal = {Environmental Modelling & Software},\\n number = {3}\\n}\",\"author_short\":[\"Farmani,  R.\",\"Henriksen,  H., J.\",\"Savic,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815208001527\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"Evolutionary optimization\",\"Multi-objective\",\"Uncertainty\",\"Water resources management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayes Theorem,Geographic Information Systems,Groundwater,Models, Theoretical\",\"pages\":\"136-46\",\"volume\":\"115\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479712005968\",\"month\":\"1\",\"day\":\"30\",\"id\":\"eb1d6109-7a14-3dea-87f7-7d525816fa8b\",\"created\":\"2015-04-11T18:33:36.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches.\",\"bibtype\":\"article\",\"author\":\"Giordano, Raffaele and D'Agostino, Daniela and Apollonio, Ciro and Lamaddalena, Nicola and Vurro, Michele\",\"doi\":\"10.1016/j.jenvman.2012.11.011\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.},\\n type = {article},\\n year = {2013},\\n keywords = {Bayes Theorem,Geographic Information Systems,Groundwater,Models, Theoretical},\\n pages = {136-46},\\n volume = {115},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479712005968},\\n month = {1},\\n day = {30},\\n id = {eb1d6109-7a14-3dea-87f7-7d525816fa8b},\\n created = {2015-04-11T18:33:36.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches.},\\n bibtype = {article},\\n author = {Giordano, Raffaele and D'Agostino, Daniela and Apollonio, Ciro and Lamaddalena, Nicola and Vurro, Michele},\\n doi = {10.1016/j.jenvman.2012.11.011},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Giordano,  R.\",\"D'Agostino,  D.\",\"Apollonio,  C.\",\"Lamaddalena,  N.\",\"Vurro,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479712005968\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Geographic Information Systems\",\"Groundwater\",\"Models\",\"Theoretical\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Artificial neural networks,Bayesian belief networks,Knowledge extraction,Net ecosystem metabolism\",\"pages\":\"1199-1210\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815211001022\",\"month\":\"10\",\"id\":\"9abb4fc4-588f-32bf-9854-9b2c13bed6e9\",\"created\":\"2015-04-11T18:33:36.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.\",\"bibtype\":\"article\",\"author\":\"Young, William A. and Millie, David F. and Weckman, Gary R. and Anderson, Jerone S. and Klarer, David M. and Fahnenstiel, Gary L.\",\"doi\":\"10.1016/j.envsoft.2011.04.004\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"10\",\"bibtex\":\"@article{\\n title = {Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network},\\n type = {article},\\n year = {2011},\\n keywords = {Artificial neural networks,Bayesian belief networks,Knowledge extraction,Net ecosystem metabolism},\\n pages = {1199-1210},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001022},\\n month = {10},\\n id = {9abb4fc4-588f-32bf-9854-9b2c13bed6e9},\\n created = {2015-04-11T18:33:36.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.},\\n bibtype = {article},\\n author = {Young, William A. and Millie, David F. and Weckman, Gary R. and Anderson, Jerone S. and Klarer, David M. and Fahnenstiel, Gary L.},\\n doi = {10.1016/j.envsoft.2011.04.004},\\n journal = {Environmental Modelling & Software},\\n number = {10}\\n}\",\"author_short\":[\"Young,  W., A.\",\"Millie,  D., F.\",\"Weckman,  G., R.\",\"Anderson,  J., S.\",\"Klarer,  D., M.\",\"Fahnenstiel,  G., L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815211001022\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011\",\"role\":\"author\",\"keyword\":[\"Artificial neural networks\",\"Bayesian belief networks\",\"Knowledge extraction\",\"Net ecosystem metabolism\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Belief Networks,Clean-up costs,Maritime traffic,Oil spill,Risk analysis,The Gulf of Finland\",\"pages\":\"61-71\",\"volume\":\"76\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0025326X13005821\",\"month\":\"11\",\"id\":\"f778c0e8-482c-32c1-8276-b92a0d3e2c33\",\"created\":\"2015-04-11T18:33:36.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).\",\"bibtype\":\"article\",\"author\":\"Montewka, Jakub and Weckström, Mia and Kujala, Pentti\",\"doi\":\"10.1016/j.marpolbul.2013.09.031\",\"journal\":\"Marine Pollution Bulletin\",\"number\":\"1-2\",\"bibtex\":\"@article{\\n title = {A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Belief Networks,Clean-up costs,Maritime traffic,Oil spill,Risk analysis,The Gulf of Finland},\\n pages = {61-71},\\n volume = {76},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13005821},\\n month = {11},\\n id = {f778c0e8-482c-32c1-8276-b92a0d3e2c33},\\n created = {2015-04-11T18:33:36.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).},\\n bibtype = {article},\\n author = {Montewka, Jakub and Weckström, Mia and Kujala, Pentti},\\n doi = {10.1016/j.marpolbul.2013.09.031},\\n journal = {Marine Pollution Bulletin},\\n number = {1-2}\\n}\",\"author_short\":[\"Montewka,  J.\",\"Weckström,  M.\",\"Kujala,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0025326X13005821\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Networks\",\"Clean-up costs\",\"Maritime traffic\",\"Oil spill\",\"Risk analysis\",\"The Gulf of Finland\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A review of Bayesian belief networks in ecosystem service modelling\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models\",\"pages\":\"1-11\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\",\"month\":\"8\",\"id\":\"0229274b-5eb8-3c13-82dd-e9f5691ae50a\",\"created\":\"2015-04-11T18:46:32.000Z\",\"accessed\":\"2015-02-10\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.\",\"bibtype\":\"article\",\"author\":\"Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.\",\"doi\":\"10.1016/j.envsoft.2013.03.011\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A review of Bayesian belief networks in ecosystem service modelling},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},\\n pages = {1-11},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},\\n month = {8},\\n id = {0229274b-5eb8-3c13-82dd-e9f5691ae50a},\\n created = {2015-04-11T18:46:32.000Z},\\n accessed = {2015-02-10},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},\\n bibtype = {article},\\n author = {Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},\\n doi = {10.1016/j.envsoft.2013.03.011},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Landuyt,  D.\",\"Broekx,  S.\",\"D'hondt,  R.\",\"Engelen,  G.\",\"Aertsens,  J.\",\"Goethals,  P., L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Ecosystem services\",\"Expert based systems\",\"Graphical models\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Belief Network,Expert knowledge,Risk assessment,Soil Framework directive,Soil compaction,Uncertainty\",\"pages\":\"56-68\",\"volume\":\"132\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0167198713000925\",\"month\":\"8\",\"id\":\"ec8cccf5-6295-358f-8c7f-855694c983ee\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil's vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland.\",\"bibtype\":\"article\",\"author\":\"Troldborg, Mads and Aalders, Inge and Towers, Willie and Hallett, Paul D. and McKenzie, Blair M. and Bengough, A. Glyn and Lilly, Allan and Ball, Bruce C. and Hough, Rupert L.\",\"doi\":\"10.1016/j.still.2013.05.005\",\"journal\":\"Soil and Tillage Research\",\"bibtex\":\"@article{\\n title = {Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Belief Network,Expert knowledge,Risk assessment,Soil Framework directive,Soil compaction,Uncertainty},\\n pages = {56-68},\\n volume = {132},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0167198713000925},\\n month = {8},\\n id = {ec8cccf5-6295-358f-8c7f-855694c983ee},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil's vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland.},\\n bibtype = {article},\\n author = {Troldborg, Mads and Aalders, Inge and Towers, Willie and Hallett, Paul D. and McKenzie, Blair M. and Bengough, A. Glyn and Lilly, Allan and Ball, Bruce C. and Hough, Rupert L.},\\n doi = {10.1016/j.still.2013.05.005},\\n journal = {Soil and Tillage Research}\\n}\",\"author_short\":[\"Troldborg,  M.\",\"Aalders,  I.\",\"Towers,  W.\",\"Hallett,  P., D.\",\"McKenzie,  B., M.\",\"Bengough,  A., G.\",\"Lilly,  A.\",\"Ball,  B., C.\",\"Hough,  R., L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0167198713000925\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Network\",\"Expert knowledge\",\"Risk assessment\",\"Soil Framework directive\",\"Soil compaction\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Good practice in Bayesian network modelling\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayes network,Bayesian belief network,Ecological models,Good modelling practice,Integration,Model evaluation\",\"pages\":\"134-145\",\"volume\":\"37\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001041\",\"month\":\"11\",\"id\":\"2b4fbce7-9e6c-3add-a5bb-c5edf47da7ec\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs) are increasingly being used to model environmental systems, in order to: integrate multiple issues and system components; utilise information from different sources; and handle missing data and uncertainty. BNs also have a modular architecture that facilitates iterative model development. For a model to be of value in generating and sharing knowledge or providing decision support, it must be built using good modelling practice. This paper provides guidelines to developing and evaluating Bayesian network models of environmental systems, and presents a case study habitat suitability model for juvenile Astacopsis gouldi, the giant freshwater crayfish of Tasmania. The guidelines entail clearly defining the model objectives and scope, and using a conceptual model of the system to form the structure of the BN, which should be parsimonious yet capture all key components and processes. After the states and conditional probabilities of all variables are defined, the BN should be assessed by a suite of quantitative and qualitative forms of model evaluation. All the assumptions, uncertainties, descriptions and reasoning for each node and linkage, data and information sources, and evaluation results must be clearly documented. Following these standards will enable the modelling process and the model itself to be transparent, credible and robust, within its given limitations.\",\"bibtype\":\"article\",\"author\":\"Chen, Serena H. and Pollino, Carmel A.\",\"doi\":\"10.1016/j.envsoft.2012.03.012\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Good practice in Bayesian network modelling},\\n type = {article},\\n year = {2012},\\n keywords = {Bayes network,Bayesian belief network,Ecological models,Good modelling practice,Integration,Model evaluation},\\n pages = {134-145},\\n volume = {37},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001041},\\n month = {11},\\n id = {2b4fbce7-9e6c-3add-a5bb-c5edf47da7ec},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs) are increasingly being used to model environmental systems, in order to: integrate multiple issues and system components; utilise information from different sources; and handle missing data and uncertainty. BNs also have a modular architecture that facilitates iterative model development. For a model to be of value in generating and sharing knowledge or providing decision support, it must be built using good modelling practice. This paper provides guidelines to developing and evaluating Bayesian network models of environmental systems, and presents a case study habitat suitability model for juvenile Astacopsis gouldi, the giant freshwater crayfish of Tasmania. The guidelines entail clearly defining the model objectives and scope, and using a conceptual model of the system to form the structure of the BN, which should be parsimonious yet capture all key components and processes. After the states and conditional probabilities of all variables are defined, the BN should be assessed by a suite of quantitative and qualitative forms of model evaluation. All the assumptions, uncertainties, descriptions and reasoning for each node and linkage, data and information sources, and evaluation results must be clearly documented. Following these standards will enable the modelling process and the model itself to be transparent, credible and robust, within its given limitations.},\\n bibtype = {article},\\n author = {Chen, Serena H. and Pollino, Carmel A.},\\n doi = {10.1016/j.envsoft.2012.03.012},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Chen,  S., H.\",\"Pollino,  C., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001041\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"chen-pollino-goodpracticeinbayesiannetworkmodelling-2012\",\"role\":\"author\",\"keyword\":[\"Bayes network\",\"Bayesian belief network\",\"Ecological models\",\"Good modelling practice\",\"Integration\",\"Model evaluation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes\",\"type\":\"article\",\"year\":\"1996\",\"keywords\":\"Bayesian belief networks,causal belief networks,diagnosis,expert systems,rulebased systems,uncertainty,wastewater treatment\",\"pages\":\"265-273\",\"volume\":\"10\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/0954181096000039\",\"month\":\"8\",\"id\":\"ac924305-ac28-37c9-90aa-5e5f4444ce33\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The need for computer-based diagnostic tools in wastewater management is outlined. Rule-based and probabilistic approaches to the development of diagnostic expert systems are critically reviewed, and it is demonstrated that the rule-based approach has serious limitations which make it unsuitable for diagnostic tasks under conditions of uncertainty. It is shown that Bayesian belief networks (BBNs), a probabilistic approach, has none of these limitations and is well-suited to diagnosis under uncertainty. The theory and application of BBNs are outlined and illustrated by a simple example based on a wastewater treatment plant. A brief case study is presented of the development of a full-scale BBN for the diagnosis of faults in a wastewater treatment plant. It is concluded that BBNs are far superior to rule-based systems in their ability to diagnose faults in complex systems like wastewater treatment processes, whose behaviour is inherently uncertain.\",\"bibtype\":\"article\",\"author\":\"Chong, H.G. and Walley, W.J.\",\"doi\":\"10.1016/0954-1810(96)00003-9\",\"journal\":\"Artificial Intelligence in Engineering\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes},\\n type = {article},\\n year = {1996},\\n keywords = {Bayesian belief networks,causal belief networks,diagnosis,expert systems,rulebased systems,uncertainty,wastewater treatment},\\n pages = {265-273},\\n volume = {10},\\n websites = {http://www.sciencedirect.com/science/article/pii/0954181096000039},\\n month = {8},\\n id = {ac924305-ac28-37c9-90aa-5e5f4444ce33},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The need for computer-based diagnostic tools in wastewater management is outlined. Rule-based and probabilistic approaches to the development of diagnostic expert systems are critically reviewed, and it is demonstrated that the rule-based approach has serious limitations which make it unsuitable for diagnostic tasks under conditions of uncertainty. It is shown that Bayesian belief networks (BBNs), a probabilistic approach, has none of these limitations and is well-suited to diagnosis under uncertainty. The theory and application of BBNs are outlined and illustrated by a simple example based on a wastewater treatment plant. A brief case study is presented of the development of a full-scale BBN for the diagnosis of faults in a wastewater treatment plant. It is concluded that BBNs are far superior to rule-based systems in their ability to diagnose faults in complex systems like wastewater treatment processes, whose behaviour is inherently uncertain.},\\n bibtype = {article},\\n author = {Chong, H.G. and Walley, W.J.},\\n doi = {10.1016/0954-1810(96)00003-9},\\n journal = {Artificial Intelligence in Engineering},\\n number = {3}\\n}\",\"author_short\":[\"Chong,  H.\",\"Walley,  W.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/0954181096000039\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"causal belief networks\",\"diagnosis\",\"expert systems\",\"rulebased systems\",\"uncertainty\",\"wastewater treatment\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement\",\"type\":\"article\",\"year\":\"2001\",\"keywords\":\"Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling\",\"pages\":\"29-42\",\"volume\":\"153\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\",\"month\":\"10\",\"id\":\"2a076313-dfae-38fb-b4b2-d549d498e92e\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.\",\"bibtype\":\"article\",\"author\":\"Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J\",\"doi\":\"10.1016/S0378-1127(01)00452-2\",\"journal\":\"Forest Ecology and Management\",\"number\":\"1-3\",\"bibtex\":\"@article{\\n title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},\\n type = {article},\\n year = {2001},\\n keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},\\n pages = {29-42},\\n volume = {153},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},\\n month = {10},\\n id = {2a076313-dfae-38fb-b4b2-d549d498e92e},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},\\n bibtype = {article},\\n author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},\\n doi = {10.1016/S0378-1127(01)00452-2},\\n journal = {Forest Ecology and Management},\\n number = {1-3}\\n}\",\"author_short\":[\"Marcot,  B., G.\",\"Holthausen,  R., S.\",\"Raphael,  M., G.\",\"Rowland,  M., M.\",\"Wisdom,  M., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Bayesian statistics\",\"Columbia River\",\"Fish modeling\",\"Interior Columbia basin\",\"Population viability\",\"Wildlife modeling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using the integrated ecosystem assessment framework to build consensus and transfer information to managers\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian Belief Networks,Conceptual ecological models,EBM-DPSER,Ecosystem-based management,Integrated ecosystem assessments,South Florida\",\"pages\":\"11-25\",\"volume\":\"44\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1470160X14001265\",\"month\":\"9\",\"id\":\"91133e08-bba3-37b8-abb3-99a57aca3fa1\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-03-24\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Ecosystem-based management is widely regarded as a method to improve the way we manage our coastal marine resources and ecosystems. Effective ecosystem-based management relies upon synthesizing our scientific knowledge and transferring this knowledge into management actions. Integrated ecosystem assessment is a framework to conduct this scientific synthesis and transfer information to resource managers. Portions of the framework were applied to build consensus on the focal ecosystem components and processes that are characteristic of a sustainable South Florida coastal ecosystem that is producing ecosystem services at the level society desires. Consensus was developed through facilitated meetings that aimed to conceptualize the ecosystem, develop ecosystem indicators, and conduct risk analysis. Resource managers, researchers, academics, and non-governmental organizations participated in these meetings and contributed to the synthesis of science and a myriad of science communications to transfer information to decision makers and the public. A proof of concept Bayesian Belief Network was developed to explore integrating the results of this assessment into an interactive management scenario evaluation tool. The four year effort resulted in the development of a research and management coordination network in South Florida that should provide the foundation for implementing ecosystem-based resource management across multiple agencies.\",\"bibtype\":\"article\",\"author\":\"Fletcher, Pamela J. and Kelble, Christopher R. and Nuttle, William K. and Kiker, Gregory A.\",\"doi\":\"10.1016/j.ecolind.2014.03.024\",\"journal\":\"Ecological Indicators\",\"bibtex\":\"@article{\\n title = {Using the integrated ecosystem assessment framework to build consensus and transfer information to managers},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian Belief Networks,Conceptual ecological models,EBM-DPSER,Ecosystem-based management,Integrated ecosystem assessments,South Florida},\\n pages = {11-25},\\n volume = {44},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X14001265},\\n month = {9},\\n id = {91133e08-bba3-37b8-abb3-99a57aca3fa1},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-03-24},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Ecosystem-based management is widely regarded as a method to improve the way we manage our coastal marine resources and ecosystems. Effective ecosystem-based management relies upon synthesizing our scientific knowledge and transferring this knowledge into management actions. Integrated ecosystem assessment is a framework to conduct this scientific synthesis and transfer information to resource managers. Portions of the framework were applied to build consensus on the focal ecosystem components and processes that are characteristic of a sustainable South Florida coastal ecosystem that is producing ecosystem services at the level society desires. Consensus was developed through facilitated meetings that aimed to conceptualize the ecosystem, develop ecosystem indicators, and conduct risk analysis. Resource managers, researchers, academics, and non-governmental organizations participated in these meetings and contributed to the synthesis of science and a myriad of science communications to transfer information to decision makers and the public. A proof of concept Bayesian Belief Network was developed to explore integrating the results of this assessment into an interactive management scenario evaluation tool. The four year effort resulted in the development of a research and management coordination network in South Florida that should provide the foundation for implementing ecosystem-based resource management across multiple agencies.},\\n bibtype = {article},\\n author = {Fletcher, Pamela J. and Kelble, Christopher R. and Nuttle, William K. and Kiker, Gregory A.},\\n doi = {10.1016/j.ecolind.2014.03.024},\\n journal = {Ecological Indicators}\\n}\",\"author_short\":[\"Fletcher,  P., J.\",\"Kelble,  C., R.\",\"Nuttle,  W., K.\",\"Kiker,  G., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1470160X14001265\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Networks\",\"Conceptual ecological models\",\"EBM-DPSER\",\"Ecosystem-based management\",\"Integrated ecosystem assessments\",\"South Florida\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian Belief Networks,Coastal management,Hydrography,Jellyfish,Periphylla,Stakeholders\",\"pages\":\"72-83\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0308597X13002893\",\"month\":\"5\",\"id\":\"a11badc8-0e7a-3e78-8a55-673f7d1c98b4\",\"created\":\"2015-04-11T18:46:33.000Z\",\"accessed\":\"2015-04-01\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The following article outlines of an assessment of the adaptive capacity of stakeholder groups in the Trondheimsfjord region to the impacts related to local changes in Periphylla periphylla (jellyfish) concentrations. This paper addresses the interaction between the socio-ecological system and the marine ecosystem and the management challenges inherent therein by focusing on a serious management problem that is occurring in several Norwegian fjords. This is the recent superabundance of the lower trophic level jellyfish species P. periphylla, which competes with commercial Norwegian fish species for a wide variety of pelagic organisms including redfeed (Calanus finmarchicus), a key species in the coastal ecosystem and a particularly important food item for all codfishes in coastal waters. P. periphylla has, however, also some properties that might make it a valuable new resource in Norwegian waters, namely its potential for being a new and abundant source of collagen. The question addressed here is how to manage this jellyfish species in a manner that is rational from both socio-political and ecological perspectives, exploring stakeholder perceptions concerning their adaptation options and capacity to implement these options to this new resource and management mitigation options based on a set of stakeholder driven future scenarios.\",\"bibtype\":\"article\",\"author\":\"Gjelsvik Tiller, Rachel and Mork, Jarle and Richards, Russell and Eisenhauer, Lionel and Liu, Yajie and Nakken, Jens-Fredrik and Borgersen, Åshild.L\",\"doi\":\"10.1016/j.marpol.2013.12.006\",\"journal\":\"Marine Policy\",\"bibtex\":\"@article{\\n title = {Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian Belief Networks,Coastal management,Hydrography,Jellyfish,Periphylla,Stakeholders},\\n pages = {72-83},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0308597X13002893},\\n month = {5},\\n id = {a11badc8-0e7a-3e78-8a55-673f7d1c98b4},\\n created = {2015-04-11T18:46:33.000Z},\\n accessed = {2015-04-01},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The following article outlines of an assessment of the adaptive capacity of stakeholder groups in the Trondheimsfjord region to the impacts related to local changes in Periphylla periphylla (jellyfish) concentrations. This paper addresses the interaction between the socio-ecological system and the marine ecosystem and the management challenges inherent therein by focusing on a serious management problem that is occurring in several Norwegian fjords. This is the recent superabundance of the lower trophic level jellyfish species P. periphylla, which competes with commercial Norwegian fish species for a wide variety of pelagic organisms including redfeed (Calanus finmarchicus), a key species in the coastal ecosystem and a particularly important food item for all codfishes in coastal waters. P. periphylla has, however, also some properties that might make it a valuable new resource in Norwegian waters, namely its potential for being a new and abundant source of collagen. The question addressed here is how to manage this jellyfish species in a manner that is rational from both socio-political and ecological perspectives, exploring stakeholder perceptions concerning their adaptation options and capacity to implement these options to this new resource and management mitigation options based on a set of stakeholder driven future scenarios.},\\n bibtype = {article},\\n author = {Gjelsvik Tiller, Rachel and Mork, Jarle and Richards, Russell and Eisenhauer, Lionel and Liu, Yajie and Nakken, Jens-Fredrik and Borgersen, Åshild.L},\\n doi = {10.1016/j.marpol.2013.12.006},\\n journal = {Marine Policy}\\n}\",\"author_short\":[\"Gjelsvik Tiller,  R.\",\"Mork,  J.\",\"Richards,  R.\",\"Eisenhauer,  L.\",\"Liu,  Y.\",\"Nakken,  J.\",\"Borgersen,  Å.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0308597X13002893\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian Belief Networks\",\"Coastal management\",\"Hydrography\",\"Jellyfish\",\"Periphylla\",\"Stakeholders\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Green spaces in the direct living environment and social contacts of the aging population\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Aging,Bayesian belief network,Green spaces,Living environment,Social contacts\",\"pages\":\"44-54\",\"volume\":\"129\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S016920461400125X\",\"month\":\"9\",\"id\":\"f4ed9030-bc5b-34a8-bf10-1e2619ae784d\",\"created\":\"2015-04-11T18:46:34.000Z\",\"accessed\":\"2014-11-28\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Green spaces in the living environment may provide a meeting place and support social contacts. When people get older they, in general, are less mobile and have more limited activity spaces. At the same time they are faced with smaller social networks due to social and health related changes. Green spaces in their direct living environment are therefore important to support their needs. The aim of this study was to better understand the nature of the relationship between various types of green spaces in the direct living environment and the extent and nature of social contacts of the aging generation, taking into account socio-demographics and other physical and social environmental characteristics. Data for this study were obtained from a survey about living surroundings from a national representative sample of 1501 persons in the age category of 60 years and over in the Netherlands conducted in 2009. The survey included both subjective and objective measurements of the direct living environment of the respondents. Specifically, a Bayesian belief network was used to formulate and estimate the direct and indirect relationships between the selected variables. Results show that social contacts among neighbors are mainly influenced by the availability of trees and grass and the perceived level of green. Green spaces support social contacts in the neighborhood. However, the safety and maintenance of the green spaces are also important; high quality green spaces support social contacts between neighbors and strengthen communities for the aging population.\",\"bibtype\":\"article\",\"author\":\"Kemperman, Astrid and Timmermans, Harry\",\"doi\":\"10.1016/j.landurbplan.2014.05.003\",\"journal\":\"Landscape and Urban Planning\",\"bibtex\":\"@article{\\n title = {Green spaces in the direct living environment and social contacts of the aging population},\\n type = {article},\\n year = {2014},\\n keywords = {Aging,Bayesian belief network,Green spaces,Living environment,Social contacts},\\n pages = {44-54},\\n volume = {129},\\n websites = {http://www.sciencedirect.com/science/article/pii/S016920461400125X},\\n month = {9},\\n id = {f4ed9030-bc5b-34a8-bf10-1e2619ae784d},\\n created = {2015-04-11T18:46:34.000Z},\\n accessed = {2014-11-28},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Green spaces in the living environment may provide a meeting place and support social contacts. When people get older they, in general, are less mobile and have more limited activity spaces. At the same time they are faced with smaller social networks due to social and health related changes. Green spaces in their direct living environment are therefore important to support their needs. The aim of this study was to better understand the nature of the relationship between various types of green spaces in the direct living environment and the extent and nature of social contacts of the aging generation, taking into account socio-demographics and other physical and social environmental characteristics. Data for this study were obtained from a survey about living surroundings from a national representative sample of 1501 persons in the age category of 60 years and over in the Netherlands conducted in 2009. The survey included both subjective and objective measurements of the direct living environment of the respondents. Specifically, a Bayesian belief network was used to formulate and estimate the direct and indirect relationships between the selected variables. Results show that social contacts among neighbors are mainly influenced by the availability of trees and grass and the perceived level of green. Green spaces support social contacts in the neighborhood. However, the safety and maintenance of the green spaces are also important; high quality green spaces support social contacts between neighbors and strengthen communities for the aging population.},\\n bibtype = {article},\\n author = {Kemperman, Astrid and Timmermans, Harry},\\n doi = {10.1016/j.landurbplan.2014.05.003},\\n journal = {Landscape and Urban Planning}\\n}\",\"author_short\":[\"Kemperman,  A.\",\"Timmermans,  H.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S016920461400125X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014\",\"role\":\"author\",\"keyword\":[\"Aging\",\"Bayesian belief network\",\"Green spaces\",\"Living environment\",\"Social contacts\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayes Theorem,Climate,Climate Change,Ecosystem,Estuaries,Eutrophication,Models, Theoretical,North Carolina,Water Quality\",\"pages\":\"107-15\",\"volume\":\"83\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0025326X14002148\",\"month\":\"6\",\"day\":\"15\",\"id\":\"6210ae43-abaf-357b-9e72-dc054e812bcb\",\"created\":\"2015-04-11T18:56:31.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions.\",\"bibtype\":\"article\",\"author\":\"Nojavan A, Farnaz and Qian, Song S and Paerl, Hans W and Reckhow, Kenneth H and Albright, Elizabeth A\",\"doi\":\"10.1016/j.marpolbul.2014.04.011\",\"journal\":\"Marine pollution bulletin\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.},\\n type = {article},\\n year = {2014},\\n keywords = {Bayes Theorem,Climate,Climate Change,Ecosystem,Estuaries,Eutrophication,Models, Theoretical,North Carolina,Water Quality},\\n pages = {107-15},\\n volume = {83},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X14002148},\\n month = {6},\\n day = {15},\\n id = {6210ae43-abaf-357b-9e72-dc054e812bcb},\\n created = {2015-04-11T18:56:31.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions.},\\n bibtype = {article},\\n author = {Nojavan A, Farnaz and Qian, Song S and Paerl, Hans W and Reckhow, Kenneth H and Albright, Elizabeth A},\\n doi = {10.1016/j.marpolbul.2014.04.011},\\n journal = {Marine pollution bulletin},\\n number = {1}\\n}\",\"author_short\":[\"Nojavan A,  F.\",\"Qian,  S., S.\",\"Paerl,  H., W.\",\"Reckhow,  K., H.\",\"Albright,  E., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0025326X14002148\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Climate\",\"Climate Change\",\"Ecosystem\",\"Estuaries\",\"Eutrophication\",\"Models\",\"Theoretical\",\"North Carolina\",\"Water Quality\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian decision analysis for environmental and resource management\",\"type\":\"article\",\"year\":\"1997\",\"keywords\":\"Bayesian inference,belief networks,decision analysis,influence diagrams,risk,uncertainty,value of information\",\"pages\":\"177-185\",\"volume\":\"12\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481529700008X\",\"month\":\"1\",\"id\":\"1fbcbc94-b930-34e8-afeb-2528dc5c3fac\",\"created\":\"2015-04-11T18:56:32.000Z\",\"accessed\":\"2015-03-03\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"During the last two decades, much of the theoretical and practical advances in Bayesian decision analysis have been closely linked to the adaptation of emerging new computational — usually Artificial Intelligence — techniques and to progress in computer software, respectively. This paper documents and discusses experience on the use of two recent network model approaches, influence diagrams and belief networks, and relates those approaches to decision trees. They both allow probabilistic, Bayesian studies with classical decision analytic concepts such as risk attitude analysis, value of information and control, multi-attribute analysis, and various structural analyses. The theory of influence diagrams dates back to the early 1980s, and a variety of commercial software are on market. Belief network is a more recent concept that is under process of finding its way to applications. Illustration on environmental and resource management is provided with examples on freshwater and fisheries studies.\",\"bibtype\":\"article\",\"author\":\"Varis, Olli\",\"doi\":\"10.1016/S1364-8152(97)00008-X\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"2-3\",\"bibtex\":\"@article{\\n title = {Bayesian decision analysis for environmental and resource management},\\n type = {article},\\n year = {1997},\\n keywords = {Bayesian inference,belief networks,decision analysis,influence diagrams,risk,uncertainty,value of information},\\n pages = {177-185},\\n volume = {12},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481529700008X},\\n month = {1},\\n id = {1fbcbc94-b930-34e8-afeb-2528dc5c3fac},\\n created = {2015-04-11T18:56:32.000Z},\\n accessed = {2015-03-03},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {During the last two decades, much of the theoretical and practical advances in Bayesian decision analysis have been closely linked to the adaptation of emerging new computational — usually Artificial Intelligence — techniques and to progress in computer software, respectively. This paper documents and discusses experience on the use of two recent network model approaches, influence diagrams and belief networks, and relates those approaches to decision trees. They both allow probabilistic, Bayesian studies with classical decision analytic concepts such as risk attitude analysis, value of information and control, multi-attribute analysis, and various structural analyses. The theory of influence diagrams dates back to the early 1980s, and a variety of commercial software are on market. Belief network is a more recent concept that is under process of finding its way to applications. Illustration on environmental and resource management is provided with examples on freshwater and fisheries studies.},\\n bibtype = {article},\\n author = {Varis, Olli},\\n doi = {10.1016/S1364-8152(97)00008-X},\\n journal = {Environmental Modelling & Software},\\n number = {2-3}\\n}\",\"author_short\":[\"Varis,  O.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481529700008X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997\",\"role\":\"author\",\"keyword\":[\"Bayesian inference\",\"belief networks\",\"decision analysis\",\"influence diagrams\",\"risk\",\"uncertainty\",\"value of information\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian belief network,Climate change,Conservation planning,Coral reef,Expert elicitation,Risk assessment\",\"pages\":\"64-72\",\"volume\":\"27\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0959378014000843\",\"month\":\"7\",\"id\":\"e6a03683-84ae-3be6-807c-9dfc0103c216\",\"created\":\"2015-04-11T19:07:35.000Z\",\"accessed\":\"2015-01-15\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian belief networks are finding increasing application in adaptive ecosystem management where data are limited and uncertainty is high. The combined effect of multiple stressors is one area where considerable uncertainty exists. Our study area, the Great Barrier Reef is simultaneously data-rich – concerning the physical and biological environment – and data-poor – concerning the effects of interacting stressors. We used a formal expert-elicitation process to obtain estimates of outcomes associated with a variety of scenarios that combined stressors both within and outside the control of local managers. There was much stronger consensus about certain stressor effects – such as between temperature anomalies and bleaching – than others, such as the relationship between water quality and coral cover. In general, the expert outlook for the Great Barrier Reef is pessimistic, with the potential for climate change effects potentially to overshadow the effects of local management actions.\",\"bibtype\":\"article\",\"author\":\"Ban, Stephen S. and Pressey, Robert L. and Graham, Nicholas A.J.\",\"doi\":\"10.1016/j.gloenvcha.2014.04.018\",\"journal\":\"Global Environmental Change\",\"bibtex\":\"@article{\\n title = {Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian belief network,Climate change,Conservation planning,Coral reef,Expert elicitation,Risk assessment},\\n pages = {64-72},\\n volume = {27},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0959378014000843},\\n month = {7},\\n id = {e6a03683-84ae-3be6-807c-9dfc0103c216},\\n created = {2015-04-11T19:07:35.000Z},\\n accessed = {2015-01-15},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian belief networks are finding increasing application in adaptive ecosystem management where data are limited and uncertainty is high. The combined effect of multiple stressors is one area where considerable uncertainty exists. Our study area, the Great Barrier Reef is simultaneously data-rich – concerning the physical and biological environment – and data-poor – concerning the effects of interacting stressors. We used a formal expert-elicitation process to obtain estimates of outcomes associated with a variety of scenarios that combined stressors both within and outside the control of local managers. There was much stronger consensus about certain stressor effects – such as between temperature anomalies and bleaching – than others, such as the relationship between water quality and coral cover. In general, the expert outlook for the Great Barrier Reef is pessimistic, with the potential for climate change effects potentially to overshadow the effects of local management actions.},\\n bibtype = {article},\\n author = {Ban, Stephen S. and Pressey, Robert L. and Graham, Nicholas A.J.},\\n doi = {10.1016/j.gloenvcha.2014.04.018},\\n journal = {Global Environmental Change}\\n}\",\"author_short\":[\"Ban,  S., S.\",\"Pressey,  R., L.\",\"Graham,  N., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0959378014000843\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network\",\"Climate change\",\"Conservation planning\",\"Coral reef\",\"Expert elicitation\",\"Risk assessment\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Adaptive management,Adaptive modelling,Bayesian Belief Network,Great Barrier Reef,Learning support,Water quality\",\"pages\":\"1291-1301\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002618\",\"month\":\"11\",\"id\":\"9e63a1d1-b78a-3e51-8c45-3f012125a461\",\"created\":\"2015-04-11T19:07:35.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The development and use of a Bayesian Belief Network (BBN) model, within an adaptive management process for the management of water quality in the Mackay Whitsunday region of Queensland, Australia is described. The management goal is firstly to set achievable targets for water quality entering the Great Barrier Reef lagoon from the Mackay Whitsunday natural resource management region and then secondly to define and implement a strategy to achieve these targets. The BBN serves as an adaptive framework that managers and scientists may use to articulate what they know about the managed system. It then provides a tool to guide where, when and what interventions (including research) are most likely to achieve management outcomes. Importantly the BBN provides a platform for collective learning. BBN estimates of total suspended sediment (TSS) loads and event mean concentrations (EMCs) were compared to observed data and results from current best practice models. The BBN estimates were reasonable relative to empirical observations. Example results from the BBN are thereafter used to illustrate the use of the model in estimating the likelihood of exceeding water quality targets with and without proposed actions to improve water quality. Example results are also used to illustrate what spatial or land use elements might contribute most to exceeding water quality targets. Finally key limitations of the tool are discussed and important learnings from the process are highlighted.\",\"bibtype\":\"article\",\"author\":\"Lynam, Tim and Drewry, John and Higham, Will and Mitchell, Carl\",\"doi\":\"10.1016/j.envsoft.2009.09.013\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia},\\n type = {article},\\n year = {2010},\\n keywords = {Adaptive management,Adaptive modelling,Bayesian Belief Network,Great Barrier Reef,Learning support,Water quality},\\n pages = {1291-1301},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002618},\\n month = {11},\\n id = {9e63a1d1-b78a-3e51-8c45-3f012125a461},\\n created = {2015-04-11T19:07:35.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The development and use of a Bayesian Belief Network (BBN) model, within an adaptive management process for the management of water quality in the Mackay Whitsunday region of Queensland, Australia is described. The management goal is firstly to set achievable targets for water quality entering the Great Barrier Reef lagoon from the Mackay Whitsunday natural resource management region and then secondly to define and implement a strategy to achieve these targets. The BBN serves as an adaptive framework that managers and scientists may use to articulate what they know about the managed system. It then provides a tool to guide where, when and what interventions (including research) are most likely to achieve management outcomes. Importantly the BBN provides a platform for collective learning. BBN estimates of total suspended sediment (TSS) loads and event mean concentrations (EMCs) were compared to observed data and results from current best practice models. The BBN estimates were reasonable relative to empirical observations. Example results from the BBN are thereafter used to illustrate the use of the model in estimating the likelihood of exceeding water quality targets with and without proposed actions to improve water quality. Example results are also used to illustrate what spatial or land use elements might contribute most to exceeding water quality targets. Finally key limitations of the tool are discussed and important learnings from the process are highlighted.},\\n bibtype = {article},\\n author = {Lynam, Tim and Drewry, John and Higham, Will and Mitchell, Carl},\\n doi = {10.1016/j.envsoft.2009.09.013},\\n journal = {Environmental Modelling & Software},\\n number = {11}\\n}\",\"author_short\":[\"Lynam,  T.\",\"Drewry,  J.\",\"Higham,  W.\",\"Mitchell,  C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002618\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010\",\"role\":\"author\",\"keyword\":[\"Adaptive management\",\"Adaptive modelling\",\"Bayesian Belief Network\",\"Great Barrier Reef\",\"Learning support\",\"Water quality\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Hailfinder: A Bayesian system for forecasting severe weather\",\"type\":\"article\",\"year\":\"1996\",\"keywords\":\"Bayesian,Belief networks,Elicitation,Intelligent systems,Meteorology,System design,Weather forecasting\",\"pages\":\"57-71\",\"volume\":\"12\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/0169207095006648\",\"month\":\"3\",\"id\":\"edb592f0-50e3-39c0-98f3-18b2f3c8b066\",\"created\":\"2015-04-11T19:07:35.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.\",\"bibtype\":\"article\",\"author\":\"Abramson, Bruce and Brown, John and Edwards, Ward and Murphy, Allan and Winkler, Robert L.\",\"doi\":\"10.1016/0169-2070(95)00664-8\",\"journal\":\"International Journal of Forecasting\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Hailfinder: A Bayesian system for forecasting severe weather},\\n type = {article},\\n year = {1996},\\n keywords = {Bayesian,Belief networks,Elicitation,Intelligent systems,Meteorology,System design,Weather forecasting},\\n pages = {57-71},\\n volume = {12},\\n websites = {http://www.sciencedirect.com/science/article/pii/0169207095006648},\\n month = {3},\\n id = {edb592f0-50e3-39c0-98f3-18b2f3c8b066},\\n created = {2015-04-11T19:07:35.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.},\\n bibtype = {article},\\n author = {Abramson, Bruce and Brown, John and Edwards, Ward and Murphy, Allan and Winkler, Robert L.},\\n doi = {10.1016/0169-2070(95)00664-8},\\n journal = {International Journal of Forecasting},\\n number = {1}\\n}\",\"author_short\":[\"Abramson,  B.\",\"Brown,  J.\",\"Edwards,  W.\",\"Murphy,  A.\",\"Winkler,  R., L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/0169207095006648\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996\",\"role\":\"author\",\"keyword\":[\"Bayesian\",\"Belief networks\",\"Elicitation\",\"Intelligent systems\",\"Meteorology\",\"System design\",\"Weather forecasting\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Afforestation,Bayesian belief network,China,Forest transition,Land use change,SLCP\",\"pages\":\"248-258\",\"volume\":\"36\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0264837713001555\",\"month\":\"1\",\"id\":\"952422ca-1136-3fed-b247-7519a9b7cd81\",\"created\":\"2015-04-11T19:07:36.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Strict enforcement of forest protection and massive afforestation campaigns have contributed to a significant increase in China's forest cover during the last 20 years. At the same time, demographic changes in rural areas due to changes in reproduction patterns and the emigration of younger population segments have affected land-use strategies. We identified proximate causes and underlying drivers that influence the decisions of farm households to plant trees on former cropland with Bayesian networks (BNs). BNs allow the incorporation of causal relationships in data analysis and can combine qualitative stakeholder knowledge with quantitative data. We defined the structure of the network with expert knowledge and in-depth discussions with land users. The network was calibrated and validated with data from a survey of 509 rural households in two upland areas of Yunnan Province in Southwest China. The results substantiate the influence of land endowments, labor availability and forest policies for switching from cropland to tree planting. State forest policies have constituted the main underlying driver to the forest transition in the past, but private afforestation activities increasingly dominate the expansion of tree cover. Farmers plant trees on private incentives mainly to cash in on the improved economic opportunities provided by tree crops, but tree planting also constitutes an important strategy to adjust to growing labor scarcities.\",\"bibtype\":\"article\",\"author\":\"Frayer, Jens and Sun, Zhanli and Müller, Daniel and Munroe, Darla K. and Xu, Jianchu\",\"doi\":\"10.1016/j.landusepol.2013.08.005\",\"journal\":\"Land Use Policy\",\"bibtex\":\"@article{\\n title = {Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks},\\n type = {article},\\n year = {2014},\\n keywords = {Afforestation,Bayesian belief network,China,Forest transition,Land use change,SLCP},\\n pages = {248-258},\\n volume = {36},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0264837713001555},\\n month = {1},\\n id = {952422ca-1136-3fed-b247-7519a9b7cd81},\\n created = {2015-04-11T19:07:36.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Strict enforcement of forest protection and massive afforestation campaigns have contributed to a significant increase in China's forest cover during the last 20 years. At the same time, demographic changes in rural areas due to changes in reproduction patterns and the emigration of younger population segments have affected land-use strategies. We identified proximate causes and underlying drivers that influence the decisions of farm households to plant trees on former cropland with Bayesian networks (BNs). BNs allow the incorporation of causal relationships in data analysis and can combine qualitative stakeholder knowledge with quantitative data. We defined the structure of the network with expert knowledge and in-depth discussions with land users. The network was calibrated and validated with data from a survey of 509 rural households in two upland areas of Yunnan Province in Southwest China. The results substantiate the influence of land endowments, labor availability and forest policies for switching from cropland to tree planting. State forest policies have constituted the main underlying driver to the forest transition in the past, but private afforestation activities increasingly dominate the expansion of tree cover. Farmers plant trees on private incentives mainly to cash in on the improved economic opportunities provided by tree crops, but tree planting also constitutes an important strategy to adjust to growing labor scarcities.},\\n bibtype = {article},\\n author = {Frayer, Jens and Sun, Zhanli and Müller, Daniel and Munroe, Darla K. and Xu, Jianchu},\\n doi = {10.1016/j.landusepol.2013.08.005},\\n journal = {Land Use Policy}\\n}\",\"author_short\":[\"Frayer,  J.\",\"Sun,  Z.\",\"Müller,  D.\",\"Munroe,  D., K.\",\"Xu,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0264837713001555\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014\",\"role\":\"author\",\"keyword\":[\"Afforestation\",\"Bayesian belief network\",\"China\",\"Forest transition\",\"Land use change\",\"SLCP\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian belief network (BBN),Black Sea,DPSIR,Eutrophication,Marine socio-ecological systems\",\"pages\":\"2927-2939\",\"volume\":\"220\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380008004420\",\"month\":\"11\",\"id\":\"9204e42d-e51a-375c-b9b1-7c0626665bcf\",\"created\":\"2015-04-11T19:07:36.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.\",\"bibtype\":\"article\",\"author\":\"Langmead, Olivia and McQuatters-Gollop, Abigail and Mee, Laurence D. and Friedrich, Jana and Gilbert, Alison J. and Gomoiu, Marian-Traian and Jackson, Emma L. and Knudsen, Ståle and Minicheva, Galina and Todorova, Valentina\",\"doi\":\"10.1016/j.ecolmodel.2008.09.011\",\"journal\":\"Ecological Modelling\",\"number\":\"21\",\"bibtex\":\"@article{\\n title = {Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian belief network (BBN),Black Sea,DPSIR,Eutrophication,Marine socio-ecological systems},\\n pages = {2927-2939},\\n volume = {220},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380008004420},\\n month = {11},\\n id = {9204e42d-e51a-375c-b9b1-7c0626665bcf},\\n created = {2015-04-11T19:07:36.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.},\\n bibtype = {article},\\n author = {Langmead, Olivia and McQuatters-Gollop, Abigail and Mee, Laurence D. and Friedrich, Jana and Gilbert, Alison J. and Gomoiu, Marian-Traian and Jackson, Emma L. and Knudsen, Ståle and Minicheva, Galina and Todorova, Valentina},\\n doi = {10.1016/j.ecolmodel.2008.09.011},\\n journal = {Ecological Modelling},\\n number = {21}\\n}\",\"author_short\":[\"Langmead,  O.\",\"McQuatters-Gollop,  A.\",\"Mee,  L., D.\",\"Friedrich,  J.\",\"Gilbert,  A., J.\",\"Gomoiu,  M.\",\"Jackson,  E., L.\",\"Knudsen,  S.\",\"Minicheva,  G.\",\"Todorova,  V.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380008004420\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian belief network (BBN)\",\"Black Sea\",\"DPSIR\",\"Eutrophication\",\"Marine socio-ecological systems\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Reducing the risk of house loss due to wildfires\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian Network,Community engagement,Fire management,Planning,Suppression,Wildfire\",\"pages\":\"12-25\",\"volume\":\"67\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214003776\",\"month\":\"5\",\"id\":\"dd85fb82-33ed-3112-9eaa-a0b2c1b5186e\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors.\",\"bibtype\":\"article\",\"author\":\"Penman, T.D. and Nicholson, A.E. and Bradstock, R.A. and Collins, L. and Penman, S.H. and Price, O.F.\",\"doi\":\"10.1016/j.envsoft.2014.12.020\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Reducing the risk of house loss due to wildfires},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian Network,Community engagement,Fire management,Planning,Suppression,Wildfire},\\n pages = {12-25},\\n volume = {67},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003776},\\n month = {5},\\n id = {dd85fb82-33ed-3112-9eaa-a0b2c1b5186e},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors.},\\n bibtype = {article},\\n author = {Penman, T.D. and Nicholson, A.E. and Bradstock, R.A. and Collins, L. and Penman, S.H. and Price, O.F.},\\n doi = {10.1016/j.envsoft.2014.12.020},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Penman,  T.\",\"Nicholson,  A.\",\"Bradstock,  R.\",\"Collins,  L.\",\"Penman,  S.\",\"Price,  O.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214003776\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian Network\",\"Community engagement\",\"Fire management\",\"Planning\",\"Suppression\",\"Wildfire\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Adoption,Bayesian Networks,Natural resource management,Policy development\",\"pages\":\"52-65\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815210000915\",\"month\":\"1\",\"id\":\"d2c4459f-07d8-3c2d-bbfd-ea3722ab6385\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Influencing the management of private landholders is a key element of improving the condition of Australia’s natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.\",\"bibtype\":\"article\",\"author\":\"Ticehurst, J.L and Curtis, A. and Merritt, W.S.\",\"doi\":\"10.1016/j.envsoft.2010.03.032\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation},\\n type = {article},\\n year = {2011},\\n keywords = {Adoption,Bayesian Networks,Natural resource management,Policy development},\\n pages = {52-65},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000915},\\n month = {1},\\n id = {d2c4459f-07d8-3c2d-bbfd-ea3722ab6385},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Influencing the management of private landholders is a key element of improving the condition of Australia’s natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.},\\n bibtype = {article},\\n author = {Ticehurst, J.L and Curtis, A. and Merritt, W.S.},\\n doi = {10.1016/j.envsoft.2010.03.032},\\n journal = {Environmental Modelling & Software},\\n number = {1}\\n}\",\"author_short\":[\"Ticehurst,  J.\",\"Curtis,  A.\",\"Merritt,  W.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815210000915\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011\",\"role\":\"author\",\"keyword\":[\"Adoption\",\"Bayesian Networks\",\"Natural resource management\",\"Policy development\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian hierarchical modeling,Bayesian network,Dreissenid invasion,Observation error,Phosphorus targets,Saginaw Bay,Water quality criteria\",\"pages\":\"90-100\",\"volume\":\"57\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214000619\",\"month\":\"7\",\"id\":\"ec29901c-feb6-3c2b-acdb-e93991455248\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-02-18\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.\",\"bibtype\":\"article\",\"author\":\"Cha, YoonKyung and Stow, Craig A.\",\"doi\":\"10.1016/j.envsoft.2014.02.010\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian hierarchical modeling,Bayesian network,Dreissenid invasion,Observation error,Phosphorus targets,Saginaw Bay,Water quality criteria},\\n pages = {90-100},\\n volume = {57},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214000619},\\n month = {7},\\n id = {ec29901c-feb6-3c2b-acdb-e93991455248},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-02-18},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.},\\n bibtype = {article},\\n author = {Cha, YoonKyung and Stow, Craig A.},\\n doi = {10.1016/j.envsoft.2014.02.010},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Cha,  Y.\",\"Stow,  C., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214000619\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian hierarchical modeling\",\"Bayesian network\",\"Dreissenid invasion\",\"Observation error\",\"Phosphorus targets\",\"Saginaw Bay\",\"Water quality criteria\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Prediction analysis of a wastewater treatment system using a Bayesian network\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis\",\"pages\":\"140-150\",\"volume\":\"40\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\",\"month\":\"2\",\"id\":\"07511849-6753-38c4-9bdb-aeb95cf6d63c\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.\",\"bibtype\":\"article\",\"author\":\"Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng\",\"doi\":\"10.1016/j.envsoft.2012.08.011\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Prediction analysis of a wastewater treatment system using a Bayesian network},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},\\n pages = {140-150},\\n volume = {40},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},\\n month = {2},\\n id = {07511849-6753-38c4-9bdb-aeb95cf6d63c},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},\\n bibtype = {article},\\n author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},\\n doi = {10.1016/j.envsoft.2012.08.011},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Li,  D.\",\"Yang,  H., Z.\",\"Liang,  X., F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Inference\",\"Modified sequencing batch reactor\",\"Prediction analysis\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Aquatic ecology,Bayesian networks,Discretization,Ecological community,Macroinvertebrates,TITAN,Thresholds\",\"pages\":\"36-45\",\"volume\":\"66\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214003764\",\"month\":\"4\",\"id\":\"e08492c9-2d60-3b06-bd97-9fccb755eef8\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-01-22\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The TITAN-based method may be used together with expert opinion.\",\"bibtype\":\"article\",\"author\":\"Lucena-Moya, Paloma and Brawata, Renee and Kath, Jarrod and Harrison, Evan and ElSawah, Sondoss and Dyer, Fiona\",\"doi\":\"10.1016/j.envsoft.2014.12.019\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach},\\n type = {article},\\n year = {2015},\\n keywords = {Aquatic ecology,Bayesian networks,Discretization,Ecological community,Macroinvertebrates,TITAN,Thresholds},\\n pages = {36-45},\\n volume = {66},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003764},\\n month = {4},\\n id = {e08492c9-2d60-3b06-bd97-9fccb755eef8},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-01-22},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The TITAN-based method may be used together with expert opinion.},\\n bibtype = {article},\\n author = {Lucena-Moya, Paloma and Brawata, Renee and Kath, Jarrod and Harrison, Evan and ElSawah, Sondoss and Dyer, Fiona},\\n doi = {10.1016/j.envsoft.2014.12.019},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Lucena-Moya,  P.\",\"Brawata,  R.\",\"Kath,  J.\",\"Harrison,  E.\",\"ElSawah,  S.\",\"Dyer,  F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214003764\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015\",\"role\":\"author\",\"keyword\":[\"Aquatic ecology\",\"Bayesian networks\",\"Discretization\",\"Ecological community\",\"Macroinvertebrates\",\"TITAN\",\"Thresholds\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian networks,Land use decisions,Land use modeling,Participatory modeling\",\"pages\":\"222-233\",\"volume\":\"52\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213002570\",\"month\":\"2\",\"id\":\"49e939ec-75cf-3c6b-a23e-c8bfb76b0ac8\",\"created\":\"2015-04-11T19:51:55.000Z\",\"accessed\":\"2015-02-23\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors' knowledge into a spatially explicit BN. A structured experts' process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors' characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.\",\"bibtype\":\"article\",\"author\":\"Celio, Enrico and Koellner, Thomas and Grêt-Regamey, Adrienne\",\"doi\":\"10.1016/j.envsoft.2013.10.014\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian networks,Land use decisions,Land use modeling,Participatory modeling},\\n pages = {222-233},\\n volume = {52},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002570},\\n month = {2},\\n id = {49e939ec-75cf-3c6b-a23e-c8bfb76b0ac8},\\n created = {2015-04-11T19:51:55.000Z},\\n accessed = {2015-02-23},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors' knowledge into a spatially explicit BN. A structured experts' process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors' characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.},\\n bibtype = {article},\\n author = {Celio, Enrico and Koellner, Thomas and Grêt-Regamey, Adrienne},\\n doi = {10.1016/j.envsoft.2013.10.014},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Celio,  E.\",\"Koellner,  T.\",\"Grêt-Regamey,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213002570\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Land use decisions\",\"Land use modeling\",\"Participatory modeling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian networks,Endangered species,Hypotheses\",\"pages\":\"37-59\",\"volume\":\"201\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\",\"month\":\"2\",\"id\":\"5d0ffe0d-cdb0-326f-9f54-ba86da63d807\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.\",\"bibtype\":\"article\",\"author\":\"Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.\",\"doi\":\"10.1016/j.ecolmodel.2006.07.032\",\"journal\":\"Ecological Modelling\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian networks,Endangered species,Hypotheses},\\n pages = {37-59},\\n volume = {201},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},\\n month = {2},\\n id = {5d0ffe0d-cdb0-326f-9f54-ba86da63d807},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},\\n bibtype = {article},\\n author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},\\n doi = {10.1016/j.ecolmodel.2006.07.032},\\n journal = {Ecological Modelling},\\n number = {1}\\n}\",\"author_short\":[\"Pollino,  C., A.\",\"White,  A., K.\",\"Hart,  B., T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Endangered species\",\"Hypotheses\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation\",\"pages\":\"641-651\",\"volume\":\"221\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\",\"month\":\"2\",\"id\":\"efbda3bc-67d8-309a-8188-fee0c8a80d3b\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.\",\"bibtype\":\"article\",\"author\":\"Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine\",\"doi\":\"10.1016/j.ecolmodel.2009.11.012\",\"journal\":\"Ecological Modelling\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},\\n type = {article},\\n year = {2010},\\n keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},\\n pages = {641-651},\\n volume = {221},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},\\n month = {2},\\n id = {efbda3bc-67d8-309a-8188-fee0c8a80d3b},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},\\n bibtype = {article},\\n author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},\\n doi = {10.1016/j.ecolmodel.2009.11.012},\\n journal = {Ecological Modelling},\\n number = {4}\\n}\",\"author_short\":[\"Johnson,  S.\",\"Mengersen,  K.\",\"de Waal,  A.\",\"Marnewick,  K.\",\"Cilliers,  D.\",\"Houser,  A., M.\",\"Boast,  L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\",\"role\":\"author\",\"keyword\":[\"Acinonyx jubatus\",\"Bayesian network\",\"Cheetah metapopulation\",\"IBNDC\",\"Iterative approach\",\"Predator human conflict\",\"Relocation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A meta-assessment for elasmobranchs based on dietary data and Bayesian networks\",\"type\":\"article\",\"year\":\"2002\",\"keywords\":\"Bayesian networks,Elasmobranchs,Fisheries management,Food webs,Threatened species\",\"pages\":\"197-211\",\"volume\":\"1\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1470160X02000055\",\"month\":\"3\",\"id\":\"6cfb406e-23d4-39ad-8c18-503cdcd07905\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.\",\"bibtype\":\"article\",\"author\":\"Hammond, T.R and Ellis, J.R\",\"doi\":\"10.1016/S1470-160X(02)00005-5\",\"journal\":\"Ecological Indicators\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {A meta-assessment for elasmobranchs based on dietary data and Bayesian networks},\\n type = {article},\\n year = {2002},\\n keywords = {Bayesian networks,Elasmobranchs,Fisheries management,Food webs,Threatened species},\\n pages = {197-211},\\n volume = {1},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X02000055},\\n month = {3},\\n id = {6cfb406e-23d4-39ad-8c18-503cdcd07905},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.},\\n bibtype = {article},\\n author = {Hammond, T.R and Ellis, J.R},\\n doi = {10.1016/S1470-160X(02)00005-5},\\n journal = {Ecological Indicators},\\n number = {3}\\n}\",\"author_short\":[\"Hammond,  T.\",\"Ellis,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1470160X02000055\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Elasmobranchs\",\"Fisheries management\",\"Food webs\",\"Threatened species\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Analysis of topographic and vegetative factors with data mining for landslide verification\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index\",\"pages\":\"669-677\",\"volume\":\"61\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\",\"month\":\"12\",\"id\":\"d9301f8a-f1f0-3dd7-b8fe-36b17a45dd03\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-03-03\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.\",\"bibtype\":\"article\",\"author\":\"Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang\",\"doi\":\"10.1016/j.ecoleng.2013.07.070\",\"journal\":\"Ecological Engineering\",\"bibtex\":\"@article{\\n title = {Analysis of topographic and vegetative factors with data mining for landslide verification},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},\\n pages = {669-677},\\n volume = {61},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},\\n month = {12},\\n id = {d9301f8a-f1f0-3dd7-b8fe-36b17a45dd03},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-03-03},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},\\n bibtype = {article},\\n author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},\\n doi = {10.1016/j.ecoleng.2013.07.070},\\n journal = {Ecological Engineering}\\n}\",\"author_short\":[\"Tsai,  F.\",\"Lai,  J.\",\"Chen,  W., W.\",\"Lin,  T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Network\",\"Data mining\",\"Decision Tree\",\"Landslide\",\"Slope stability\",\"Vegetation index\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian networks,Conservation,Land use planning,Land use suitability,Natural resource management,Stakeholder engagement\",\"pages\":\"42-57\",\"volume\":\"291\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380014003056\",\"month\":\"11\",\"id\":\"8adb7754-2183-324d-8933-8e5102931288\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-01-27\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, USA, we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socio-economic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30m×30m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.\",\"bibtype\":\"article\",\"author\":\"\",\"doi\":\"10.1016/j.ecolmodel.2014.06.023\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian networks,Conservation,Land use planning,Land use suitability,Natural resource management,Stakeholder engagement},\\n pages = {42-57},\\n volume = {291},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014003056},\\n month = {11},\\n id = {8adb7754-2183-324d-8933-8e5102931288},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-01-27},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, USA, we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socio-economic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30m×30m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.},\\n bibtype = {article},\\n author = {},\\n doi = {10.1016/j.ecolmodel.2014.06.023},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380014003056\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014\",\"role\":\"\",\"keyword\":[\"Bayesian networks\",\"Conservation\",\"Land use planning\",\"Land use suitability\",\"Natural resource management\",\"Stakeholder engagement\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayesian networks,Benefit–cost analysis,Decision analysis,Eutrophication,Influence diagrams,Uncertainty,Water Framework Directive\",\"pages\":\"91-104\",\"volume\":\"66\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0921800908000827\",\"month\":\"5\",\"id\":\"8eea9de3-e133-3100-8084-d4f26e98112b\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-02-19\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing cost-effectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.\",\"bibtype\":\"article\",\"author\":\"Barton, D.N. and Saloranta, T. and Moe, S.J. and Eggestad, H.O. and Kuikka, S.\",\"doi\":\"10.1016/j.ecolecon.2008.02.012\",\"journal\":\"Ecological Economics\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin},\\n type = {article},\\n year = {2008},\\n keywords = {Bayesian networks,Benefit–cost analysis,Decision analysis,Eutrophication,Influence diagrams,Uncertainty,Water Framework Directive},\\n pages = {91-104},\\n volume = {66},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0921800908000827},\\n month = {5},\\n id = {8eea9de3-e133-3100-8084-d4f26e98112b},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-02-19},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing cost-effectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.},\\n bibtype = {article},\\n author = {Barton, D.N. and Saloranta, T. and Moe, S.J. and Eggestad, H.O. and Kuikka, S.},\\n doi = {10.1016/j.ecolecon.2008.02.012},\\n journal = {Ecological Economics},\\n number = {1}\\n}\",\"author_short\":[\"Barton,  D.\",\"Saloranta,  T.\",\"Moe,  S.\",\"Eggestad,  H.\",\"Kuikka,  S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0921800908000827\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Benefit–cost analysis\",\"Decision analysis\",\"Eutrophication\",\"Influence diagrams\",\"Uncertainty\",\"Water Framework Directive\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian network,Decision support,Integrated catchment management,Iran,Sustainability assessment,Vegetation management\",\"pages\":\"48-54\",\"volume\":\"268\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380013003967\",\"month\":\"10\",\"id\":\"1927d58f-21fe-3e7f-9be6-314f51358ff8\",\"created\":\"2015-04-11T19:51:57.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.\",\"bibtype\":\"article\",\"author\":\"Keshtkar, A.R. and Salajegheh, A. and Sadoddin, A. and Allan, M.G.\",\"doi\":\"10.1016/j.ecolmodel.2013.08.003\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian network,Decision support,Integrated catchment management,Iran,Sustainability assessment,Vegetation management},\\n pages = {48-54},\\n volume = {268},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380013003967},\\n month = {10},\\n id = {1927d58f-21fe-3e7f-9be6-314f51358ff8},\\n created = {2015-04-11T19:51:57.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.},\\n bibtype = {article},\\n author = {Keshtkar, A.R. and Salajegheh, A. and Sadoddin, A. and Allan, M.G.},\\n doi = {10.1016/j.ecolmodel.2013.08.003},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Keshtkar,  A.\",\"Salajegheh,  A.\",\"Sadoddin,  A.\",\"Allan,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380013003967\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Decision support\",\"Integrated catchment management\",\"Iran\",\"Sustainability assessment\",\"Vegetation management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Metrics for evaluating performance and uncertainty of Bayesian network models\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"AIC,AUC,Akaike information criterion,BIC,BN,Bayesian information criterion,Bayesian network,Bayesian network model,CPT,Error rates,GCM,GHG,Model performance,Model validation,PPCI,PPCIMIN,PPD,PPPCIMAX,Probability analysis,ROC,SP,Sensitivity analysis,TSS,Uncertainty,VR,area under the (receiver operating) curve,conditional probability table,global circulation model,greenhouse gas,maximum PPCI value given one or more state probabi,minimum PPCI value given one or more state probabi,posterior probability certainty index,posterior probability distribution,receiver operating characteristic (curve),spherical payoff,true skill statistic,variance reduction\",\"pages\":\"50-62\",\"volume\":\"230\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380012000245\",\"month\":\"4\",\"id\":\"3348523f-73e2-388c-a877-9d4052212f08\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-02-18\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model variables, links, node states, conditional probabilities, and node cliques); assessing prediction performance (confusion tables, covariate- and conditional probability-weighted confusion error rates, area under receiver operating characteristic curves, k-fold cross-validation, spherical payoff, Schwarz’ Bayesian information criterion, true skill statistic, Cohen's kappa); and evaluating uncertainty of model posterior probability distributions (Bayesian credible interval, posterior probability certainty index, certainty envelope, Gini coefficient). Examples are presented of applying the metrics to 3 real-world models of wildlife population analysis and management. Using such metrics can vitally bolster model credibility, acceptance, and appropriate application, particularly when informing management decisions.\",\"bibtype\":\"article\",\"author\":\"Marcot, Bruce G.\",\"doi\":\"10.1016/j.ecolmodel.2012.01.013\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Metrics for evaluating performance and uncertainty of Bayesian network models},\\n type = {article},\\n year = {2012},\\n keywords = {AIC,AUC,Akaike information criterion,BIC,BN,Bayesian information criterion,Bayesian network,Bayesian network model,CPT,Error rates,GCM,GHG,Model performance,Model validation,PPCI,PPCIMIN,PPD,PPPCIMAX,Probability analysis,ROC,SP,Sensitivity analysis,TSS,Uncertainty,VR,area under the (receiver operating) curve,conditional probability table,global circulation model,greenhouse gas,maximum PPCI value given one or more state probabi,minimum PPCI value given one or more state probabi,posterior probability certainty index,posterior probability distribution,receiver operating characteristic (curve),spherical payoff,true skill statistic,variance reduction},\\n pages = {50-62},\\n volume = {230},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380012000245},\\n month = {4},\\n id = {3348523f-73e2-388c-a877-9d4052212f08},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-02-18},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model variables, links, node states, conditional probabilities, and node cliques); assessing prediction performance (confusion tables, covariate- and conditional probability-weighted confusion error rates, area under receiver operating characteristic curves, k-fold cross-validation, spherical payoff, Schwarz’ Bayesian information criterion, true skill statistic, Cohen's kappa); and evaluating uncertainty of model posterior probability distributions (Bayesian credible interval, posterior probability certainty index, certainty envelope, Gini coefficient). Examples are presented of applying the metrics to 3 real-world models of wildlife population analysis and management. Using such metrics can vitally bolster model credibility, acceptance, and appropriate application, particularly when informing management decisions.},\\n bibtype = {article},\\n author = {Marcot, Bruce G.},\\n doi = {10.1016/j.ecolmodel.2012.01.013},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Marcot,  B., G.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380012000245\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012\",\"role\":\"author\",\"keyword\":[\"AIC\",\"AUC\",\"Akaike information criterion\",\"BIC\",\"BN\",\"Bayesian information criterion\",\"Bayesian network\",\"Bayesian network model\",\"CPT\",\"Error rates\",\"GCM\",\"GHG\",\"Model performance\",\"Model validation\",\"PPCI\",\"PPCIMIN\",\"PPD\",\"PPPCIMAX\",\"Probability analysis\",\"ROC\",\"SP\",\"Sensitivity analysis\",\"TSS\",\"Uncertainty\",\"VR\",\"area under the (receiver operating) curve\",\"conditional probability table\",\"global circulation model\",\"greenhouse gas\",\"maximum PPCI value given one or more state probabi\",\"minimum PPCI value given one or more state probabi\",\"posterior probability certainty index\",\"posterior probability distribution\",\"receiver operating characteristic (curve)\",\"spherical payoff\",\"true skill statistic\",\"variance reduction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Amphibian monitoring,Ascaphus truei,Bayesian networks,Dicamptodon tenebrosus,Hierarchical Bayesian models,Rhyacotriton spp.\",\"pages\":\"210-218\",\"volume\":\"214\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380008000768\",\"month\":\"6\",\"id\":\"b9c62cf5-6e60-39c6-8883-19a93b8353aa\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs) are a probabilistic modeling platform that connect variables through a series of conditional dependences. We demonstrate their utility for broad-scale conservation of amphibian populations where different types of information may be available within the region. Wildlife conservation decisions for most species are made jointly with other objectives and are tightly constrained by finances. Bayesian networks allow the use of all available information in predictions, and can provide managers with the best available information for making decisions. Habitat models were developed as a hierarchical Bayesian (HB) model for aquatic amphibian populations in the temperate Oregon Coast Range, USA. Predictions for new streams sections were made jointly using a Bayesian network to allow the inclusion of different types of available information. Missing habitat variables were modeled based on habitat survey information. Uncertainty in the true (but unknown) habitat variables were incorporated into the prediction intervals. Further, the probabilistic approach allowed us to incorporate survey information for co-occurring species to help make better predictions. Such species information was connected through the Bayesian network by the conditional dependence that arises from shared habitat variables. The utility of Bayesian networks was shown for these populations for broad-scale risk management. In contrast to deterministic models, the probabilistic nature of Bayesian networks is a natural platform for incorporating uncertainty in predictions and inference.\",\"bibtype\":\"article\",\"author\":\"Wilson, Duncan S. and Stoddard, Margo A. and Puettmann, Klaus J.\",\"doi\":\"10.1016/j.ecolmodel.2008.02.003\",\"journal\":\"Ecological Modelling\",\"number\":\"2-4\",\"bibtex\":\"@article{\\n title = {Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model},\\n type = {article},\\n year = {2008},\\n keywords = {Amphibian monitoring,Ascaphus truei,Bayesian networks,Dicamptodon tenebrosus,Hierarchical Bayesian models,Rhyacotriton spp.},\\n pages = {210-218},\\n volume = {214},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380008000768},\\n month = {6},\\n id = {b9c62cf5-6e60-39c6-8883-19a93b8353aa},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs) are a probabilistic modeling platform that connect variables through a series of conditional dependences. We demonstrate their utility for broad-scale conservation of amphibian populations where different types of information may be available within the region. Wildlife conservation decisions for most species are made jointly with other objectives and are tightly constrained by finances. Bayesian networks allow the use of all available information in predictions, and can provide managers with the best available information for making decisions. Habitat models were developed as a hierarchical Bayesian (HB) model for aquatic amphibian populations in the temperate Oregon Coast Range, USA. Predictions for new streams sections were made jointly using a Bayesian network to allow the inclusion of different types of available information. Missing habitat variables were modeled based on habitat survey information. Uncertainty in the true (but unknown) habitat variables were incorporated into the prediction intervals. Further, the probabilistic approach allowed us to incorporate survey information for co-occurring species to help make better predictions. Such species information was connected through the Bayesian network by the conditional dependence that arises from shared habitat variables. The utility of Bayesian networks was shown for these populations for broad-scale risk management. In contrast to deterministic models, the probabilistic nature of Bayesian networks is a natural platform for incorporating uncertainty in predictions and inference.},\\n bibtype = {article},\\n author = {Wilson, Duncan S. and Stoddard, Margo A. and Puettmann, Klaus J.},\\n doi = {10.1016/j.ecolmodel.2008.02.003},\\n journal = {Ecological Modelling},\\n number = {2-4}\\n}\",\"author_short\":[\"Wilson,  D., S.\",\"Stoddard,  M., A.\",\"Puettmann,  K., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380008000768\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008\",\"role\":\"author\",\"keyword\":[\"Amphibian monitoring\",\"Ascaphus truei\",\"Bayesian networks\",\"Dicamptodon tenebrosus\",\"Hierarchical Bayesian models\",\"Rhyacotriton spp.\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird\",\"pages\":\"38-50\",\"volume\":\"276\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380014000398\",\"month\":\"3\",\"id\":\"7ae94537-1682-30b1-b604-7af959748642\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modeling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model's dataset. We found that model predictions were more successful when the ranges of physical conditions included in model development were varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modeling impacts of sea-level rise or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.\",\"bibtype\":\"article\",\"author\":\"Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.\",\"doi\":\"10.1016/j.ecolmodel.2014.01.005\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},\\n pages = {38-50},\\n volume = {276},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014000398},\\n month = {3},\\n id = {7ae94537-1682-30b1-b604-7af959748642},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modeling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model's dataset. We found that model predictions were more successful when the ranges of physical conditions included in model development were varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modeling impacts of sea-level rise or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.},\\n bibtype = {article},\\n author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},\\n doi = {10.1016/j.ecolmodel.2014.01.005},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Gieder,  K., D.\",\"Karpanty,  S., M.\",\"Fraser,  J., D.\",\"Catlin,  D., H.\",\"Gutierrez,  B., T.\",\"Plant,  N., G.\",\"Turecek,  A., M.\",\"Robert Thieler,  E.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380014000398\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Development\",\"Habitat\",\"Piping plover\",\"Sea-level rise\",\"Shorebird\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"EBI: An index for delivery of ecosystem service bundles\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs\",\"pages\":\"252-265\",\"volume\":\"37\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\",\"month\":\"2\",\"id\":\"4950ea88-8fbd-3696-874a-efb0cce29b0c\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-02-04\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.\",\"bibtype\":\"article\",\"author\":\"Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.\",\"doi\":\"10.1016/j.ecolind.2013.04.006\",\"journal\":\"Ecological Indicators\",\"bibtex\":\"@article{\\n title = {EBI: An index for delivery of ecosystem service bundles},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},\\n pages = {252-265},\\n volume = {37},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},\\n month = {2},\\n id = {4950ea88-8fbd-3696-874a-efb0cce29b0c},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-02-04},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},\\n bibtype = {article},\\n author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},\\n doi = {10.1016/j.ecolind.2013.04.006},\\n journal = {Ecological Indicators}\\n}\",\"author_short\":[\"Van der Biest,  K.\",\"D’Hondt,  R.\",\"Jacobs,  S.\",\"Landuyt,  D.\",\"Staes,  J.\",\"Goethals,  P.\",\"Meire,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Biophysical potential\",\"Climate regulation\",\"Ecosystem services\",\"Land use planning\",\"Provisioning services\",\"Trade-offs\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian networks,Ecosystem services,Interdisciplinary research,Valuation\",\"pages\":\"15-27\",\"volume\":\"110\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0921800914003711\",\"month\":\"2\",\"id\":\"8062ddd5-b97f-32bd-9a5d-7de30cdc0186\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-01-21\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services from riparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context.\",\"bibtype\":\"article\",\"author\":\"McVittie, Alistair and Norton, Lisa and Martin-Ortega, Julia and Siameti, Ioanna and Glenk, Klaus and Aalders, Inge\",\"doi\":\"10.1016/j.ecolecon.2014.12.004\",\"journal\":\"Ecological Economics\",\"bibtex\":\"@article{\\n title = {Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian networks,Ecosystem services,Interdisciplinary research,Valuation},\\n pages = {15-27},\\n volume = {110},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0921800914003711},\\n month = {2},\\n id = {8062ddd5-b97f-32bd-9a5d-7de30cdc0186},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-01-21},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services from riparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context.},\\n bibtype = {article},\\n author = {McVittie, Alistair and Norton, Lisa and Martin-Ortega, Julia and Siameti, Ioanna and Glenk, Klaus and Aalders, Inge},\\n doi = {10.1016/j.ecolecon.2014.12.004},\\n journal = {Ecological Economics}\\n}\",\"author_short\":[\"McVittie,  A.\",\"Norton,  L.\",\"Martin-Ortega,  J.\",\"Siameti,  I.\",\"Glenk,  K.\",\"Aalders,  I.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0921800914003711\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Ecosystem services\",\"Interdisciplinary research\",\"Valuation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Combining state and transition models with dynamic Bayesian networks\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics\",\"pages\":\"555-566\",\"volume\":\"222\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\",\"month\":\"2\",\"id\":\"a7a054c9-1e05-3e86-8633-252c31c686f8\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.\",\"bibtype\":\"article\",\"author\":\"Nicholson, Ann E. and Flores, M. Julia\",\"doi\":\"10.1016/j.ecolmodel.2010.10.010\",\"journal\":\"Ecological Modelling\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Combining state and transition models with dynamic Bayesian networks},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},\\n pages = {555-566},\\n volume = {222},\\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},\\n month = {2},\\n id = {a7a054c9-1e05-3e86-8633-252c31c686f8},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},\\n bibtype = {article},\\n author = {Nicholson, Ann E. and Flores, M. Julia},\\n doi = {10.1016/j.ecolmodel.2010.10.010},\\n journal = {Ecological Modelling},\\n number = {3}\\n}\",\"author_short\":[\"Nicholson,  A., E.\",\"Flores,  M., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Dynamic Bayesian networks\",\"Rangeland management\",\"State-and-transition models\",\"System dynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian networks,Fisheries management,Kernel density estimation,Pelagic fish,Recruitment forecasting,Supervised classification\",\"pages\":\"35-42\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1574954114001563\",\"month\":\"1\",\"id\":\"7a2bc8b9-dad4-3812-bab1-52f4f01aaf66\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.\",\"bibtype\":\"article\",\"author\":\"Fernandes, Jose A. and Irigoien, Xabier and Lozano, Jose A. and Inza, Iñaki and Goikoetxea, Nerea and Pérez, Aritz\",\"doi\":\"10.1016/j.ecoinf.2014.11.004\",\"journal\":\"Ecological Informatics\",\"bibtex\":\"@article{\\n title = {Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian networks,Fisheries management,Kernel density estimation,Pelagic fish,Recruitment forecasting,Supervised classification},\\n pages = {35-42},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1574954114001563},\\n month = {1},\\n id = {7a2bc8b9-dad4-3812-bab1-52f4f01aaf66},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.},\\n bibtype = {article},\\n author = {Fernandes, Jose A. and Irigoien, Xabier and Lozano, Jose A. and Inza, Iñaki and Goikoetxea, Nerea and Pérez, Aritz},\\n doi = {10.1016/j.ecoinf.2014.11.004},\\n journal = {Ecological Informatics}\\n}\",\"author_short\":[\"Fernandes,  J., A.\",\"Irigoien,  X.\",\"Lozano,  J., A.\",\"Inza,  I.\",\"Goikoetxea,  N.\",\"Pérez,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1574954114001563\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Fisheries management\",\"Kernel density estimation\",\"Pelagic fish\",\"Recruitment forecasting\",\"Supervised classification\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A systems approach to unravel complex water management institutions\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayesian network,Complex systems,India,Institutional analysis,Integrated management\",\"pages\":\"202-215\",\"volume\":\"5\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\",\"month\":\"9\",\"id\":\"03e1c5c5-ca0e-39f7-aac8-77dfa167f9e9\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.\",\"bibtype\":\"article\",\"author\":\"Saravanan, V.S.\",\"doi\":\"10.1016/j.ecocom.2008.04.003\",\"journal\":\"Ecological Complexity\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {A systems approach to unravel complex water management institutions},\\n type = {article},\\n year = {2008},\\n keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},\\n pages = {202-215},\\n volume = {5},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},\\n month = {9},\\n id = {03e1c5c5-ca0e-39f7-aac8-77dfa167f9e9},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},\\n bibtype = {article},\\n author = {Saravanan, V.S.},\\n doi = {10.1016/j.ecocom.2008.04.003},\\n journal = {Ecological Complexity},\\n number = {3}\\n}\",\"author_short\":[\"Saravanan,  V.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Complex systems\",\"India\",\"Institutional analysis\",\"Integrated management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Mining monitored data for decision-making with a Bayesian network model\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian networks,Cyanobacteria,Data mining,Elicitation,Reservoir management,Water quality\",\"pages\":\"26-36\",\"volume\":\"249\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S030438001200333X\",\"month\":\"1\",\"id\":\"27102ba9-ac77-3ba5-87dd-7283b4291c45\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-08\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers. Monitored data were arranged in a consistently formatted database from which the model could ‘learn’ probabilistic relationships between model elements such as pumped nutrient load, lake water column nutrient concentrations, and Anabaena concentrations. This ‘minimal model’ produced useful insights into ecosystem relationships and provided a basic model for later development. Subsequent modelling and elicitation of conditional probabilities from experts strengthened components of the model for which there is little data available. The approach to incorporating elicited data is described and some simple scenario testing is also presented. Management outcomes resulting from application of the model are presented.\",\"bibtype\":\"article\",\"author\":\"Williams, B.J. and Cole, B.\",\"doi\":\"10.1016/j.ecolmodel.2012.07.008\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Mining monitored data for decision-making with a Bayesian network model},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian networks,Cyanobacteria,Data mining,Elicitation,Reservoir management,Water quality},\\n pages = {26-36},\\n volume = {249},\\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001200333X},\\n month = {1},\\n id = {27102ba9-ac77-3ba5-87dd-7283b4291c45},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-08},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers. Monitored data were arranged in a consistently formatted database from which the model could ‘learn’ probabilistic relationships between model elements such as pumped nutrient load, lake water column nutrient concentrations, and Anabaena concentrations. This ‘minimal model’ produced useful insights into ecosystem relationships and provided a basic model for later development. Subsequent modelling and elicitation of conditional probabilities from experts strengthened components of the model for which there is little data available. The approach to incorporating elicited data is described and some simple scenario testing is also presented. Management outcomes resulting from application of the model are presented.},\\n bibtype = {article},\\n author = {Williams, B.J. and Cole, B.},\\n doi = {10.1016/j.ecolmodel.2012.07.008},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Williams,  B.\",\"Cole,  B.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S030438001200333X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Cyanobacteria\",\"Data mining\",\"Elicitation\",\"Reservoir management\",\"Water quality\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening\",\"pages\":\"2565-2575\",\"volume\":\"221\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\",\"month\":\"10\",\"id\":\"90ca0fff-a0db-3b88-a996-692a49ce2441\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.\",\"bibtype\":\"article\",\"author\":\"Liedloff, Adam C. and Smith, Carl S.\",\"doi\":\"10.1016/j.ecolmodel.2010.07.022\",\"journal\":\"Ecological Modelling\",\"number\":\"21\",\"bibtex\":\"@article{\\n title = {Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour},\\n type = {article},\\n year = {2010},\\n keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},\\n pages = {2565-2575},\\n volume = {221},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},\\n month = {10},\\n id = {90ca0fff-a0db-3b88-a996-692a49ce2441},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},\\n bibtype = {article},\\n author = {Liedloff, Adam C. and Smith, Carl S.},\\n doi = {10.1016/j.ecolmodel.2010.07.022},\\n journal = {Ecological Modelling},\\n number = {21}\\n}\",\"author_short\":[\"Liedloff,  A., C.\",\"Smith,  C., S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Fire management\",\"Flames\",\"Grazing management\",\"Probabilistic modelling\",\"Simulation modelling\",\"Tree density\",\"Woody thickening\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A data mining approach to predictive vegetation mapping using probabilistic graphical models\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian network,Data mining,Expectation-maximization,Graphical model,Predictive vegetation mapping\",\"pages\":\"111-124\",\"volume\":\"6\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1574954111000045\",\"month\":\"3\",\"id\":\"11a286ee-60c8-38cb-a2a6-634a98587984\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2015-02-16\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.\",\"bibtype\":\"article\",\"author\":\"Dlamini, Wisdom M.\",\"doi\":\"10.1016/j.ecoinf.2010.12.005\",\"journal\":\"Ecological Informatics\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {A data mining approach to predictive vegetation mapping using probabilistic graphical models},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian network,Data mining,Expectation-maximization,Graphical model,Predictive vegetation mapping},\\n pages = {111-124},\\n volume = {6},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1574954111000045},\\n month = {3},\\n id = {11a286ee-60c8-38cb-a2a6-634a98587984},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2015-02-16},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.},\\n bibtype = {article},\\n author = {Dlamini, Wisdom M.},\\n doi = {10.1016/j.ecoinf.2010.12.005},\\n journal = {Ecological Informatics},\\n number = {2}\\n}\",\"author_short\":[\"Dlamini,  W., M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1574954111000045\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Data mining\",\"Expectation-maximization\",\"Graphical model\",\"Predictive vegetation mapping\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Advantages and challenges of Bayesian networks in environmental modelling\",\"type\":\"article\",\"year\":\"2007\",\"pages\":\"312-318\",\"volume\":\"203\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380006006089\",\"month\":\"5\",\"id\":\"983df284-5049-3b1c-92dd-fc5e567896b1\",\"created\":\"2015-04-11T19:51:58.000Z\",\"accessed\":\"2014-07-14\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs) are an increasingly popular method of modelling uncertain and complex domains such as ecosystems and environmental management. At best, they provide a robust and mathematically coherent framework for the analysis of this kind of problems. However, there are certain pitfalls as well. In this paper, I summarise the pros and cons of the use of Bayesian networks especially in the context of environmental modelling and management. I will also give references to relevant publications, and introduce some software products that can be used to build Bayesian networks.\",\"bibtype\":\"article\",\"author\":\"\",\"journal\":\"Ecological Modelling\",\"number\":\"3-4\",\"bibtex\":\"@article{\\n title = {Advantages and challenges of Bayesian networks in environmental modelling},\\n type = {article},\\n year = {2007},\\n pages = {312-318},\\n volume = {203},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006006089},\\n month = {5},\\n id = {983df284-5049-3b1c-92dd-fc5e567896b1},\\n created = {2015-04-11T19:51:58.000Z},\\n accessed = {2014-07-14},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs) are an increasingly popular method of modelling uncertain and complex domains such as ecosystems and environmental management. At best, they provide a robust and mathematically coherent framework for the analysis of this kind of problems. However, there are certain pitfalls as well. In this paper, I summarise the pros and cons of the use of Bayesian networks especially in the context of environmental modelling and management. I will also give references to relevant publications, and introduce some software products that can be used to build Bayesian networks.},\\n bibtype = {article},\\n author = {},\\n journal = {Ecological Modelling},\\n number = {3-4}\\n}\",\"author_short\":[],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380006006089\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007\",\"role\":\"\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian network modelling,Biodiesel,Expert opinion,Family farming,Social inclusion,Systems thinking\",\"pages\":\"81-95\",\"volume\":\"121\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0308521X13000887\",\"month\":\"10\",\"id\":\"484e0845-a9f8-3bb7-a2a4-1fbd4a6c552a\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-03-10\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This study focuses on family farmer engagement in the Brazilian national programme for Production and use of Biodiesel (PNPB). The Brazilian government has been promoting the role of family farmers as producers of biomass for biodiesel since 2004; however, fewer than expected family farmers have decided to produce biomass for biodiesel. The North of Minas Gerais is one region where a biodiesel plant has been strategically located to source castor beans grown by family farmers. The target family farm type in this region specializes in beef and/or dairy production with low input pasture (approximately 30ha per farm), maize intercropped with beans (approximately 1ha per farm) and sugarcane (approximately 1ha per farm). We selected this region for a case study to explore management decisions of farmers, industry and policy makers that influence family farmer engagement with biodiesel production through cultivation of castor beans. To evaluate outcomes for family farmers engaging with the PNPB, we focused on how cultivation of castor beans impacts family farmers in terms of income levels, income stability and levels of milk production. We used an application of systems thinking known as Bayesian network modelling (BNM). BNM was chosen for its suitability to integrate different types of knowledge and to include quantitative and qualitative variables. The study was built on a body of scientific literature explaining why family farmers have not been cultivating castor beans for biodiesel production and a body of experiential knowledge of local actors (farmers, extension officers, policy makers, biodiesel manufacturers and researchers in North of Minas Gerais). The complete BNM consisted of a ‘cause and effect’ diagram where the strengths of the causal relationships were quantified with elicited opinions from surveyed local actors. We used the complete BNM to explore scenarios that could improve outcomes for family farmers and consequently increase their level of engagement. For example, we addressed subsidy structures of the PNPB, crop management, farm-level trade-offs and value-chain innovations. We demonstrate that decisions to support family farmer engagement with biodiesel are not singular. Engagement by family farmers requires simultaneously: improvements in technical crop management, reductions in farm-level cash constraints and innovations in the production chain such that engagement of family farmers goes beyond cultivation of one more low-value crop. Finally we discuss some methodological issues from this application of BNM to farming systems research.\",\"bibtype\":\"article\",\"author\":\"Florin, Madeleine J. and van Ittersum, Martin K. and van de Ven, Gerrie W.J.\",\"doi\":\"10.1016/j.agsy.2013.07.002\",\"journal\":\"Agricultural Systems\",\"bibtex\":\"@article{\\n title = {Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian network modelling,Biodiesel,Expert opinion,Family farming,Social inclusion,Systems thinking},\\n pages = {81-95},\\n volume = {121},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X13000887},\\n month = {10},\\n id = {484e0845-a9f8-3bb7-a2a4-1fbd4a6c552a},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-03-10},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This study focuses on family farmer engagement in the Brazilian national programme for Production and use of Biodiesel (PNPB). The Brazilian government has been promoting the role of family farmers as producers of biomass for biodiesel since 2004; however, fewer than expected family farmers have decided to produce biomass for biodiesel. The North of Minas Gerais is one region where a biodiesel plant has been strategically located to source castor beans grown by family farmers. The target family farm type in this region specializes in beef and/or dairy production with low input pasture (approximately 30ha per farm), maize intercropped with beans (approximately 1ha per farm) and sugarcane (approximately 1ha per farm). We selected this region for a case study to explore management decisions of farmers, industry and policy makers that influence family farmer engagement with biodiesel production through cultivation of castor beans. To evaluate outcomes for family farmers engaging with the PNPB, we focused on how cultivation of castor beans impacts family farmers in terms of income levels, income stability and levels of milk production. We used an application of systems thinking known as Bayesian network modelling (BNM). BNM was chosen for its suitability to integrate different types of knowledge and to include quantitative and qualitative variables. The study was built on a body of scientific literature explaining why family farmers have not been cultivating castor beans for biodiesel production and a body of experiential knowledge of local actors (farmers, extension officers, policy makers, biodiesel manufacturers and researchers in North of Minas Gerais). The complete BNM consisted of a ‘cause and effect’ diagram where the strengths of the causal relationships were quantified with elicited opinions from surveyed local actors. We used the complete BNM to explore scenarios that could improve outcomes for family farmers and consequently increase their level of engagement. For example, we addressed subsidy structures of the PNPB, crop management, farm-level trade-offs and value-chain innovations. We demonstrate that decisions to support family farmer engagement with biodiesel are not singular. Engagement by family farmers requires simultaneously: improvements in technical crop management, reductions in farm-level cash constraints and innovations in the production chain such that engagement of family farmers goes beyond cultivation of one more low-value crop. Finally we discuss some methodological issues from this application of BNM to farming systems research.},\\n bibtype = {article},\\n author = {Florin, Madeleine J. and van Ittersum, Martin K. and van de Ven, Gerrie W.J.},\\n doi = {10.1016/j.agsy.2013.07.002},\\n journal = {Agricultural Systems}\\n}\",\"author_short\":[\"Florin,  M., J.\",\"van Ittersum,  M., K.\",\"van de Ven,  G., W.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0308521X13000887\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian network modelling\",\"Biodiesel\",\"Expert opinion\",\"Family farming\",\"Social inclusion\",\"Systems thinking\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Participatory decision support for agricultural management. A case study from Sri Lanka\",\"type\":\"article\",\"year\":\"2003\",\"keywords\":\"Agricultural management,Agricultural policy,Bayesian network,Decision support system,Integrated management,Sri Lanka,Stakeholder participation\",\"pages\":\"457-482\",\"volume\":\"76\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0308521X02000069\",\"month\":\"5\",\"id\":\"ea7f2f84-1ccf-376d-a2da-1cfe7620b78a\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Agricultural policy makers were helped to construct and use a decision support system (DSS) to identify problems and assess potential solutions for a river basin in Sri Lanka. Through building the DSS themselves, policy makers should reach better decisions. The main aim of the study was to test whether this could be done using a tool called a Bayesian network (BN) which is accessible to non-specialists and able to provide a generic, flexible framework for the construction of DSS. Results from a workshop indicated that the approach showed promise, providing a common framework for discussion and allowing policy makers to structure complex systems from a multi-disciplinary perspective. The need for a multi-disciplinary perspective was clearly demonstrated. The study also suggested improvements to the ways in which BNs can be used in practice. Further workshops with farmers highlighted the importance of involving them in the planning process and suggested more effective ways of doing this while using BNs.\",\"bibtype\":\"article\",\"author\":\"Cain, J.D and Jinapala, K and Makin, I.W and Somaratna, P.G and Ariyaratna, B.R and Perera, L.R\",\"doi\":\"10.1016/S0308-521X(02)00006-9\",\"journal\":\"Agricultural Systems\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Participatory decision support for agricultural management. A case study from Sri Lanka},\\n type = {article},\\n year = {2003},\\n keywords = {Agricultural management,Agricultural policy,Bayesian network,Decision support system,Integrated management,Sri Lanka,Stakeholder participation},\\n pages = {457-482},\\n volume = {76},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X02000069},\\n month = {5},\\n id = {ea7f2f84-1ccf-376d-a2da-1cfe7620b78a},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Agricultural policy makers were helped to construct and use a decision support system (DSS) to identify problems and assess potential solutions for a river basin in Sri Lanka. Through building the DSS themselves, policy makers should reach better decisions. The main aim of the study was to test whether this could be done using a tool called a Bayesian network (BN) which is accessible to non-specialists and able to provide a generic, flexible framework for the construction of DSS. Results from a workshop indicated that the approach showed promise, providing a common framework for discussion and allowing policy makers to structure complex systems from a multi-disciplinary perspective. The need for a multi-disciplinary perspective was clearly demonstrated. The study also suggested improvements to the ways in which BNs can be used in practice. Further workshops with farmers highlighted the importance of involving them in the planning process and suggested more effective ways of doing this while using BNs.},\\n bibtype = {article},\\n author = {Cain, J.D and Jinapala, K and Makin, I.W and Somaratna, P.G and Ariyaratna, B.R and Perera, L.R},\\n doi = {10.1016/S0308-521X(02)00006-9},\\n journal = {Agricultural Systems},\\n number = {2}\\n}\",\"author_short\":[\"Cain,  J.\",\"Jinapala,  K.\",\"Makin,  I.\",\"Somaratna,  P.\",\"Ariyaratna,  B.\",\"Perera,  L.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0308521X02000069\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003\",\"role\":\"author\",\"keyword\":[\"Agricultural management\",\"Agricultural policy\",\"Bayesian network\",\"Decision support system\",\"Integrated management\",\"Sri Lanka\",\"Stakeholder participation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Negotiating participatory irrigation management in the Indian Himalayas\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Bayesian network,Institutional integration,Integrated water management,Policy modelling,South Asia\",\"pages\":\"651-658\",\"volume\":\"97\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378377409003576\",\"month\":\"5\",\"id\":\"03d55546-ca56-351b-b7a8-66ee6994cadc\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-03-31\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Participatory irrigation management (PIM) reforms are implemented in India to facilitate farmers’ participation in irrigation management, through water user groups. Although thousands of user groups have been formed, a closer examination reveals inefficient water use, social power capture by rural elites in the name of participation, inadequate support from government institutions and government's inability to alleviate poverty. Currently, there is inadequate understanding of the linkage between socio-cultural, institutional and ecological factors affecting the outcome of the PIM reforms in India. Drawing from a case study village in the Shiwalik region of the Indian Himalayas, the paper identifies the role of diverse actors to exploit historic and ecological factors to derail the PIM reforms to frame water management problems. Using a combination of research methods and with application of a Bayesian network, the paper explores the inter-linkages between socio-cultural, institutional and ecological factors in derailing the PIM reforms. The paper reveals that PIM policies are never implemented, but integrated through the negotiation with other diverse policies and socio-cultural settings in (re)shaping water resources management. The analysis demonstrates that water is managed by multifaceted governance arrangements. In this governance arrangement state-centric or market-oriented or community-centered institutional arrangements are not superior to each other, rather they incrementally and cumulatively superimpose to (re)shape water resources management. In this process, integration represents a complex blend of statutory and socially embedded actors bringing with them diverse rules to negotiate, along with contextual factors. The findings call for laying out broad principles/ideologies in the policy statements of the statutory public actors that allow other actors to integrate, adapt and make policy processes dynamic. To facilitate this processes, the paper calls for statutory public actors to regulate water distribution, build capacity of actors and offer diverse forums for actors share and debate on the available information to take informed water-related decisions for a sustainable future.\",\"bibtype\":\"article\",\"author\":\"Saravanan, V.S.\",\"doi\":\"10.1016/j.agwat.2009.12.003\",\"journal\":\"Agricultural Water Management\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Negotiating participatory irrigation management in the Indian Himalayas},\\n type = {article},\\n year = {2010},\\n keywords = {Bayesian network,Institutional integration,Integrated water management,Policy modelling,South Asia},\\n pages = {651-658},\\n volume = {97},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377409003576},\\n month = {5},\\n id = {03d55546-ca56-351b-b7a8-66ee6994cadc},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-03-31},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Participatory irrigation management (PIM) reforms are implemented in India to facilitate farmers’ participation in irrigation management, through water user groups. Although thousands of user groups have been formed, a closer examination reveals inefficient water use, social power capture by rural elites in the name of participation, inadequate support from government institutions and government's inability to alleviate poverty. Currently, there is inadequate understanding of the linkage between socio-cultural, institutional and ecological factors affecting the outcome of the PIM reforms in India. Drawing from a case study village in the Shiwalik region of the Indian Himalayas, the paper identifies the role of diverse actors to exploit historic and ecological factors to derail the PIM reforms to frame water management problems. Using a combination of research methods and with application of a Bayesian network, the paper explores the inter-linkages between socio-cultural, institutional and ecological factors in derailing the PIM reforms. The paper reveals that PIM policies are never implemented, but integrated through the negotiation with other diverse policies and socio-cultural settings in (re)shaping water resources management. The analysis demonstrates that water is managed by multifaceted governance arrangements. In this governance arrangement state-centric or market-oriented or community-centered institutional arrangements are not superior to each other, rather they incrementally and cumulatively superimpose to (re)shape water resources management. In this process, integration represents a complex blend of statutory and socially embedded actors bringing with them diverse rules to negotiate, along with contextual factors. The findings call for laying out broad principles/ideologies in the policy statements of the statutory public actors that allow other actors to integrate, adapt and make policy processes dynamic. To facilitate this processes, the paper calls for statutory public actors to regulate water distribution, build capacity of actors and offer diverse forums for actors share and debate on the available information to take informed water-related decisions for a sustainable future.},\\n bibtype = {article},\\n author = {Saravanan, V.S.},\\n doi = {10.1016/j.agwat.2009.12.003},\\n journal = {Agricultural Water Management},\\n number = {5}\\n}\",\"author_short\":[\"Saravanan,  V.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378377409003576\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Institutional integration\",\"Integrated water management\",\"Policy modelling\",\"South Asia\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks\",\"type\":\"article\",\"year\":\"2005\",\"keywords\":\"Bayesian Networks,Irrigated land,Overexploitation,Stakeholders\",\"pages\":\"21-36\",\"volume\":\"77\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378377405000818\",\"month\":\"8\",\"id\":\"eeeb90f3-7bd6-33de-87b5-af5d9033a066\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Included into the objectives of the EU Water Framework Directive (Directive 2000/60/EC) there are the correct management of the water resources and the involvement of the stakeholders in the decision process. Bayesian Networks, mathematical models based on the probability theory, have been used recently to solve environmental problems. This methodology meets the relevant requirements to the effect that it is fully comprehensive and integrated, as it deals with the water resource as a whole and encourages the participation of all those people and groups who are somehow involved in its use or management. A Bayesian Network was developed by means of stakeholders participation which is intended to be useful in the decision-making process related to water resource management in the Hydrogeological Unit “Eastern Mancha”. The main problem in the region is the risk of overexploitation of the local aquifer, brought about by a considerable increase, over the last 25 years, in the surface area of irrigated arable land. The results offered by the tool show that the current situation is non-sustainable concerning the aquifer exploitation. There are several ways to solve this situation. The first one could be decreasing the current volume of ground water for irrigation, but this solution would not be welcome by the farmers due to losses of income. The second one is replacing groundwater for irrigation by surface water, where the main problem would be the considerable expenses in infrastructures.\",\"bibtype\":\"article\",\"author\":\"Martín de Santa Olalla, F.J. and Domínguez, A. and Artigao, A. and Fabeiro, C. and Ortega, J.F.\",\"doi\":\"10.1016/j.agwat.2004.09.029\",\"journal\":\"Agricultural Water Management\",\"number\":\"1-3\",\"bibtex\":\"@article{\\n title = {Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks},\\n type = {article},\\n year = {2005},\\n keywords = {Bayesian Networks,Irrigated land,Overexploitation,Stakeholders},\\n pages = {21-36},\\n volume = {77},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377405000818},\\n month = {8},\\n id = {eeeb90f3-7bd6-33de-87b5-af5d9033a066},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Included into the objectives of the EU Water Framework Directive (Directive 2000/60/EC) there are the correct management of the water resources and the involvement of the stakeholders in the decision process. Bayesian Networks, mathematical models based on the probability theory, have been used recently to solve environmental problems. This methodology meets the relevant requirements to the effect that it is fully comprehensive and integrated, as it deals with the water resource as a whole and encourages the participation of all those people and groups who are somehow involved in its use or management. A Bayesian Network was developed by means of stakeholders participation which is intended to be useful in the decision-making process related to water resource management in the Hydrogeological Unit “Eastern Mancha”. The main problem in the region is the risk of overexploitation of the local aquifer, brought about by a considerable increase, over the last 25 years, in the surface area of irrigated arable land. The results offered by the tool show that the current situation is non-sustainable concerning the aquifer exploitation. There are several ways to solve this situation. The first one could be decreasing the current volume of ground water for irrigation, but this solution would not be welcome by the farmers due to losses of income. The second one is replacing groundwater for irrigation by surface water, where the main problem would be the considerable expenses in infrastructures.},\\n bibtype = {article},\\n author = {Martín de Santa Olalla, F.J. and Domínguez, A. and Artigao, A. and Fabeiro, C. and Ortega, J.F.},\\n doi = {10.1016/j.agwat.2004.09.029},\\n journal = {Agricultural Water Management},\\n number = {1-3}\\n}\",\"author_short\":[\"Martín de Santa Olalla,  F.\",\"Domínguez,  A.\",\"Artigao,  A.\",\"Fabeiro,  C.\",\"Ortega,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378377405000818\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Irrigated land\",\"Overexploitation\",\"Stakeholders\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision.\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Accidents,Accidents: statistics & numerical data,Environment,Models, Chemical,Models, Statistical,Petroleum,Petroleum Pollution,Petroleum Pollution: statistics & numerical data,Risk Assessment,Ships,Ships: statistics & numerical data,Water Pollution, Chemical,Water Pollution, Chemical: statistics & numerical\",\"pages\":\"130-44\",\"volume\":\"79\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0025326X13007595\",\"month\":\"2\",\"day\":\"15\",\"id\":\"44afabf0-e88c-34f0-9569-aaf076fb3d2c\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.\",\"bibtype\":\"article\",\"author\":\"Goerlandt, Floris and Montewka, Jakub\",\"doi\":\"10.1016/j.marpolbul.2013.12.026\",\"journal\":\"Marine pollution bulletin\",\"number\":\"1-2\",\"bibtex\":\"@article{\\n title = {A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision.},\\n type = {article},\\n year = {2014},\\n keywords = {Accidents,Accidents: statistics & numerical data,Environment,Models, Chemical,Models, Statistical,Petroleum,Petroleum Pollution,Petroleum Pollution: statistics & numerical data,Risk Assessment,Ships,Ships: statistics & numerical data,Water Pollution, Chemical,Water Pollution, Chemical: statistics & numerical},\\n pages = {130-44},\\n volume = {79},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13007595},\\n month = {2},\\n day = {15},\\n id = {44afabf0-e88c-34f0-9569-aaf076fb3d2c},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.},\\n bibtype = {article},\\n author = {Goerlandt, Floris and Montewka, Jakub},\\n doi = {10.1016/j.marpolbul.2013.12.026},\\n journal = {Marine pollution bulletin},\\n number = {1-2}\\n}\",\"author_short\":[\"Goerlandt,  F.\",\"Montewka,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0025326X13007595\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014\",\"role\":\"author\",\"keyword\":[\"Accidents\",\"Accidents: statistics & numerical data\",\"Environment\",\"Models\",\"Chemical\",\"Models\",\"Statistical\",\"Petroleum\",\"Petroleum Pollution\",\"Petroleum Pollution: statistics & numerical data\",\"Risk Assessment\",\"Ships\",\"Ships: statistics & numerical data\",\"Water Pollution\",\"Chemical\",\"Water Pollution\",\"Chemical: statistics & numerical\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Baltic salmon,Bayesian network,Commitment,Expert knowledge,Implementation uncertainty,Management plan,Stakeholders\",\"pages\":\"477-486\",\"volume\":\"34\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0308597X09001626\",\"month\":\"5\",\"id\":\"a30b55db-89e3-3dc7-852c-22231aaba337\",\"created\":\"2015-04-11T19:52:01.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.\",\"bibtype\":\"article\",\"author\":\"Haapasaari, Päivi and Karjalainen, Timo P.\",\"doi\":\"10.1016/j.marpol.2009.10.002\",\"journal\":\"Marine Policy\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks},\\n type = {article},\\n year = {2010},\\n keywords = {Baltic salmon,Bayesian network,Commitment,Expert knowledge,Implementation uncertainty,Management plan,Stakeholders},\\n pages = {477-486},\\n volume = {34},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0308597X09001626},\\n month = {5},\\n id = {a30b55db-89e3-3dc7-852c-22231aaba337},\\n created = {2015-04-11T19:52:01.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.},\\n bibtype = {article},\\n author = {Haapasaari, Päivi and Karjalainen, Timo P.},\\n doi = {10.1016/j.marpol.2009.10.002},\\n journal = {Marine Policy},\\n number = {3}\\n}\",\"author_short\":[\"Haapasaari,  P.\",\"Karjalainen,  T., P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0308597X09001626\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010\",\"role\":\"author\",\"keyword\":[\"Baltic salmon\",\"Bayesian network\",\"Commitment\",\"Expert knowledge\",\"Implementation uncertainty\",\"Management plan\",\"Stakeholders\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland.\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Animals,Aquatic Organisms,Aquatic Organisms: drug effects,Bayes Theorem,Computer Simulation,Environmental Monitoring,Environmental Monitoring: methods,Finland,Fresh Water,Fresh Water: chemistry,Models, Theoretical,Oceans and Seas,Petroleum,Petroleum Pollution,Petroleum: toxicity,Plants,Plants: drug effects,Population Dynamics,Reproduction,Species Specificity,Water Pollutants, Chemical,Water Pollutants, Chemical: chemistry,Water Pollutants, Chemical: toxicity\",\"pages\":\"2822-35\",\"volume\":\"62\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0025326X11004693\",\"month\":\"12\",\"id\":\"0cfe363b-d1c2-36b8-9ee4-3c0b8f3d308d\",\"created\":\"2015-04-11T19:52:02.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.\",\"bibtype\":\"article\",\"author\":\"Lecklin, Tiina and Ryömä, Riitta and Kuikka, Sakari\",\"doi\":\"10.1016/j.marpolbul.2011.08.045\",\"journal\":\"Marine pollution bulletin\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland.},\\n type = {article},\\n year = {2011},\\n keywords = {Animals,Aquatic Organisms,Aquatic Organisms: drug effects,Bayes Theorem,Computer Simulation,Environmental Monitoring,Environmental Monitoring: methods,Finland,Fresh Water,Fresh Water: chemistry,Models, Theoretical,Oceans and Seas,Petroleum,Petroleum Pollution,Petroleum: toxicity,Plants,Plants: drug effects,Population Dynamics,Reproduction,Species Specificity,Water Pollutants, Chemical,Water Pollutants, Chemical: chemistry,Water Pollutants, Chemical: toxicity},\\n pages = {2822-35},\\n volume = {62},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X11004693},\\n month = {12},\\n id = {0cfe363b-d1c2-36b8-9ee4-3c0b8f3d308d},\\n created = {2015-04-11T19:52:02.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.},\\n bibtype = {article},\\n author = {Lecklin, Tiina and Ryömä, Riitta and Kuikka, Sakari},\\n doi = {10.1016/j.marpolbul.2011.08.045},\\n journal = {Marine pollution bulletin},\\n number = {12}\\n}\",\"author_short\":[\"Lecklin,  T.\",\"Ryömä,  R.\",\"Kuikka,  S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0025326X11004693\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011\",\"role\":\"author\",\"keyword\":[\"Animals\",\"Aquatic Organisms\",\"Aquatic Organisms: drug effects\",\"Bayes Theorem\",\"Computer Simulation\",\"Environmental Monitoring\",\"Environmental Monitoring: methods\",\"Finland\",\"Fresh Water\",\"Fresh Water: chemistry\",\"Models\",\"Theoretical\",\"Oceans and Seas\",\"Petroleum\",\"Petroleum Pollution\",\"Petroleum: toxicity\",\"Plants\",\"Plants: drug effects\",\"Population Dynamics\",\"Reproduction\",\"Species Specificity\",\"Water Pollutants\",\"Chemical\",\"Water Pollutants\",\"Chemical: chemistry\",\"Water Pollutants\",\"Chemical: toxicity\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian networks,Conservation,Development,GIS,Land use,Smart Growth\",\"pages\":\"190-203\",\"volume\":\"101\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0169204611000697\",\"month\":\"5\",\"id\":\"3d0bde03-c6af-3992-8432-3c72eef0f719\",\"created\":\"2015-04-11T19:52:02.000Z\",\"accessed\":\"2015-01-14\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine's Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales.\",\"bibtype\":\"article\",\"author\":\"McCloskey, Jon T. and Lilieholm, Robert J. and Cronan, Christopher\",\"doi\":\"10.1016/j.landurbplan.2011.02.011\",\"journal\":\"Landscape and Urban Planning\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian networks,Conservation,Development,GIS,Land use,Smart Growth},\\n pages = {190-203},\\n volume = {101},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0169204611000697},\\n month = {5},\\n id = {3d0bde03-c6af-3992-8432-3c72eef0f719},\\n created = {2015-04-11T19:52:02.000Z},\\n accessed = {2015-01-14},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine's Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales.},\\n bibtype = {article},\\n author = {McCloskey, Jon T. and Lilieholm, Robert J. and Cronan, Christopher},\\n doi = {10.1016/j.landurbplan.2011.02.011},\\n journal = {Landscape and Urban Planning},\\n number = {2}\\n}\",\"author_short\":[\"McCloskey,  J., T.\",\"Lilieholm,  R., J.\",\"Cronan,  C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0169204611000697\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Conservation\",\"Development\",\"GIS\",\"Land use\",\"Smart Growth\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Coffee,Expert knowledge,Remote sensing,Rwanda,Very high resolution imagery\",\"pages\":\"331-340\",\"volume\":\"33\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0303243414001251\",\"month\":\"12\",\"id\":\"792bc970-bcee-3e78-bee7-7361ff38848e\",\"created\":\"2015-04-11T19:52:03.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2=0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.\",\"bibtype\":\"article\",\"author\":\"Mukashema, A. and Veldkamp, A. and Vrieling, A.\",\"doi\":\"10.1016/j.jag.2014.05.005\",\"journal\":\"International Journal of Applied Earth Observation and Geoinformation\",\"bibtex\":\"@article{\\n title = {Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Coffee,Expert knowledge,Remote sensing,Rwanda,Very high resolution imagery},\\n pages = {331-340},\\n volume = {33},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0303243414001251},\\n month = {12},\\n id = {792bc970-bcee-3e78-bee7-7361ff38848e},\\n created = {2015-04-11T19:52:03.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2=0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.},\\n bibtype = {article},\\n author = {Mukashema, A. and Veldkamp, A. and Vrieling, A.},\\n doi = {10.1016/j.jag.2014.05.005},\\n journal = {International Journal of Applied Earth Observation and Geoinformation}\\n}\",\"author_short\":[\"Mukashema,  A.\",\"Veldkamp,  A.\",\"Vrieling,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0303243414001251\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Coffee\",\"Expert knowledge\",\"Remote sensing\",\"Rwanda\",\"Very high resolution imagery\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian network,Germplasm supply,Nursery accreditation,Nursery organisation\",\"pages\":\"29-41\",\"volume\":\"47\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0264837715000824\",\"month\":\"9\",\"id\":\"595f7fe3-90b0-35a3-98f2-c555ac0599e7\",\"created\":\"2015-04-11T19:52:02.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The limited supply of high quality planting materials for a wide species base is a major reason for the limited success of reforestation programmes or projects in many developing countries. This paper reports the research that was undertaken to improve the supply of high quality planting materials for agroforestry, tree farming and reforestation in the Philippines. A systems approach was used to identify mechanisms to improve the operational effectiveness of the forest nursery sector. A Bayesian Belief Network of the forest nursery sector was developed to examine the interactions between the key components of the forest nursery sector, identify key leverage points for intervention and explore potential impacts of possible policy interventions. Although improving the operational effectiveness of individual, communal and government nurseries will result in high operational effectiveness of the forest nursery sector, the operational effectiveness of government nurseries is likely to have a negative impact on the market for seedlings from smallholder nurseries i.e. individual and communal nurseries, thus impeding the sustainability of smallholder nurseries. Increasing the supply of high quality germplasm for a wide variety of species, improving the technical capabilities of smallholder nursery operators in seedling production and increasing the market demand of high quality seedlings from smallholder nurseries are the most important requirements for improving the operational effectiveness of the forest nursery sector. However, government nurseries can play a crucial role in improving the effectiveness of the forest nursery sector by diversifying their production to focus on species that are in demand by smallholder farmers and which cannot be supplied by individual or communal nurseries. Failing to do this will result in the current situation continuing in which government nursery sector competes with private and communal nurseries.\",\"bibtype\":\"article\",\"author\":\"Gregorio, Nestor and Herbohn, John and Harrison, Steve and Smith, Carl\",\"doi\":\"10.1016/j.landusepol.2015.03.009\",\"journal\":\"Land Use Policy\",\"bibtex\":\"@article{\\n title = {A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian network,Germplasm supply,Nursery accreditation,Nursery organisation},\\n pages = {29-41},\\n volume = {47},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0264837715000824},\\n month = {9},\\n id = {595f7fe3-90b0-35a3-98f2-c555ac0599e7},\\n created = {2015-04-11T19:52:02.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The limited supply of high quality planting materials for a wide species base is a major reason for the limited success of reforestation programmes or projects in many developing countries. This paper reports the research that was undertaken to improve the supply of high quality planting materials for agroforestry, tree farming and reforestation in the Philippines. A systems approach was used to identify mechanisms to improve the operational effectiveness of the forest nursery sector. A Bayesian Belief Network of the forest nursery sector was developed to examine the interactions between the key components of the forest nursery sector, identify key leverage points for intervention and explore potential impacts of possible policy interventions. Although improving the operational effectiveness of individual, communal and government nurseries will result in high operational effectiveness of the forest nursery sector, the operational effectiveness of government nurseries is likely to have a negative impact on the market for seedlings from smallholder nurseries i.e. individual and communal nurseries, thus impeding the sustainability of smallholder nurseries. Increasing the supply of high quality germplasm for a wide variety of species, improving the technical capabilities of smallholder nursery operators in seedling production and increasing the market demand of high quality seedlings from smallholder nurseries are the most important requirements for improving the operational effectiveness of the forest nursery sector. However, government nurseries can play a crucial role in improving the effectiveness of the forest nursery sector by diversifying their production to focus on species that are in demand by smallholder farmers and which cannot be supplied by individual or communal nurseries. Failing to do this will result in the current situation continuing in which government nursery sector competes with private and communal nurseries.},\\n bibtype = {article},\\n author = {Gregorio, Nestor and Herbohn, John and Harrison, Steve and Smith, Carl},\\n doi = {10.1016/j.landusepol.2015.03.009},\\n journal = {Land Use Policy}\\n}\",\"author_short\":[\"Gregorio,  N.\",\"Herbohn,  J.\",\"Harrison,  S.\",\"Smith,  C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0264837715000824\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Germplasm supply\",\"Nursery accreditation\",\"Nursery organisation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bi-directional risk assessment in carbon capture and storage with Bayesian Networks\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian Networks,CCS,Risk assessment\",\"pages\":\"150-159\",\"volume\":\"35\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1750583615000262\",\"month\":\"4\",\"id\":\"4e33b138-ca45-3429-8b20-cd35252bbabf\",\"created\":\"2015-04-11T19:52:03.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The complex system required for carbon capture and storage (CCS) encompasses numerous sub-systems with inter-dependencies and large parameter uncertainties that propagate throughout the system. Exploring and understanding these inter-dependencies and uncertainties is invaluable for developing robust risk information. Bayesian Networks (BN), a decision support tool, are being increasingly used in the broader risk assessment community and show promise for use in CCS. BNs explore the dependencies and uncertainties within a system and have the potential to provide a better understanding of risk than more traditional tools such as logic trees or other less integrated approaches. Working with experts from within the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), we have developed a generic BN structure for the storage sub-system of CCS which can be used to guide the development of BNs for other CCS applications and for use in both diagnostic and predictive analysis. This bi-directionality provides one of the more important benefits of BNs; it allows for (1) traditional bottom-up risk assessment where the likely consequences based on the expected state of the system can be calculated and also (2) top-down, or outcome oriented risk, where the state of the system leading to a particular outcome, such as the likelihood of 2% leakage in 1000 years, is determined. This allows for a comprehensive sensitivity analysis which highlights important contributors to the risk and also where additional knowledge may benefit the project and reduce uncertainty. A robust expert elicitation procedure, for both the development of the network structure and the determination of event probabilities, is an integral part of the use of any such BN tool in CCS. Finally, we show the direct application of a smaller CCS BN by the CO2CRC.\",\"bibtype\":\"article\",\"author\":\"Gerstenberger, M.C. and Christophersen, A. and Buxton, R. and Nicol, A.\",\"doi\":\"10.1016/j.ijggc.2015.01.010\",\"journal\":\"International Journal of Greenhouse Gas Control\",\"bibtex\":\"@article{\\n title = {Bi-directional risk assessment in carbon capture and storage with Bayesian Networks},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian Networks,CCS,Risk assessment},\\n pages = {150-159},\\n volume = {35},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1750583615000262},\\n month = {4},\\n id = {4e33b138-ca45-3429-8b20-cd35252bbabf},\\n created = {2015-04-11T19:52:03.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The complex system required for carbon capture and storage (CCS) encompasses numerous sub-systems with inter-dependencies and large parameter uncertainties that propagate throughout the system. Exploring and understanding these inter-dependencies and uncertainties is invaluable for developing robust risk information. Bayesian Networks (BN), a decision support tool, are being increasingly used in the broader risk assessment community and show promise for use in CCS. BNs explore the dependencies and uncertainties within a system and have the potential to provide a better understanding of risk than more traditional tools such as logic trees or other less integrated approaches. Working with experts from within the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), we have developed a generic BN structure for the storage sub-system of CCS which can be used to guide the development of BNs for other CCS applications and for use in both diagnostic and predictive analysis. This bi-directionality provides one of the more important benefits of BNs; it allows for (1) traditional bottom-up risk assessment where the likely consequences based on the expected state of the system can be calculated and also (2) top-down, or outcome oriented risk, where the state of the system leading to a particular outcome, such as the likelihood of 2% leakage in 1000 years, is determined. This allows for a comprehensive sensitivity analysis which highlights important contributors to the risk and also where additional knowledge may benefit the project and reduce uncertainty. A robust expert elicitation procedure, for both the development of the network structure and the determination of event probabilities, is an integral part of the use of any such BN tool in CCS. Finally, we show the direct application of a smaller CCS BN by the CO2CRC.},\\n bibtype = {article},\\n author = {Gerstenberger, M.C. and Christophersen, A. and Buxton, R. and Nicol, A.},\\n doi = {10.1016/j.ijggc.2015.01.010},\\n journal = {International Journal of Greenhouse Gas Control}\\n}\",\"author_short\":[\"Gerstenberger,  M.\",\"Christophersen,  A.\",\"Buxton,  R.\",\"Nicol,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1750583615000262\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"CCS\",\"Risk assessment\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessing pricing assumptions for weather index insurance in a changing climate\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Adaptation,Bayesian Networks,Climate modeling,India,Uncertainty\",\"pages\":\"76-91\",\"volume\":\"1\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S2212096314000023\",\"id\":\"10344d5f-c88c-3aaf-869a-863ec53e1c06\",\"created\":\"2015-04-11T19:52:11.000Z\",\"accessed\":\"2015-03-17\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not these products are themselves resilient to climate change has not been well studied. Given climate variability and climate change, an over-reliance on historical climate observations to guide the design of such products can result in premiums which mislead policyholders and insurers alike, about the magnitude of underlying risks. Here, a method to incorporate different sources of climate data into the product design phase is presented. Bayesian Networks are constructed to demonstrate how insurers can assess the product viability from a climate perspective, using past observations and simulations of future climate. Sensitivity analyses illustrate the dependence of pricing decisions on both the choice of information, and the method for incorporating such data. The methods and their sensitivities are illustrated using a case study analysing the provision of index-based crop insurance in Kolhapur, India. We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data.\",\"bibtype\":\"article\",\"author\":\"Daron, J.D. and Stainforth, D.A.\",\"doi\":\"10.1016/j.crm.2014.01.001\",\"journal\":\"Climate Risk Management\",\"bibtex\":\"@article{\\n title = {Assessing pricing assumptions for weather index insurance in a changing climate},\\n type = {article},\\n year = {2014},\\n keywords = {Adaptation,Bayesian Networks,Climate modeling,India,Uncertainty},\\n pages = {76-91},\\n volume = {1},\\n websites = {http://www.sciencedirect.com/science/article/pii/S2212096314000023},\\n id = {10344d5f-c88c-3aaf-869a-863ec53e1c06},\\n created = {2015-04-11T19:52:11.000Z},\\n accessed = {2015-03-17},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not these products are themselves resilient to climate change has not been well studied. Given climate variability and climate change, an over-reliance on historical climate observations to guide the design of such products can result in premiums which mislead policyholders and insurers alike, about the magnitude of underlying risks. Here, a method to incorporate different sources of climate data into the product design phase is presented. Bayesian Networks are constructed to demonstrate how insurers can assess the product viability from a climate perspective, using past observations and simulations of future climate. Sensitivity analyses illustrate the dependence of pricing decisions on both the choice of information, and the method for incorporating such data. The methods and their sensitivities are illustrated using a case study analysing the provision of index-based crop insurance in Kolhapur, India. We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data.},\\n bibtype = {article},\\n author = {Daron, J.D. and Stainforth, D.A.},\\n doi = {10.1016/j.crm.2014.01.001},\\n journal = {Climate Risk Management}\\n}\",\"author_short\":[\"Daron,  J.\",\"Stainforth,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S2212096314000023\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014\",\"role\":\"author\",\"keyword\":[\"Adaptation\",\"Bayesian Networks\",\"Climate modeling\",\"India\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis\",\"type\":\"article\",\"year\":\"2001\",\"keywords\":\"Bayesian networks,Computer vision,Ecosystem analysis,Hydrologic modeling,Image analysis,Image feature extraction,Image segmentation,Knowledge integration,Monitoring urban growth\",\"pages\":\"435-444\",\"volume\":\"5\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1093019101000958\",\"month\":\"11\",\"id\":\"40ab50eb-80b4-34d8-882d-a222c43f65d0\",\"created\":\"2015-04-11T19:52:11.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this paper, we discuss the use of hierarchical tree-structured Bayesian networks for integrating knowledge concerning contextual relationships between environmentally relevant features extracted from digital imagery at multiple resolution scales. In our model, conditional probability distributions over continuous valued observations are parameterized using a mixture of multivariate Gaussian distributions. Separate classifiers for pixels and groups of pixels are used as sub-components of the overall model. The Bayesian formalism allows models to be composed in a systematic and statistically sound manner. We illustrate how this approach can be used to resolve ambiguity leading to classification errors and thus improve techniques for the classification of land use from aerial imagery. We present an example relevant to ecosystem analysis, the monitoring of urban growth and the automatic generation of input parameters for hydrologic models.\",\"bibtype\":\"article\",\"author\":\"Pal, Chris and Swayne, Dave and Frey, Brendan\",\"doi\":\"10.1016/S1093-0191(01)00095-8\",\"journal\":\"Advances in Environmental Research\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis},\\n type = {article},\\n year = {2001},\\n keywords = {Bayesian networks,Computer vision,Ecosystem analysis,Hydrologic modeling,Image analysis,Image feature extraction,Image segmentation,Knowledge integration,Monitoring urban growth},\\n pages = {435-444},\\n volume = {5},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1093019101000958},\\n month = {11},\\n id = {40ab50eb-80b4-34d8-882d-a222c43f65d0},\\n created = {2015-04-11T19:52:11.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this paper, we discuss the use of hierarchical tree-structured Bayesian networks for integrating knowledge concerning contextual relationships between environmentally relevant features extracted from digital imagery at multiple resolution scales. In our model, conditional probability distributions over continuous valued observations are parameterized using a mixture of multivariate Gaussian distributions. Separate classifiers for pixels and groups of pixels are used as sub-components of the overall model. The Bayesian formalism allows models to be composed in a systematic and statistically sound manner. We illustrate how this approach can be used to resolve ambiguity leading to classification errors and thus improve techniques for the classification of land use from aerial imagery. We present an example relevant to ecosystem analysis, the monitoring of urban growth and the automatic generation of input parameters for hydrologic models.},\\n bibtype = {article},\\n author = {Pal, Chris and Swayne, Dave and Frey, Brendan},\\n doi = {10.1016/S1093-0191(01)00095-8},\\n journal = {Advances in Environmental Research},\\n number = {4}\\n}\",\"author_short\":[\"Pal,  C.\",\"Swayne,  D.\",\"Frey,  B.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1093019101000958\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Computer vision\",\"Ecosystem analysis\",\"Hydrologic modeling\",\"Image analysis\",\"Image feature extraction\",\"Image segmentation\",\"Knowledge integration\",\"Monitoring urban growth\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian Network,Integrated Modelling,Sustainability Appraisal,Urban River Corridor\",\"pages\":\"687-697\",\"volume\":\"13\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1878029612000631\",\"id\":\"2267e51e-912e-347d-ac26-635682b9676f\",\"created\":\"2015-04-11T19:52:14.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Sustainability Appraisal (SA) is mandatory under the relevant legislation of UK (DCLG, 2008a) and applies to the preparation of Regional Spatial Strategies, Development Plans and Supplementary Planning documents. SA is a complex task that involves integration of social, environmental and economic considerations into formal plans and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical assessment can facilitate discussion, but these can only partially inform decision makers as many important aspects of sustainability are abstract and not quantifiable. Such abstract criteria however can be modelled using a Bayesian Network (BN), combining expert opinions, empirical evidence and other information such as model simulation, survey etc. This paper discusses the work of the URSULA project at the University of Sheffield, in which a participative and integrative approach to urban river corridor development, incorporating the principal of sustainability was used. The project used a case study site in Sheffield, UK, and three alternative scenarios were developed, incorporating a number of possible riverside design features. Scenarios were fully designed and visualised using a variety of different media and a sustainability appraisal was undertaken using a broad range of environmental, social and economic indicators. Experts’ assessment logics were captured through mind mapping and further expert elicitation was used to develop an integrated model for SA. The BN approach allows model complexity to be reduced to a level appropriate for an assessment process, whilst still taking complex system interactions implicitly into account. The integrated SA model is being used to develop better design by optimising different design elements in order to deliver an optimum (re)-development plan.\",\"bibtype\":\"article\",\"author\":\"Kumar, Vikas and Rouquette, J.R. and Lerner, D.N.\",\"doi\":\"10.1016/j.proenv.2012.01.062\",\"journal\":\"Procedia Environmental Sciences\",\"bibtex\":\"@article{\\n title = {Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian Network,Integrated Modelling,Sustainability Appraisal,Urban River Corridor},\\n pages = {687-697},\\n volume = {13},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029612000631},\\n id = {2267e51e-912e-347d-ac26-635682b9676f},\\n created = {2015-04-11T19:52:14.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Sustainability Appraisal (SA) is mandatory under the relevant legislation of UK (DCLG, 2008a) and applies to the preparation of Regional Spatial Strategies, Development Plans and Supplementary Planning documents. SA is a complex task that involves integration of social, environmental and economic considerations into formal plans and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical assessment can facilitate discussion, but these can only partially inform decision makers as many important aspects of sustainability are abstract and not quantifiable. Such abstract criteria however can be modelled using a Bayesian Network (BN), combining expert opinions, empirical evidence and other information such as model simulation, survey etc. This paper discusses the work of the URSULA project at the University of Sheffield, in which a participative and integrative approach to urban river corridor development, incorporating the principal of sustainability was used. The project used a case study site in Sheffield, UK, and three alternative scenarios were developed, incorporating a number of possible riverside design features. Scenarios were fully designed and visualised using a variety of different media and a sustainability appraisal was undertaken using a broad range of environmental, social and economic indicators. Experts’ assessment logics were captured through mind mapping and further expert elicitation was used to develop an integrated model for SA. The BN approach allows model complexity to be reduced to a level appropriate for an assessment process, whilst still taking complex system interactions implicitly into account. The integrated SA model is being used to develop better design by optimising different design elements in order to deliver an optimum (re)-development plan.},\\n bibtype = {article},\\n author = {Kumar, Vikas and Rouquette, J.R. and Lerner, D.N.},\\n doi = {10.1016/j.proenv.2012.01.062},\\n journal = {Procedia Environmental Sciences}\\n}\",\"author_short\":[\"Kumar,  V.\",\"Rouquette,  J.\",\"Lerner,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1878029612000631\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian Network\",\"Integrated Modelling\",\"Sustainability Appraisal\",\"Urban River Corridor\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Trust Model Based on Cloud Model and Bayesian Networks\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"cloud model ;Bayesian network,context aware,trust model,unceratinty\",\"pages\":\"452-459\",\"volume\":\"11\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1878029611008954\",\"id\":\"832ba102-96b9-3e71-917e-fe967b5c591a\",\"created\":\"2015-04-11T19:52:14.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.\",\"bibtype\":\"article\",\"author\":\"Jin, Bo and Wang, Yong and Liu, Zhenyan and Xue, Jingfeng\",\"doi\":\"10.1016/j.proenv.2011.12.072\",\"journal\":\"Procedia Environmental Sciences\",\"bibtex\":\"@article{\\n title = {A Trust Model Based on Cloud Model and Bayesian Networks},\\n type = {article},\\n year = {2011},\\n keywords = {cloud model ;Bayesian network,context aware,trust model,unceratinty},\\n pages = {452-459},\\n volume = {11},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029611008954},\\n id = {832ba102-96b9-3e71-917e-fe967b5c591a},\\n created = {2015-04-11T19:52:14.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.},\\n bibtype = {article},\\n author = {Jin, Bo and Wang, Yong and Liu, Zhenyan and Xue, Jingfeng},\\n doi = {10.1016/j.proenv.2011.12.072},\\n journal = {Procedia Environmental Sciences}\\n}\",\"author_short\":[\"Jin,  B.\",\"Wang,  Y.\",\"Liu,  Z.\",\"Xue,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1878029611008954\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011\",\"role\":\"author\",\"keyword\":[\"cloud model ;Bayesian network\",\"context aware\",\"trust model\",\"unceratinty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian Networks,Destruc*tion equipment,Health assessment,Health status,High-risk hazardous chemical wastes\",\"pages\":\"192-201\",\"volume\":\"16\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1878029612005658\",\"id\":\"42ee5947-da27-3dba-9e58-0291cce06870\",\"created\":\"2015-04-11T19:52:14.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.\",\"bibtype\":\"article\",\"author\":\"Zhang, Hongyuan and Zhang, Jing and Liu, Xuecheng and Yan, Guohui and Liu, Yanzhao\",\"doi\":\"10.1016/j.proenv.2012.10.027\",\"journal\":\"Procedia Environmental Sciences\",\"bibtex\":\"@article{\\n title = {Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian Networks,Destruc*tion equipment,Health assessment,Health status,High-risk hazardous chemical wastes},\\n pages = {192-201},\\n volume = {16},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029612005658},\\n id = {42ee5947-da27-3dba-9e58-0291cce06870},\\n created = {2015-04-11T19:52:14.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.},\\n bibtype = {article},\\n author = {Zhang, Hongyuan and Zhang, Jing and Liu, Xuecheng and Yan, Guohui and Liu, Yanzhao},\\n doi = {10.1016/j.proenv.2012.10.027},\\n journal = {Procedia Environmental Sciences}\\n}\",\"author_short\":[\"Zhang,  H.\",\"Zhang,  J.\",\"Liu,  X.\",\"Yan,  G.\",\"Liu,  Y.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1878029612005658\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Destruc*tion equipment\",\"Health assessment\",\"Health status\",\"High-risk hazardous chemical wastes\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"EM-algorithm,Gaussian Bayesian networks (GBNs),Moderate Resolution Imaging Spectroradiometer (MOD,leaf area index (LAI)\",\"pages\":\"74-79\",\"volume\":\"7\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1878029611001411\",\"id\":\"499bacd1-d3b3-347b-8c68-3547a1cb097a\",\"created\":\"2015-04-11T19:52:14.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Leaf area index (LAI) is a biophysical variable that is related to atmosphere-biosphere exchange of CO2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products (LAI MODIS). The LAI MODIS has been used to improve the physiological principles predicting growth (3-PG) model within a Bayesian Network (BN) set-up. The MODIS time series, however, contains gaps caused by persistent clouds, cloud contamination, and other retrieval problems. We therefore formulated the EM-algorithm to estimate the missing MODIS LAI values. The EM-algorithm is applied to three different cases: successive and not successive two winter seasons, and not successive missing MODIS LAI during the time study of 26 successive months at which the performance of the BN is assessed. Results show that the MODIS LAI is estimated such that the maximum value of the mean absolute error between the original MODIS LAI and the estimated MODIS LAI by EM-algorithm is 0.16. This is a low value, and shows the success of our approach. Moreover, the BN output improves when the EM-algorithm is carried out to estimate the inconsecutive missing MODIS LAI such that the root mean square error reduces from 1.57 to 1.49. We conclude that the EM-algorithm within a BN can handle the missing MODIS LAI values and that it improves estimation of the LAI.\",\"bibtype\":\"article\",\"author\":\"Mustafaa, Y.T. and Tolpekin, V. and Stein, A.\",\"doi\":\"10.1016/j.proenv.2011.07.014\",\"journal\":\"Procedia Environmental Sciences\",\"bibtex\":\"@article{\\n title = {Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates},\\n type = {article},\\n year = {2011},\\n keywords = {EM-algorithm,Gaussian Bayesian networks (GBNs),Moderate Resolution Imaging Spectroradiometer (MOD,leaf area index (LAI)},\\n pages = {74-79},\\n volume = {7},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029611001411},\\n id = {499bacd1-d3b3-347b-8c68-3547a1cb097a},\\n created = {2015-04-11T19:52:14.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Leaf area index (LAI) is a biophysical variable that is related to atmosphere-biosphere exchange of CO2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products (LAI MODIS). The LAI MODIS has been used to improve the physiological principles predicting growth (3-PG) model within a Bayesian Network (BN) set-up. The MODIS time series, however, contains gaps caused by persistent clouds, cloud contamination, and other retrieval problems. We therefore formulated the EM-algorithm to estimate the missing MODIS LAI values. The EM-algorithm is applied to three different cases: successive and not successive two winter seasons, and not successive missing MODIS LAI during the time study of 26 successive months at which the performance of the BN is assessed. Results show that the MODIS LAI is estimated such that the maximum value of the mean absolute error between the original MODIS LAI and the estimated MODIS LAI by EM-algorithm is 0.16. This is a low value, and shows the success of our approach. Moreover, the BN output improves when the EM-algorithm is carried out to estimate the inconsecutive missing MODIS LAI such that the root mean square error reduces from 1.57 to 1.49. We conclude that the EM-algorithm within a BN can handle the missing MODIS LAI values and that it improves estimation of the LAI.},\\n bibtype = {article},\\n author = {Mustafaa, Y.T. and Tolpekin, V. and Stein, A.},\\n doi = {10.1016/j.proenv.2011.07.014},\\n journal = {Procedia Environmental Sciences}\\n}\",\"author_short\":[\"Mustafaa,  Y.\",\"Tolpekin,  V.\",\"Stein,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1878029611001411\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011\",\"role\":\"author\",\"keyword\":[\"EM-algorithm\",\"Gaussian Bayesian networks (GBNs)\",\"Moderate Resolution Imaging Spectroradiometer (MOD\",\"leaf area index (LAI)\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Bayesian network,Cyanobacteria,DOOBN,Dynamic,IBN,Lyngbya majuscula,OOBN,Object oriented\",\"pages\":\"27-37\",\"volume\":\"69\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0141113609001032\",\"month\":\"2\",\"id\":\"32672e3a-e7fd-34b5-befa-92b0a26378f9\",\"created\":\"2015-04-11T19:52:18.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Blooms of the cyanobacteria Lyngbya majuscula have occurred for decades around the world. However, with the increase in size and frequency of these blooms, coupled with the toxicity of such algae and their increased biomass, they have become substantial environmental and health issues. It is therefore imperative to develop a better understanding of the scientific and management factors impacting on Lyngbya bloom initiation. This paper suggests an Integrated Bayesian Network (IBN) approach that facilitates the merger of the research being conducted by various parties on Lyngbya. Pivotal to this approach are two Bayesian networks modelling the management and scientific factors of bloom initiation. The research found that Bayesian Networks (BN) and specifically Object Oriented BNs (OOBN) and Dynamic OOBNs facilitate an integrated approach to modelling ecological issues of concern. The merger of multiple models which explore different aspects of the problem through an IBN approach can apply to many multi-faceted environmental problems.\",\"bibtype\":\"article\",\"author\":\"Johnson, Sandra and Fielding, Fiona and Hamilton, Grant and Mengersen, Kerrie\",\"doi\":\"10.1016/j.marenvres.2009.07.004\",\"journal\":\"Marine Environmental Research\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation},\\n type = {article},\\n year = {2010},\\n keywords = {Bayesian network,Cyanobacteria,DOOBN,Dynamic,IBN,Lyngbya majuscula,OOBN,Object oriented},\\n pages = {27-37},\\n volume = {69},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0141113609001032},\\n month = {2},\\n id = {32672e3a-e7fd-34b5-befa-92b0a26378f9},\\n created = {2015-04-11T19:52:18.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Blooms of the cyanobacteria Lyngbya majuscula have occurred for decades around the world. However, with the increase in size and frequency of these blooms, coupled with the toxicity of such algae and their increased biomass, they have become substantial environmental and health issues. It is therefore imperative to develop a better understanding of the scientific and management factors impacting on Lyngbya bloom initiation. This paper suggests an Integrated Bayesian Network (IBN) approach that facilitates the merger of the research being conducted by various parties on Lyngbya. Pivotal to this approach are two Bayesian networks modelling the management and scientific factors of bloom initiation. The research found that Bayesian Networks (BN) and specifically Object Oriented BNs (OOBN) and Dynamic OOBNs facilitate an integrated approach to modelling ecological issues of concern. The merger of multiple models which explore different aspects of the problem through an IBN approach can apply to many multi-faceted environmental problems.},\\n bibtype = {article},\\n author = {Johnson, Sandra and Fielding, Fiona and Hamilton, Grant and Mengersen, Kerrie},\\n doi = {10.1016/j.marenvres.2009.07.004},\\n journal = {Marine Environmental Research},\\n number = {1}\\n}\",\"author_short\":[\"Johnson,  S.\",\"Fielding,  F.\",\"Hamilton,  G.\",\"Mengersen,  K.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0141113609001032\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Cyanobacteria\",\"DOOBN\",\"Dynamic\",\"IBN\",\"Lyngbya majuscula\",\"OOBN\",\"Object oriented\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Network,China,Exports,Modelling,Nitrogen,Vegetable\",\"pages\":\"170-181\",\"volume\":\"46\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000716\",\"month\":\"8\",\"id\":\"43f34b8d-12ab-3de0-bfef-40b25d3b2108\",\"created\":\"2015-04-11T19:52:19.000Z\",\"accessed\":\"2015-02-26\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Vegetable farms are one of many nitrogen (N) sources adversely affecting Lake Taihu in eastern China. Given the lack of quantitative “cause and effect” relationships and data relating to these systems, we developed a conceptual Bayesian network to investigate and demonstrate causal relationships and the effects of different mitigation strategies on N exports from vegetable farms in the Lake Taihu region. Structurally, the network comprised one primary transport factor, one primary source factor and three post-mobilisation strategies, and three output factors. In general the network suggests that N exports are more sensitive to transport factors (i.e. runoff volumes) than source factors (i.e. fertiliser application rates) although the cumulative effects of excessive fertiliser were not considered. Post-mobilisation mitigations such as wetlands and ecoditches appear to be particularly effective in decreasing N exports however their implementation on a regional scale may be limited by land availability. While optimising N inputs would be prudent, the network suggests that better irrigation practice, including improved irrigation scheduling, using less imported water and optimising rainfall utilisation would be more effective in achieving environmental goals than simply limiting N supply.\",\"bibtype\":\"article\",\"author\":\"Nash, David and Waters, David and Buldu, Andres and Wu, Yuming and Lin, Yaping and Yang, Weiqiu and Song, Yuzhi and Shu, Jianhua and Qin, Wei and Hannah, Murray\",\"doi\":\"10.1016/j.envsoft.2013.03.008\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Network,China,Exports,Modelling,Nitrogen,Vegetable},\\n pages = {170-181},\\n volume = {46},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000716},\\n month = {8},\\n id = {43f34b8d-12ab-3de0-bfef-40b25d3b2108},\\n created = {2015-04-11T19:52:19.000Z},\\n accessed = {2015-02-26},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Vegetable farms are one of many nitrogen (N) sources adversely affecting Lake Taihu in eastern China. Given the lack of quantitative “cause and effect” relationships and data relating to these systems, we developed a conceptual Bayesian network to investigate and demonstrate causal relationships and the effects of different mitigation strategies on N exports from vegetable farms in the Lake Taihu region. Structurally, the network comprised one primary transport factor, one primary source factor and three post-mobilisation strategies, and three output factors. In general the network suggests that N exports are more sensitive to transport factors (i.e. runoff volumes) than source factors (i.e. fertiliser application rates) although the cumulative effects of excessive fertiliser were not considered. Post-mobilisation mitigations such as wetlands and ecoditches appear to be particularly effective in decreasing N exports however their implementation on a regional scale may be limited by land availability. While optimising N inputs would be prudent, the network suggests that better irrigation practice, including improved irrigation scheduling, using less imported water and optimising rainfall utilisation would be more effective in achieving environmental goals than simply limiting N supply.},\\n bibtype = {article},\\n author = {Nash, David and Waters, David and Buldu, Andres and Wu, Yuming and Lin, Yaping and Yang, Weiqiu and Song, Yuzhi and Shu, Jianhua and Qin, Wei and Hannah, Murray},\\n doi = {10.1016/j.envsoft.2013.03.008},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Nash,  D.\",\"Waters,  D.\",\"Buldu,  A.\",\"Wu,  Y.\",\"Lin,  Y.\",\"Yang,  W.\",\"Song,  Y.\",\"Shu,  J.\",\"Qin,  W.\",\"Hannah,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213000716\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Network\",\"China\",\"Exports\",\"Modelling\",\"Nitrogen\",\"Vegetable\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management.\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Decision Making,England,Environment,Knowledge,Models, Theoretical,Water\",\"pages\":\"116-27\",\"volume\":\"96\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479711003975\",\"month\":\"4\",\"day\":\"15\",\"id\":\"1bf4dbe7-b7d0-3be6-833a-826220dea6f5\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.\",\"bibtype\":\"article\",\"author\":\"Holzkämper, Annelie and Kumar, Vikas and Surridge, Ben W J and Paetzold, Achim and Lerner, David N\",\"doi\":\"10.1016/j.jenvman.2011.10.016\",\"journal\":\"Journal of environmental management\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management.},\\n type = {article},\\n year = {2012},\\n keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Decision Making,England,Environment,Knowledge,Models, Theoretical,Water},\\n pages = {116-27},\\n volume = {96},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479711003975},\\n month = {4},\\n day = {15},\\n id = {1bf4dbe7-b7d0-3be6-833a-826220dea6f5},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.},\\n bibtype = {article},\\n author = {Holzkämper, Annelie and Kumar, Vikas and Surridge, Ben W J and Paetzold, Achim and Lerner, David N},\\n doi = {10.1016/j.jenvman.2011.10.016},\\n journal = {Journal of environmental management},\\n number = {1}\\n}\",\"author_short\":[\"Holzkämper,  A.\",\"Kumar,  V.\",\"Surridge,  B., W., J.\",\"Paetzold,  A.\",\"Lerner,  D., N.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479711003975\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Conservation of Natural Resources\",\"Conservation of Natural Resources: methods\",\"Decision Making\",\"England\",\"Environment\",\"Knowledge\",\"Models\",\"Theoretical\",\"Water\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Algorithms,Bayes Theorem,Biological Evolution,Conservation of Natural Resources,Ecosystem,Environment,Geography,Models, Theoretical,Probability,Scotland,Software\",\"pages\":\"236-50\",\"volume\":\"90\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479707003465\",\"month\":\"1\",\"id\":\"dd17dce9-55c0-3c0d-8b3c-e0151478561c\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.\",\"bibtype\":\"article\",\"author\":\"Aitkenhead, M J and Aalders, I H\",\"doi\":\"10.1016/j.jenvman.2007.09.010\",\"journal\":\"Journal of environmental management\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.},\\n type = {article},\\n year = {2009},\\n keywords = {Algorithms,Bayes Theorem,Biological Evolution,Conservation of Natural Resources,Ecosystem,Environment,Geography,Models, Theoretical,Probability,Scotland,Software},\\n pages = {236-50},\\n volume = {90},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479707003465},\\n month = {1},\\n id = {dd17dce9-55c0-3c0d-8b3c-e0151478561c},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.},\\n bibtype = {article},\\n author = {Aitkenhead, M J and Aalders, I H},\\n doi = {10.1016/j.jenvman.2007.09.010},\\n journal = {Journal of environmental management},\\n number = {1}\\n}\",\"author_short\":[\"Aitkenhead,  M., J.\",\"Aalders,  I., H.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479707003465\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009\",\"role\":\"author\",\"keyword\":[\"Algorithms\",\"Bayes Theorem\",\"Biological Evolution\",\"Conservation of Natural Resources\",\"Ecosystem\",\"Environment\",\"Geography\",\"Models\",\"Theoretical\",\"Probability\",\"Scotland\",\"Software\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Facing uncertainty in ecosystem services-based resource management.\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Ecosystem,Uncertainty\",\"pages\":\"S145-54\",\"volume\":\"127 Suppl\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479712003921\",\"month\":\"9\",\"id\":\"fa8ccc4c-6586-33a7-afda-0ca728827b7c\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-03-26\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.\",\"bibtype\":\"article\",\"author\":\"Grêt-Regamey, Adrienne and Brunner, Sibyl H and Altwegg, Jürg and Bebi, Peter\",\"doi\":\"10.1016/j.jenvman.2012.07.028\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Facing uncertainty in ecosystem services-based resource management.},\\n type = {article},\\n year = {2013},\\n keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Ecosystem,Uncertainty},\\n pages = {S145-54},\\n volume = {127 Suppl},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479712003921},\\n month = {9},\\n id = {fa8ccc4c-6586-33a7-afda-0ca728827b7c},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-03-26},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.},\\n bibtype = {article},\\n author = {Grêt-Regamey, Adrienne and Brunner, Sibyl H and Altwegg, Jürg and Bebi, Peter},\\n doi = {10.1016/j.jenvman.2012.07.028},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Grêt-Regamey,  A.\",\"Brunner,  S., H.\",\"Altwegg,  J.\",\"Bebi,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479712003921\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Conservation of Natural Resources\",\"Conservation of Natural Resources: methods\",\"Ecosystem\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain.\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Agriculture,Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Consumer Participation,Decision Making,Income,Models, Economic,Models, Theoretical,Questionnaires,Rivers,Spain,Uncertainty\",\"pages\":\"400-12\",\"volume\":\"128\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479713003472\",\"month\":\"10\",\"day\":\"15\",\"id\":\"a4674948-9d5e-3785-a9c3-ed8069a4f597\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-03-20\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each other's views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.\",\"bibtype\":\"article\",\"author\":\"Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John\",\"doi\":\"10.1016/j.jenvman.2013.05.019\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain.},\\n type = {article},\\n year = {2013},\\n keywords = {Agriculture,Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Consumer Participation,Decision Making,Income,Models, Economic,Models, Theoretical,Questionnaires,Rivers,Spain,Uncertainty},\\n pages = {400-12},\\n volume = {128},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713003472},\\n month = {10},\\n day = {15},\\n id = {a4674948-9d5e-3785-a9c3-ed8069a4f597},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-03-20},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each other's views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.},\\n bibtype = {article},\\n author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},\\n doi = {10.1016/j.jenvman.2013.05.019},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Carmona,  G.\",\"Varela-Ortega,  C.\",\"Bromley,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479713003472\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013\",\"role\":\"author\",\"keyword\":[\"Agriculture\",\"Bayes Theorem\",\"Conservation of Natural Resources\",\"Conservation of Natural Resources: methods\",\"Consumer Participation\",\"Decision Making\",\"Income\",\"Models\",\"Economic\",\"Models\",\"Theoretical\",\"Questionnaires\",\"Rivers\",\"Spain\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayes Theorem,Dairying,Environment,Industry\",\"pages\":\"184-92\",\"volume\":\"133\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479713007548\",\"month\":\"1\",\"day\":\"15\",\"id\":\"e81c4063-dfc3-35dc-b60b-a148baecaf10\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-02-28\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.\",\"bibtype\":\"article\",\"author\":\"Buys, L and Mengersen, K and Johnson, S and van Buuren, N and Chauvin, A\",\"doi\":\"10.1016/j.jenvman.2013.12.013\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.},\\n type = {article},\\n year = {2014},\\n keywords = {Bayes Theorem,Dairying,Environment,Industry},\\n pages = {184-92},\\n volume = {133},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713007548},\\n month = {1},\\n day = {15},\\n id = {e81c4063-dfc3-35dc-b60b-a148baecaf10},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-02-28},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.},\\n bibtype = {article},\\n author = {Buys, L and Mengersen, K and Johnson, S and van Buuren, N and Chauvin, A},\\n doi = {10.1016/j.jenvman.2013.12.013},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Buys,  L.\",\"Mengersen,  K.\",\"Johnson,  S.\",\"van Buuren,  N.\",\"Chauvin,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479713007548\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"Dairying\",\"Environment\",\"Industry\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian Networks as a screening tool for exposure assessment.\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Australia,Bayes Theorem,Environmental Exposure,Environmental Exposure: analysis,Risk Assessment,Risk Assessment: methods,Soil Pollutants,Soil Pollutants: analysis\",\"pages\":\"68-76\",\"volume\":\"123\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479713001709\",\"month\":\"7\",\"day\":\"15\",\"id\":\"d1800489-6042-3851-87b8-ec9256ddcf34\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A tiered approach to contamination exposure assessment is currently adopted in many countries. Increasing the site-specific information in exposure assessments is generally recommended when guideline values for contaminants in soil are exceeded. This work details a Bayesian Network (BN) approach to developing a site-specific environmental exposure assessment that focuses on the simple mapping and assessment of assumptions and the effect of new data on assessment outcomes. The BN approach was applied to a floodplain system in New South Wales, Australia, where site-specific information about elevated antimony (Sb) concentrations and distribution in soils was available. Guidelines for exposure assessment in Australia are used as a template for this site, although the approach is generic. The BN-based assessment used an iterative approach starting with limited soil Sb data (41 samples ranging from 0 to 18 mg kg-(1) Sb) and extending the model with more detailed Sb data (145 samples ranging from 0 to 40 mg kg-(1) Sb). The analyses identified dominant exposure pathways and assessed the sensitivity of these pathways to changes in assumptions and the level of site-specific information available. In particular, there was a 10.8% probability of exceeding the tolerable daily intake of Sb in the case study when the limited soil Sb data was used, which increased to 26.2% with the more detailed sampling regime. There was also a 47% decrease in the probability of overexposure to Sb when the dermal bioavailability of arsenic (a similar metalloid) was used as a surrogate measure instead of a default bioavailability of 100%. We conclude that the BN approach to soil exposure assessment has merit both in the context of Australian and international soil exposure assessments.\",\"bibtype\":\"article\",\"author\":\"Tighe, Matthew and Pollino, Carmel A and Wilson, Susan C\",\"doi\":\"10.1016/j.jenvman.2013.03.018\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Bayesian Networks as a screening tool for exposure assessment.},\\n type = {article},\\n year = {2013},\\n keywords = {Australia,Bayes Theorem,Environmental Exposure,Environmental Exposure: analysis,Risk Assessment,Risk Assessment: methods,Soil Pollutants,Soil Pollutants: analysis},\\n pages = {68-76},\\n volume = {123},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713001709},\\n month = {7},\\n day = {15},\\n id = {d1800489-6042-3851-87b8-ec9256ddcf34},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A tiered approach to contamination exposure assessment is currently adopted in many countries. Increasing the site-specific information in exposure assessments is generally recommended when guideline values for contaminants in soil are exceeded. This work details a Bayesian Network (BN) approach to developing a site-specific environmental exposure assessment that focuses on the simple mapping and assessment of assumptions and the effect of new data on assessment outcomes. The BN approach was applied to a floodplain system in New South Wales, Australia, where site-specific information about elevated antimony (Sb) concentrations and distribution in soils was available. Guidelines for exposure assessment in Australia are used as a template for this site, although the approach is generic. The BN-based assessment used an iterative approach starting with limited soil Sb data (41 samples ranging from 0 to 18 mg kg-(1) Sb) and extending the model with more detailed Sb data (145 samples ranging from 0 to 40 mg kg-(1) Sb). The analyses identified dominant exposure pathways and assessed the sensitivity of these pathways to changes in assumptions and the level of site-specific information available. In particular, there was a 10.8% probability of exceeding the tolerable daily intake of Sb in the case study when the limited soil Sb data was used, which increased to 26.2% with the more detailed sampling regime. There was also a 47% decrease in the probability of overexposure to Sb when the dermal bioavailability of arsenic (a similar metalloid) was used as a surrogate measure instead of a default bioavailability of 100%. We conclude that the BN approach to soil exposure assessment has merit both in the context of Australian and international soil exposure assessments.},\\n bibtype = {article},\\n author = {Tighe, Matthew and Pollino, Carmel A and Wilson, Susan C},\\n doi = {10.1016/j.jenvman.2013.03.018},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Tighe,  M.\",\"Pollino,  C., A.\",\"Wilson,  S., C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479713001709\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013\",\"role\":\"author\",\"keyword\":[\"Australia\",\"Bayes Theorem\",\"Environmental Exposure\",\"Environmental Exposure: analysis\",\"Risk Assessment\",\"Risk Assessment: methods\",\"Soil Pollutants\",\"Soil Pollutants: analysis\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Classifying environmentally significant urban land uses with satellite imagery.\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayes Theorem,California,Cities,Commerce,Environment,Housing,Industry,Recreation,Satellite Communications,Transportation,Water,Water Supply\",\"pages\":\"181-92\",\"volume\":\"86\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479706003975\",\"month\":\"1\",\"id\":\"2cca927c-aedc-3a85-9720-a78cdd55dc8a\",\"created\":\"2015-04-11T19:52:20.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.\",\"bibtype\":\"article\",\"author\":\"Park, Mi-Hyun and Stenstrom, Michael K\",\"doi\":\"10.1016/j.jenvman.2006.12.010\",\"journal\":\"Journal of environmental management\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Classifying environmentally significant urban land uses with satellite imagery.},\\n type = {article},\\n year = {2008},\\n keywords = {Bayes Theorem,California,Cities,Commerce,Environment,Housing,Industry,Recreation,Satellite Communications,Transportation,Water,Water Supply},\\n pages = {181-92},\\n volume = {86},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479706003975},\\n month = {1},\\n id = {2cca927c-aedc-3a85-9720-a78cdd55dc8a},\\n created = {2015-04-11T19:52:20.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.},\\n bibtype = {article},\\n author = {Park, Mi-Hyun and Stenstrom, Michael K},\\n doi = {10.1016/j.jenvman.2006.12.010},\\n journal = {Journal of environmental management},\\n number = {1}\\n}\",\"author_short\":[\"Park,  M.\",\"Stenstrom,  M., K.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479706003975\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008\",\"role\":\"author\",\"keyword\":[\"Bayes Theorem\",\"California\",\"Cities\",\"Commerce\",\"Environment\",\"Housing\",\"Industry\",\"Recreation\",\"Satellite Communications\",\"Transportation\",\"Water\",\"Water Supply\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Reforestation planning using Bayesian networks\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian networks,Environmental variables,GIS,Machine learning,Reforestation\",\"pages\":\"1285-1292\",\"volume\":\"24\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815209001224\",\"month\":\"11\",\"id\":\"e3ab2c9a-49e3-3ad0-8389-7ef8721d92ad\",\"created\":\"2015-04-11T19:52:26.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The aim of this research was to construct a reforestation model for woodland located in the basin of the river Liébana (NW Spain). This is essentially a pattern recognition problem: the class labels are types of woodland, and the variables for each point are environmental coordinates (referring to altitude, slope, rainfall, lithology, etc.). The model trained using data for existing wooded areas will serve as a guideline for the reforestation of deforested areas. Nonetheless, with a view to tackling reforestation from a more informed perspective, of interest is an interpretable model of relationships existing not just between woodland type and environmental variables but also between and among the environmental variables themselves. For this reason we used Bayesian networks, as a tool that is capable of constructing a causal model of the relationships existing between all the variables represented in the model. The prediction results obtained were compared with those for classical linear techniques, neural networks and support vector machines.\",\"bibtype\":\"article\",\"author\":\"Ordóñez Galán, C. and Matías, J.M. and Rivas, T. and Bastante, F.G.\",\"doi\":\"10.1016/j.envsoft.2009.05.009\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Reforestation planning using Bayesian networks},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian networks,Environmental variables,GIS,Machine learning,Reforestation},\\n pages = {1285-1292},\\n volume = {24},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001224},\\n month = {11},\\n id = {e3ab2c9a-49e3-3ad0-8389-7ef8721d92ad},\\n created = {2015-04-11T19:52:26.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The aim of this research was to construct a reforestation model for woodland located in the basin of the river Liébana (NW Spain). This is essentially a pattern recognition problem: the class labels are types of woodland, and the variables for each point are environmental coordinates (referring to altitude, slope, rainfall, lithology, etc.). The model trained using data for existing wooded areas will serve as a guideline for the reforestation of deforested areas. Nonetheless, with a view to tackling reforestation from a more informed perspective, of interest is an interpretable model of relationships existing not just between woodland type and environmental variables but also between and among the environmental variables themselves. For this reason we used Bayesian networks, as a tool that is capable of constructing a causal model of the relationships existing between all the variables represented in the model. The prediction results obtained were compared with those for classical linear techniques, neural networks and support vector machines.},\\n bibtype = {article},\\n author = {Ordóñez Galán, C. and Matías, J.M. and Rivas, T. and Bastante, F.G.},\\n doi = {10.1016/j.envsoft.2009.05.009},\\n journal = {Environmental Modelling & Software},\\n number = {11}\\n}\",\"author_short\":[\"Ordóñez Galán,  C.\",\"Matías,  J.\",\"Rivas,  T.\",\"Bastante,  F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815209001224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Environmental variables\",\"GIS\",\"Machine learning\",\"Reforestation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Continuous Bayesian networks,Landscape,Mixtures of truncated exponentials,Regression,Socioeconomic structure\",\"pages\":\"127-137\",\"volume\":\"57\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481521400067X\",\"month\":\"7\",\"id\":\"b8a790cb-d7e6-3755-a346-7ee7d5969aed\",\"created\":\"2015-04-11T19:52:26.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape–socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling.\",\"bibtype\":\"article\",\"author\":\"Ropero, R.F. and Aguilera, P.A. and Fernández, A. and Rumí, R.\",\"doi\":\"10.1016/j.envsoft.2014.02.016\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships},\\n type = {article},\\n year = {2014},\\n keywords = {Continuous Bayesian networks,Landscape,Mixtures of truncated exponentials,Regression,Socioeconomic structure},\\n pages = {127-137},\\n volume = {57},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521400067X},\\n month = {7},\\n id = {b8a790cb-d7e6-3755-a346-7ee7d5969aed},\\n created = {2015-04-11T19:52:26.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape–socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling.},\\n bibtype = {article},\\n author = {Ropero, R.F. and Aguilera, P.A. and Fernández, A. and Rumí, R.},\\n doi = {10.1016/j.envsoft.2014.02.016},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Ropero,  R.\",\"Aguilera,  P.\",\"Fernández,  A.\",\"Rumí,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481521400067X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014\",\"role\":\"author\",\"keyword\":[\"Continuous Bayesian networks\",\"Landscape\",\"Mixtures of truncated exponentials\",\"Regression\",\"Socioeconomic structure\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian networks in planning a large aquifer in Eastern Mancha, Spain\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Aquifer,Bayesian networks,Integrated management,Irrigated land,Stakeholders\",\"pages\":\"1089-1100\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481520600137X\",\"month\":\"8\",\"id\":\"f5832962-d077-3d3c-bc27-5c021c6ad676\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The Eastern Mancha Aquifer is located in the south-east of the Iberian Peninsula and is included in the hydrogeological unit of the same name. This aquifer is the main source of water for urban, industrial and agricultural supply within its area of influence. Over the past 30years, the transformation of dry crop lands in the area of this Unit into irrigated crop lands, through groundwater capture, has caused precise declines in piezometric levels of the aquifer, as extraction volumes have exceeded recharge water volumes. This work illustrates the results obtained by using Bayesian networks in the sustainable planning of the Eastern Mancha aquifer. The actions through which this goal can be met are the partial substitution of groundwater with surface water, the improvement of irrigation efficiency and the adequate control of water use.\",\"bibtype\":\"article\",\"author\":\"Martín de Santa Olalla, Francisco and Dominguez, Alfonso and Ortega, Fernando and Artigao, Alfonso and Fabeiro, Concepción\",\"doi\":\"10.1016/j.envsoft.2006.05.020\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Bayesian networks in planning a large aquifer in Eastern Mancha, Spain},\\n type = {article},\\n year = {2007},\\n keywords = {Aquifer,Bayesian networks,Integrated management,Irrigated land,Stakeholders},\\n pages = {1089-1100},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481520600137X},\\n month = {8},\\n id = {f5832962-d077-3d3c-bc27-5c021c6ad676},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The Eastern Mancha Aquifer is located in the south-east of the Iberian Peninsula and is included in the hydrogeological unit of the same name. This aquifer is the main source of water for urban, industrial and agricultural supply within its area of influence. Over the past 30years, the transformation of dry crop lands in the area of this Unit into irrigated crop lands, through groundwater capture, has caused precise declines in piezometric levels of the aquifer, as extraction volumes have exceeded recharge water volumes. This work illustrates the results obtained by using Bayesian networks in the sustainable planning of the Eastern Mancha aquifer. The actions through which this goal can be met are the partial substitution of groundwater with surface water, the improvement of irrigation efficiency and the adequate control of water use.},\\n bibtype = {article},\\n author = {Martín de Santa Olalla, Francisco and Dominguez, Alfonso and Ortega, Fernando and Artigao, Alfonso and Fabeiro, Concepción},\\n doi = {10.1016/j.envsoft.2006.05.020},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Martín de Santa Olalla,  F.\",\"Dominguez,  A.\",\"Ortega,  F.\",\"Artigao,  A.\",\"Fabeiro,  C.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481520600137X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007\",\"role\":\"author\",\"keyword\":[\"Aquifer\",\"Bayesian networks\",\"Integrated management\",\"Irrigated land\",\"Stakeholders\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An integrated approach to linking economic valuation and catchment modelling\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian networks,Catchment scale modelling,Choice experiments,Environmental values,Integrated water resources management,Knowledge integration,Model development\",\"pages\":\"92-102\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815210000940\",\"month\":\"1\",\"id\":\"afa3520f-faa3-30b8-b122-20ad1cbb0bf7\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-03-02\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.\",\"bibtype\":\"article\",\"author\":\"Kragt, M.E. and Newham, L.T.H. and Bennett, J. and Jakeman, A.J.\",\"doi\":\"10.1016/j.envsoft.2010.04.002\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {An integrated approach to linking economic valuation and catchment modelling},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian networks,Catchment scale modelling,Choice experiments,Environmental values,Integrated water resources management,Knowledge integration,Model development},\\n pages = {92-102},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000940},\\n month = {1},\\n id = {afa3520f-faa3-30b8-b122-20ad1cbb0bf7},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-03-02},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.},\\n bibtype = {article},\\n author = {Kragt, M.E. and Newham, L.T.H. and Bennett, J. and Jakeman, A.J.},\\n doi = {10.1016/j.envsoft.2010.04.002},\\n journal = {Environmental Modelling & Software},\\n number = {1}\\n}\",\"author_short\":[\"Kragt,  M.\",\"Newham,  L.\",\"Bennett,  J.\",\"Jakeman,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815210000940\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Catchment scale modelling\",\"Choice experiments\",\"Environmental values\",\"Integrated water resources management\",\"Knowledge integration\",\"Model development\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian network,Ecological risk assessment,Ecology,Fish\",\"pages\":\"1140-1152\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000788\",\"month\":\"8\",\"id\":\"c1d8f2b7-97e4-3a66-beda-57aa9fd2f928\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).\",\"bibtype\":\"article\",\"author\":\"Pollino, Carmel A. and Woodberry, Owen and Nicholson, Ann and Korb, Kevin and Hart, Barry T.\",\"doi\":\"10.1016/j.envsoft.2006.03.006\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian network,Ecological risk assessment,Ecology,Fish},\\n pages = {1140-1152},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000788},\\n month = {8},\\n id = {c1d8f2b7-97e4-3a66-beda-57aa9fd2f928},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).},\\n bibtype = {article},\\n author = {Pollino, Carmel A. and Woodberry, Owen and Nicholson, Ann and Korb, Kevin and Hart, Barry T.},\\n doi = {10.1016/j.envsoft.2006.03.006},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Pollino,  C., A.\",\"Woodberry,  O.\",\"Nicholson,  A.\",\"Korb,  K.\",\"Hart,  B., T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000788\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Ecological risk assessment\",\"Ecology\",\"Fish\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning\",\"type\":\"article\",\"year\":\"2005\",\"keywords\":\"Bayesian network,Integrated water resource management,Stakeholder participation,Uncertainty\",\"pages\":\"231-242\",\"volume\":\"20\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815204000404\",\"month\":\"2\",\"id\":\"ffad8d16-04b8-3fd8-9c56-255e6e9249a2\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Integrated management is the key to the sustainable development of Europe's water resources. This means that decisions need to be taken in the light of not only environmental considerations, but also their economic, social, and political impacts; it also requires the active participation of stakeholders in the decision making process. The problem is to find a practical way to achieve these aims. One approach is to use Bayesian networks (Bns): networks allow a range of different factors to be linked together, based on probabilistic dependencies, and at the same time provide a framework within which the contributions of stakeholders can be taken into account. A further strength is that Bns explicitly include the element of uncertainty related to any strategy or decision. The links are based on whatever data are available. This may be an extensive data set, output from a model or, in the absence of data, can be based on expert opinion. Networks are being developed for four catchments in Europe as part of the MERIT project; these are in the UK, Denmark, Italy and Spain. In each case stakeholder groups are contributing to the design of the networks that are used as a focus for the consultation process. As an example, the application to water management of a UK basin is discussed.\",\"bibtype\":\"article\",\"author\":\"Bromley, J. and Jackson, N.A. and Clymer, O.J. and Giacomello, A.M. and Jensen, F.V.\",\"doi\":\"10.1016/j.envsoft.2003.12.021\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning},\\n type = {article},\\n year = {2005},\\n keywords = {Bayesian network,Integrated water resource management,Stakeholder participation,Uncertainty},\\n pages = {231-242},\\n volume = {20},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815204000404},\\n month = {2},\\n id = {ffad8d16-04b8-3fd8-9c56-255e6e9249a2},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Integrated management is the key to the sustainable development of Europe's water resources. This means that decisions need to be taken in the light of not only environmental considerations, but also their economic, social, and political impacts; it also requires the active participation of stakeholders in the decision making process. The problem is to find a practical way to achieve these aims. One approach is to use Bayesian networks (Bns): networks allow a range of different factors to be linked together, based on probabilistic dependencies, and at the same time provide a framework within which the contributions of stakeholders can be taken into account. A further strength is that Bns explicitly include the element of uncertainty related to any strategy or decision. The links are based on whatever data are available. This may be an extensive data set, output from a model or, in the absence of data, can be based on expert opinion. Networks are being developed for four catchments in Europe as part of the MERIT project; these are in the UK, Denmark, Italy and Spain. In each case stakeholder groups are contributing to the design of the networks that are used as a focus for the consultation process. As an example, the application to water management of a UK basin is discussed.},\\n bibtype = {article},\\n author = {Bromley, J. and Jackson, N.A. and Clymer, O.J. and Giacomello, A.M. and Jensen, F.V.},\\n doi = {10.1016/j.envsoft.2003.12.021},\\n journal = {Environmental Modelling & Software},\\n number = {2}\\n}\",\"author_short\":[\"Bromley,  J.\",\"Jackson,  N.\",\"Clymer,  O.\",\"Giacomello,  A.\",\"Jensen,  F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815204000404\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Integrated water resource management\",\"Stakeholder participation\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling uncertainty in social–natural interactions\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Hybrid Bayesian networks,Mixtures of truncated exponentials,Socio-ecological system,Systemic change,Water flows\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214002096\",\"month\":\"8\",\"id\":\"a3a3542a-81ec-34e9-8a4a-84bd654a598e\",\"created\":\"2015-04-11T19:52:26.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Socio-ecological systems can be represented as a complex network of causal interactions. Modelling such systems requires methodologies that are able to take uncertainty into account. Due to their probabilistic nature, Bayesian networks are a powerful tool for representing complex systems where interactions between variables are subject to uncertainty. In this paper, we study the interactions between social and natural subsystems (land use and water flow components) using hybrid Bayesian networks based on the Mixture of Truncated Exponentials model. This study aims to provide a new methodology to model systemic change in a socio-ecological context. Two endogenous changes – agricultural intensification and the maintenance of traditional cropland – are proposed. Intensification of the agricultural practices leads to a rise in the rate of immigration to the area, as well as to greater water losses through evaporation. By contrast, maintenance of traditional cropland hardly changes the social structure, while increasing evapotranspiration rates and improving the control over runoff water. These results indicate that hybrid Bayesian networks are an excellent tool for modelling social–natural interactions.\",\"bibtype\":\"article\",\"author\":\"Ropero, R.F. and Rumí, R. and Aguilera, P.A.\",\"doi\":\"10.1016/j.envsoft.2014.07.008\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Modelling uncertainty in social–natural interactions},\\n type = {article},\\n year = {2014},\\n keywords = {Hybrid Bayesian networks,Mixtures of truncated exponentials,Socio-ecological system,Systemic change,Water flows},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002096},\\n month = {8},\\n id = {a3a3542a-81ec-34e9-8a4a-84bd654a598e},\\n created = {2015-04-11T19:52:26.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Socio-ecological systems can be represented as a complex network of causal interactions. Modelling such systems requires methodologies that are able to take uncertainty into account. Due to their probabilistic nature, Bayesian networks are a powerful tool for representing complex systems where interactions between variables are subject to uncertainty. In this paper, we study the interactions between social and natural subsystems (land use and water flow components) using hybrid Bayesian networks based on the Mixture of Truncated Exponentials model. This study aims to provide a new methodology to model systemic change in a socio-ecological context. Two endogenous changes – agricultural intensification and the maintenance of traditional cropland – are proposed. Intensification of the agricultural practices leads to a rise in the rate of immigration to the area, as well as to greater water losses through evaporation. By contrast, maintenance of traditional cropland hardly changes the social structure, while increasing evapotranspiration rates and improving the control over runoff water. These results indicate that hybrid Bayesian networks are an excellent tool for modelling social–natural interactions.},\\n bibtype = {article},\\n author = {Ropero, R.F. and Rumí, R. and Aguilera, P.A.},\\n doi = {10.1016/j.envsoft.2014.07.008},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Ropero,  R.\",\"Rumí,  R.\",\"Aguilera,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214002096\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014\",\"role\":\"author\",\"keyword\":[\"Hybrid Bayesian networks\",\"Mixtures of truncated exponentials\",\"Socio-ecological system\",\"Systemic change\",\"Water flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian Networks and participatory modelling in water resource management\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian Networks,Decision making,Model integration,Participatory modelling,Water resources planning\",\"pages\":\"1075-1088\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815206001435\",\"month\":\"8\",\"id\":\"b80f9f8d-5320-37b3-a179-4ff6db8b8547\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.\",\"bibtype\":\"article\",\"author\":\"Castelletti, A. and Soncini-Sessa, R.\",\"doi\":\"10.1016/j.envsoft.2006.06.003\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Bayesian Networks and participatory modelling in water resource management},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian Networks,Decision making,Model integration,Participatory modelling,Water resources planning},\\n pages = {1075-1088},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001435},\\n month = {8},\\n id = {b80f9f8d-5320-37b3-a179-4ff6db8b8547},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.},\\n bibtype = {article},\\n author = {Castelletti, A. and Soncini-Sessa, R.},\\n doi = {10.1016/j.envsoft.2006.06.003},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Castelletti,  A.\",\"Soncini-Sessa,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815206001435\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Decision making\",\"Model integration\",\"Participatory modelling\",\"Water resources planning\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A software system for assessing the spatially distributed ecological risk posed by oil shipping\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Ecology,Geospatial,Maritime accident,Oil spill,Risk assessment\",\"pages\":\"1-11\",\"volume\":\"61\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214001960\",\"month\":\"11\",\"id\":\"d406037b-5ccb-3e43-a5f1-b36a6c7c77d5\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.\",\"bibtype\":\"article\",\"author\":\"Jolma, A. and Lehikoinen, A. and Helle, I. and Venesjärvi, R.\",\"doi\":\"10.1016/j.envsoft.2014.06.023\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A software system for assessing the spatially distributed ecological risk posed by oil shipping},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Ecology,Geospatial,Maritime accident,Oil spill,Risk assessment},\\n pages = {1-11},\\n volume = {61},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214001960},\\n month = {11},\\n id = {d406037b-5ccb-3e43-a5f1-b36a6c7c77d5},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.},\\n bibtype = {article},\\n author = {Jolma, A. and Lehikoinen, A. and Helle, I. and Venesjärvi, R.},\\n doi = {10.1016/j.envsoft.2014.06.023},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Jolma,  A.\",\"Lehikoinen,  A.\",\"Helle,  I.\",\"Venesjärvi,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214001960\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Ecology\",\"Geospatial\",\"Maritime accident\",\"Oil spill\",\"Risk assessment\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Selecting among five common modelling approaches for integrated environmental assessment and management\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Agent-based model,Bayesian network,Coupled component model,Integrated assessment,Knowledge-based model,System dynamics\",\"pages\":\"159-181\",\"volume\":\"47\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213001151\",\"month\":\"9\",\"id\":\"383ca63b-e6ee-3feb-b63d-fdb7f82b957b\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2014-07-24\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.\",\"bibtype\":\"article\",\"author\":\"Kelly (Letcher), Rebecca A. and Jakeman, Anthony J. and Barreteau, Olivier and Borsuk, Mark E. and ElSawah, Sondoss and Hamilton, Serena H. and Henriksen, Hans Jørgen and Kuikka, Sakari and Maier, Holger R. and Rizzoli, Andrea Emilio and van Delden, Hedwig and Voinov, Alexey A.\",\"doi\":\"10.1016/j.envsoft.2013.05.005\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Selecting among five common modelling approaches for integrated environmental assessment and management},\\n type = {article},\\n year = {2013},\\n keywords = {Agent-based model,Bayesian network,Coupled component model,Integrated assessment,Knowledge-based model,System dynamics},\\n pages = {159-181},\\n volume = {47},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001151},\\n month = {9},\\n id = {383ca63b-e6ee-3feb-b63d-fdb7f82b957b},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2014-07-24},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.},\\n bibtype = {article},\\n author = {Kelly (Letcher), Rebecca A. and Jakeman, Anthony J. and Barreteau, Olivier and Borsuk, Mark E. and ElSawah, Sondoss and Hamilton, Serena H. and Henriksen, Hans Jørgen and Kuikka, Sakari and Maier, Holger R. and Rizzoli, Andrea Emilio and van Delden, Hedwig and Voinov, Alexey A.},\\n doi = {10.1016/j.envsoft.2013.05.005},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Kelly (Letcher),  R., A.\",\"Jakeman,  A., J.\",\"Barreteau,  O.\",\"Borsuk,  M., E.\",\"ElSawah,  S.\",\"Hamilton,  S., H.\",\"Henriksen,  H., J.\",\"Kuikka,  S.\",\"Maier,  H., R.\",\"Rizzoli,  A., E.\",\"van Delden,  H.\",\"Voinov,  A., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213001151\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013\",\"role\":\"author\",\"keyword\":[\"Agent-based model\",\"Bayesian network\",\"Coupled component model\",\"Integrated assessment\",\"Knowledge-based model\",\"System dynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Aquifer overexploitation,Decision support systems,Integrated water management,Object-Oriented Bayesian Networks,Stakeholders' engagement\",\"pages\":\"383-397\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002679\",\"month\":\"4\",\"id\":\"3b9044a5-6c1e-392d-8748-0ccc0a0747f5\",\"created\":\"2015-04-11T19:52:26.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Object-Oriented Bayesian Networks (OOBNs) have been used increasingly over the past few decades in fields as diverse as medicine, transport and aeronautics. In this paper, OOBNs are applied to the domain of integrated water management and used as a Decision Support System (DSS). This pioneering study, set in the Altiplano region of Murcia in Southern Spain, describes a method for the integrated analysis of a complex water system supplied by groundwater from four aquifers. This method is based on the development of a multivariable integrated technique based on Bayes' theorem. After identifying all relevant factors related to water management in the area these were then translated to variables within a Bayesian Network (BN) and the relationships between them investigated. Each network represented one of the four aquifer units. These individual BNs were then linked to form an OOBN which was used to represent the complex real-world situation. In this way a DSS to simulate the entire water system was constructed using a group of conventional Bns, linked to produce an OOBN. The main stakeholders of the region contributed to network design and construction throughout the entire process. The paper shows how this type of DSS can be used to evaluate the impacts of a range of management strategies that are available to local planners.\",\"bibtype\":\"article\",\"author\":\"Molina, J.L. and Bromley, J. and García-Aróstegui, J.L. and Sullivan, C. and Benavente, J.\",\"doi\":\"10.1016/j.envsoft.2009.10.007\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks},\\n type = {article},\\n year = {2010},\\n keywords = {Aquifer overexploitation,Decision support systems,Integrated water management,Object-Oriented Bayesian Networks,Stakeholders' engagement},\\n pages = {383-397},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002679},\\n month = {4},\\n id = {3b9044a5-6c1e-392d-8748-0ccc0a0747f5},\\n created = {2015-04-11T19:52:26.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Object-Oriented Bayesian Networks (OOBNs) have been used increasingly over the past few decades in fields as diverse as medicine, transport and aeronautics. In this paper, OOBNs are applied to the domain of integrated water management and used as a Decision Support System (DSS). This pioneering study, set in the Altiplano region of Murcia in Southern Spain, describes a method for the integrated analysis of a complex water system supplied by groundwater from four aquifers. This method is based on the development of a multivariable integrated technique based on Bayes' theorem. After identifying all relevant factors related to water management in the area these were then translated to variables within a Bayesian Network (BN) and the relationships between them investigated. Each network represented one of the four aquifer units. These individual BNs were then linked to form an OOBN which was used to represent the complex real-world situation. In this way a DSS to simulate the entire water system was constructed using a group of conventional Bns, linked to produce an OOBN. The main stakeholders of the region contributed to network design and construction throughout the entire process. The paper shows how this type of DSS can be used to evaluate the impacts of a range of management strategies that are available to local planners.},\\n bibtype = {article},\\n author = {Molina, J.L. and Bromley, J. and García-Aróstegui, J.L. and Sullivan, C. and Benavente, J.},\\n doi = {10.1016/j.envsoft.2009.10.007},\\n journal = {Environmental Modelling & Software},\\n number = {4}\\n}\",\"author_short\":[\"Molina,  J.\",\"Bromley,  J.\",\"García-Aróstegui,  J.\",\"Sullivan,  C.\",\"Benavente,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815209002679\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010\",\"role\":\"author\",\"keyword\":[\"Aquifer overexploitation\",\"Decision support systems\",\"Integrated water management\",\"Object-Oriented Bayesian Networks\",\"Stakeholders' engagement\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian networks,Discretization,Environmental modelling,Feature subset selection,Missing imputation,Multi-dimensional classification,Recruitment forecasting,Supervised classification\",\"pages\":\"245-254\",\"volume\":\"40\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002472\",\"month\":\"2\",\"id\":\"26edd41d-4cf1-369a-876f-85ee33da467a\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs.\",\"bibtype\":\"article\",\"author\":\"Fernandes, Jose A. and Lozano, Jose A. and Inza, Iñaki and Irigoien, Xabier and Pérez, Aritz and Rodríguez, Juan D.\",\"doi\":\"10.1016/j.envsoft.2012.10.001\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian networks,Discretization,Environmental modelling,Feature subset selection,Missing imputation,Multi-dimensional classification,Recruitment forecasting,Supervised classification},\\n pages = {245-254},\\n volume = {40},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002472},\\n month = {2},\\n id = {26edd41d-4cf1-369a-876f-85ee33da467a},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs.},\\n bibtype = {article},\\n author = {Fernandes, Jose A. and Lozano, Jose A. and Inza, Iñaki and Irigoien, Xabier and Pérez, Aritz and Rodríguez, Juan D.},\\n doi = {10.1016/j.envsoft.2012.10.001},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Fernandes,  J., A.\",\"Lozano,  J., A.\",\"Inza,  I.\",\"Irigoien,  X.\",\"Pérez,  A.\",\"Rodríguez,  J., D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002472\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Discretization\",\"Environmental modelling\",\"Feature subset selection\",\"Missing imputation\",\"Multi-dimensional classification\",\"Recruitment forecasting\",\"Supervised classification\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Public participation modelling using Bayesian networks in management of groundwater contamination\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Active involvement,Bayesian networks,EDSS,Groundwater management,MERIT,Negotiation,Pesticides,Planning,Public participatory modelling,Stakeholders\",\"pages\":\"1101-1113\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000491\",\"month\":\"8\",\"id\":\"934f4a5c-91a2-3116-8f90-19f6396acf0b\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Negotiation and active involvement with participation of water managers, experts, stakeholders and representatives of the general public requires decision support tools (Environmental Decision Support Systems; EDSS) that build on transparency and flexibility in order to reach sound action plans and management instruments. One possible EDSS for active involvement of stakeholders is application of Bayesian networks (Bns). The paper gives an example of a case study (The Danish case) where farmers and hydrologists disputed the degree to which pesticide application affected the quality of deep groundwater. Instead of selecting one opinion or another, the decision was made to include both in the Bns. By adopting this approach, it was possible to view the results from either point of view, accepting the reality of the situation, not becoming mired in an insoluble conflict, and in this way laying the foundation for future compromises. The paper explores Bns as a tool for acting on and dealing with management of groundwater protection. Bns allow stakeholders' divergent values, interests and beliefs to be surfaced and negotiated in participatory processes for areas where conventional physically based groundwater models are insufficient due to lack of data, physical understanding, flexibility or lack of integration capability. In this way, the agency will be able to address the institutional arrangement influencing groundwater protection in all its complexity.\",\"bibtype\":\"article\",\"author\":\"Henriksen, Hans Jørgen and Rasmussen, Per and Brandt, Gyrite and von Bülow, Dorthe and Jensen, Finn V.\",\"doi\":\"10.1016/j.envsoft.2006.01.008\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Public participation modelling using Bayesian networks in management of groundwater contamination},\\n type = {article},\\n year = {2007},\\n keywords = {Active involvement,Bayesian networks,EDSS,Groundwater management,MERIT,Negotiation,Pesticides,Planning,Public participatory modelling,Stakeholders},\\n pages = {1101-1113},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000491},\\n month = {8},\\n id = {934f4a5c-91a2-3116-8f90-19f6396acf0b},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Negotiation and active involvement with participation of water managers, experts, stakeholders and representatives of the general public requires decision support tools (Environmental Decision Support Systems; EDSS) that build on transparency and flexibility in order to reach sound action plans and management instruments. One possible EDSS for active involvement of stakeholders is application of Bayesian networks (Bns). The paper gives an example of a case study (The Danish case) where farmers and hydrologists disputed the degree to which pesticide application affected the quality of deep groundwater. Instead of selecting one opinion or another, the decision was made to include both in the Bns. By adopting this approach, it was possible to view the results from either point of view, accepting the reality of the situation, not becoming mired in an insoluble conflict, and in this way laying the foundation for future compromises. The paper explores Bns as a tool for acting on and dealing with management of groundwater protection. Bns allow stakeholders' divergent values, interests and beliefs to be surfaced and negotiated in participatory processes for areas where conventional physically based groundwater models are insufficient due to lack of data, physical understanding, flexibility or lack of integration capability. In this way, the agency will be able to address the institutional arrangement influencing groundwater protection in all its complexity.},\\n bibtype = {article},\\n author = {Henriksen, Hans Jørgen and Rasmussen, Per and Brandt, Gyrite and von Bülow, Dorthe and Jensen, Finn V.},\\n doi = {10.1016/j.envsoft.2006.01.008},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Henriksen,  H., J.\",\"Rasmussen,  P.\",\"Brandt,  G.\",\"von Bülow,  D.\",\"Jensen,  F., V.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000491\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007\",\"role\":\"author\",\"keyword\":[\"Active involvement\",\"Bayesian networks\",\"EDSS\",\"Groundwater management\",\"MERIT\",\"Negotiation\",\"Pesticides\",\"Planning\",\"Public participatory modelling\",\"Stakeholders\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian Networks (BNs),Extended Trading Ratio System (ETRS),Monte Carlo simulation,Real time operating rules,The Zarjub River,Trading discharge permits (TDP)\",\"pages\":\"238-246\",\"volume\":\"24\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815208001126\",\"month\":\"2\",\"id\":\"2807af2e-21af-3c39-9611-97201287e493\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.\",\"bibtype\":\"article\",\"author\":\"Mesbah, Seyyed Morteza and Kerachian, Reza and Nikoo, Mohammad Reza\",\"doi\":\"10.1016/j.envsoft.2008.06.007\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian Networks (BNs),Extended Trading Ratio System (ETRS),Monte Carlo simulation,Real time operating rules,The Zarjub River,Trading discharge permits (TDP)},\\n pages = {238-246},\\n volume = {24},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001126},\\n month = {2},\\n id = {2807af2e-21af-3c39-9611-97201287e493},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.},\\n bibtype = {article},\\n author = {Mesbah, Seyyed Morteza and Kerachian, Reza and Nikoo, Mohammad Reza},\\n doi = {10.1016/j.envsoft.2008.06.007},\\n journal = {Environmental Modelling & Software},\\n number = {2}\\n}\",\"author_short\":[\"Mesbah,  S., M.\",\"Kerachian,  R.\",\"Nikoo,  M., R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815208001126\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks (BNs)\",\"Extended Trading Ratio System (ETRS)\",\"Monte Carlo simulation\",\"Real time operating rules\",\"The Zarjub River\",\"Trading discharge permits (TDP)\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A cross-validation package driving Netica with python\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Bayesian networks,Cross-validation,Netica,Prediction,Probability,Python,Uncertainty\",\"pages\":\"14-23\",\"volume\":\"63\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815214002606\",\"month\":\"1\",\"id\":\"265f368a-fbca-3d7a-a9d5-ec0f95618aaa\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).\",\"bibtype\":\"article\",\"author\":\"Fienen, Michael N. and Plant, Nathaniel G.\",\"doi\":\"10.1016/j.envsoft.2014.09.007\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A cross-validation package driving Netica with python},\\n type = {article},\\n year = {2015},\\n keywords = {Bayesian networks,Cross-validation,Netica,Prediction,Probability,Python,Uncertainty},\\n pages = {14-23},\\n volume = {63},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002606},\\n month = {1},\\n id = {265f368a-fbca-3d7a-a9d5-ec0f95618aaa},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).},\\n bibtype = {article},\\n author = {Fienen, Michael N. and Plant, Nathaniel G.},\\n doi = {10.1016/j.envsoft.2014.09.007},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Fienen,  M., N.\",\"Plant,  N., G.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815214002606\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Cross-validation\",\"Netica\",\"Prediction\",\"Probability\",\"Python\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Coupling real-time control and socio-economic issues in participatory river basin planning\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian Networks,Integrated Water Resource Management,Model integration,Participation,Reservoir operation\",\"pages\":\"1114-1128\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815206001344\",\"month\":\"8\",\"id\":\"580f894f-d644-37c5-ad08-eae4a743a324\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.\",\"bibtype\":\"article\",\"author\":\"Castelletti, A. and Soncini-Sessa, R.\",\"doi\":\"10.1016/j.envsoft.2006.05.018\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Coupling real-time control and socio-economic issues in participatory river basin planning},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian Networks,Integrated Water Resource Management,Model integration,Participation,Reservoir operation},\\n pages = {1114-1128},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001344},\\n month = {8},\\n id = {580f894f-d644-37c5-ad08-eae4a743a324},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.},\\n bibtype = {article},\\n author = {Castelletti, A. and Soncini-Sessa, R.},\\n doi = {10.1016/j.envsoft.2006.05.018},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Castelletti,  A.\",\"Soncini-Sessa,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815206001344\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Integrated Water Resource Management\",\"Model integration\",\"Participation\",\"Reservoir operation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian network,Coastal lakes,Decision support,Environmental management,Integrated assessment,Pathogens,Sustainability\",\"pages\":\"1129-1139\",\"volume\":\"22\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000764\",\"month\":\"8\",\"id\":\"b32c69b2-ca0d-3ddb-93b2-8e9e7fbe8cfe\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.\",\"bibtype\":\"article\",\"author\":\"Ticehurst, Jenifer L. and Newham, Lachlan T.H. and Rissik, David and Letcher, Rebecca A. and Jakeman, Anthony J.\",\"doi\":\"10.1016/j.envsoft.2006.03.003\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian network,Coastal lakes,Decision support,Environmental management,Integrated assessment,Pathogens,Sustainability},\\n pages = {1129-1139},\\n volume = {22},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000764},\\n month = {8},\\n id = {b32c69b2-ca0d-3ddb-93b2-8e9e7fbe8cfe},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.},\\n bibtype = {article},\\n author = {Ticehurst, Jenifer L. and Newham, Lachlan T.H. and Rissik, David and Letcher, Rebecca A. and Jakeman, Anthony J.},\\n doi = {10.1016/j.envsoft.2006.03.003},\\n journal = {Environmental Modelling & Software},\\n number = {8}\\n}\",\"author_short\":[\"Ticehurst,  J., L.\",\"Newham,  L., T.\",\"Rissik,  D.\",\"Letcher,  R., A.\",\"Jakeman,  A., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815206000764\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Coastal lakes\",\"Decision support\",\"Environmental management\",\"Integrated assessment\",\"Pathogens\",\"Sustainability\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessing the likelihood of realizing idealized goals: The case of urban water strategies\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian Networks (BNs),Integrated Urban Water Management,Subjective logic,Water aid\",\"pages\":\"50-60\",\"volume\":\"35\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212000539\",\"month\":\"7\",\"id\":\"db6775b2-898c-33e5-a3c2-14926129a6c5\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space.\",\"bibtype\":\"article\",\"author\":\"Moglia, M. and Perez, P. and Burn, S.\",\"doi\":\"10.1016/j.envsoft.2012.02.005\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Assessing the likelihood of realizing idealized goals: The case of urban water strategies},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian Networks (BNs),Integrated Urban Water Management,Subjective logic,Water aid},\\n pages = {50-60},\\n volume = {35},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000539},\\n month = {7},\\n id = {db6775b2-898c-33e5-a3c2-14926129a6c5},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space.},\\n bibtype = {article},\\n author = {Moglia, M. and Perez, P. and Burn, S.},\\n doi = {10.1016/j.envsoft.2012.02.005},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Moglia,  M.\",\"Perez,  P.\",\"Burn,  S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212000539\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks (BNs)\",\"Integrated Urban Water Management\",\"Subjective logic\",\"Water aid\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Bayesian Networks (BNs),Long-term and short-term operation optimization,Reservoir operating rules,Varying chromosome Length Genetic Algorithm (VLGA)\",\"pages\":\"1420-1432\",\"volume\":\"24\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815209001431\",\"month\":\"12\",\"id\":\"5985fd58-d279-3ed0-8700-3328fc628910\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this paper, a Bayesian Network (BN) is utilized for developing monthly operating rules for a cascade system of reservoirs which is mainly aimed to control floods and supply irrigation needs. BN is trained and verified using the results of a reservoir operation optimization model, which optimizes monthly releases from cascade reservoirs. The inputs of the BN are monthly inflows, reservoir storages at the beginning of the month, and downstream water demands. The trained BN provides the probability distribution functions of reservoirs' releases for each set of input data. The long-term optimization model in monthly scale is formulated to minimize the expected flood and agricultural water deficit damages. The optimization model is developed using an extended version of the Varying chromosome Length Genetic Algorithm (VLGA-II). To incorporate reservoir preparedness for controlling the probable floods in each month, damages associated with floods with different return periods have been considered in the optimization model. For this purpose, a short-term optimization model which provides the optimal hourly releases during floods is utilized and linked to a flood damage estimation model. Damages due to deficit in supplying agricultural water demands are also calculated based on the functions of crop yield responses to deficit irrigation. The developed models are applied to the cascade system of the Dez and Bakhtiari Reservoirs in Southwest of Iran. The result of the trained BN is compared with the rules developed using classical and fuzzy linear regressions and it is shown that the total damage obtained by the BN-based operating rules is about 60 percent less than the total damage obtained using the fuzzy and classical regression analyses. The average relative error in estimating optimal releases is also reduced about 30 percent by using the BN-based rules.\",\"bibtype\":\"article\",\"author\":\"Malekmohammadi, Bahram and Kerachian, Reza and Zahraie, Banafsheh\",\"doi\":\"10.1016/j.envsoft.2009.06.008\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks},\\n type = {article},\\n year = {2009},\\n keywords = {Bayesian Networks (BNs),Long-term and short-term operation optimization,Reservoir operating rules,Varying chromosome Length Genetic Algorithm (VLGA)},\\n pages = {1420-1432},\\n volume = {24},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001431},\\n month = {12},\\n id = {5985fd58-d279-3ed0-8700-3328fc628910},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this paper, a Bayesian Network (BN) is utilized for developing monthly operating rules for a cascade system of reservoirs which is mainly aimed to control floods and supply irrigation needs. BN is trained and verified using the results of a reservoir operation optimization model, which optimizes monthly releases from cascade reservoirs. The inputs of the BN are monthly inflows, reservoir storages at the beginning of the month, and downstream water demands. The trained BN provides the probability distribution functions of reservoirs' releases for each set of input data. The long-term optimization model in monthly scale is formulated to minimize the expected flood and agricultural water deficit damages. The optimization model is developed using an extended version of the Varying chromosome Length Genetic Algorithm (VLGA-II). To incorporate reservoir preparedness for controlling the probable floods in each month, damages associated with floods with different return periods have been considered in the optimization model. For this purpose, a short-term optimization model which provides the optimal hourly releases during floods is utilized and linked to a flood damage estimation model. Damages due to deficit in supplying agricultural water demands are also calculated based on the functions of crop yield responses to deficit irrigation. The developed models are applied to the cascade system of the Dez and Bakhtiari Reservoirs in Southwest of Iran. The result of the trained BN is compared with the rules developed using classical and fuzzy linear regressions and it is shown that the total damage obtained by the BN-based operating rules is about 60 percent less than the total damage obtained using the fuzzy and classical regression analyses. The average relative error in estimating optimal releases is also reduced about 30 percent by using the BN-based rules.},\\n bibtype = {article},\\n author = {Malekmohammadi, Bahram and Kerachian, Reza and Zahraie, Banafsheh},\\n doi = {10.1016/j.envsoft.2009.06.008},\\n journal = {Environmental Modelling & Software},\\n number = {12}\\n}\",\"author_short\":[\"Malekmohammadi,  B.\",\"Kerachian,  R.\",\"Zahraie,  B.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815209001431\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks (BNs)\",\"Long-term and short-term operation optimization\",\"Reservoir operating rules\",\"Varying chromosome Length Genetic Algorithm (VLGA)\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Agent based modeling,Bayesian network,China,Human–environment interaction,IAMO-LUC,Land use change,Payments for environmental services,Social influence\",\"pages\":\"15-28\",\"volume\":\"45\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001892\",\"month\":\"7\",\"id\":\"34614a54-fa08-3246-a72b-42712c6676c3\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem services. The model combines agent-based modeling (ABM) with Bayesian belief networks (BBNs) and opinion dynamics models (ODM). The model endows agents with the ability to make land-use decisions at the household and plot levels. The decision-making process is captured with the BBNs that were constructed and calibrated with both qualitative and quantitative information, i.e., knowledge gained from group discussions with stakeholders and empirical survey data. To represent interpersonal interactions within social networks, the decision process is further modulated by the opinion dynamics model. The goals of the model are to improve the ability of ABM to emulate land-use decision making and thus provide a better understanding of the potential impacts of payments for ecosystem services on land use and household livelihoods. Our approach provides three important innovations. First, decision making is represented in a causal directed graph. Second, the model provides a natural framework for combining knowledge from experts and stakeholders with quantitative data. Third, the modular architecture and the software implementation can be customized with modest efforts. The model is therefore a flexible, general platform that can be tailored to other studies by mounting the appropriate case-specific “brain” into the agents. The model was calibrated for the Sloping Land Conversion Program (SLCP) in Yunnan, China using data from participatory mapping, focus group interviews, and a survey of 509 farm households in 17 villages.\",\"bibtype\":\"article\",\"author\":\"Sun, Zhanli and Müller, Daniel\",\"doi\":\"10.1016/j.envsoft.2012.06.007\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models},\\n type = {article},\\n year = {2013},\\n keywords = {Agent based modeling,Bayesian network,China,Human–environment interaction,IAMO-LUC,Land use change,Payments for environmental services,Social influence},\\n pages = {15-28},\\n volume = {45},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001892},\\n month = {7},\\n id = {34614a54-fa08-3246-a72b-42712c6676c3},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem services. The model combines agent-based modeling (ABM) with Bayesian belief networks (BBNs) and opinion dynamics models (ODM). The model endows agents with the ability to make land-use decisions at the household and plot levels. The decision-making process is captured with the BBNs that were constructed and calibrated with both qualitative and quantitative information, i.e., knowledge gained from group discussions with stakeholders and empirical survey data. To represent interpersonal interactions within social networks, the decision process is further modulated by the opinion dynamics model. The goals of the model are to improve the ability of ABM to emulate land-use decision making and thus provide a better understanding of the potential impacts of payments for ecosystem services on land use and household livelihoods. Our approach provides three important innovations. First, decision making is represented in a causal directed graph. Second, the model provides a natural framework for combining knowledge from experts and stakeholders with quantitative data. Third, the modular architecture and the software implementation can be customized with modest efforts. The model is therefore a flexible, general platform that can be tailored to other studies by mounting the appropriate case-specific “brain” into the agents. The model was calibrated for the Sloping Land Conversion Program (SLCP) in Yunnan, China using data from participatory mapping, focus group interviews, and a survey of 509 farm households in 17 villages.},\\n bibtype = {article},\\n author = {Sun, Zhanli and Müller, Daniel},\\n doi = {10.1016/j.envsoft.2012.06.007},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Sun,  Z.\",\"Müller,  D.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001892\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013\",\"role\":\"author\",\"keyword\":[\"Agent based modeling\",\"Bayesian network\",\"China\",\"Human–environment interaction\",\"IAMO-LUC\",\"Land use change\",\"Payments for environmental services\",\"Social influence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Hybrid Bayesian network classifiers: Application to species distribution models\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Classification,Conservation planning,Hybrid Bayesian networks,Mixtures of truncated exponentials\",\"pages\":\"1630-1639\",\"volume\":\"25\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815210001222\",\"month\":\"12\",\"id\":\"d0abd407-543b-3e72-a742-dc64d2f0e3ec\",\"created\":\"2015-04-11T19:52:27.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks are one of the most powerful tools in the design of expert systems located in an uncertainty framework. However, normally their application is determined by the discretization of the continuous variables. In this paper the naïve Bayes (NB) and tree augmented naïve Bayes (TAN) models are developed. They are based on Mixtures of Truncated Exponentials (MTE) designed to deal with discrete and continuous variables in the same network simultaneously without any restriction. The aim is to characterize the habitat of the spur-thighed tortoise (Testudo graeca graeca), using several continuous environmental variables, and one discrete (binary) variable representing the presence or absence of the tortoise. These models are compared with the full discrete models and the results show a better classification rate for the continuous one. Therefore, the application of continuous models instead of discrete ones avoids loss of statistical information due to the discretization. Moreover, the results of the TAN continuous model show a more spatially accurate distribution of the tortoise. The species is located in the Doñana Natural Park, and in semiarid habitats. The proposed continuous models based on MTEs are valid for the study of species predictive distribution modelling.\",\"bibtype\":\"article\",\"author\":\"Aguilera, P.A. and Fernández, A. and Reche, F. and Rumí, R.\",\"doi\":\"10.1016/j.envsoft.2010.04.016\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Hybrid Bayesian network classifiers: Application to species distribution models},\\n type = {article},\\n year = {2010},\\n keywords = {Classification,Conservation planning,Hybrid Bayesian networks,Mixtures of truncated exponentials},\\n pages = {1630-1639},\\n volume = {25},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210001222},\\n month = {12},\\n id = {d0abd407-543b-3e72-a742-dc64d2f0e3ec},\\n created = {2015-04-11T19:52:27.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks are one of the most powerful tools in the design of expert systems located in an uncertainty framework. However, normally their application is determined by the discretization of the continuous variables. In this paper the naïve Bayes (NB) and tree augmented naïve Bayes (TAN) models are developed. They are based on Mixtures of Truncated Exponentials (MTE) designed to deal with discrete and continuous variables in the same network simultaneously without any restriction. The aim is to characterize the habitat of the spur-thighed tortoise (Testudo graeca graeca), using several continuous environmental variables, and one discrete (binary) variable representing the presence or absence of the tortoise. These models are compared with the full discrete models and the results show a better classification rate for the continuous one. Therefore, the application of continuous models instead of discrete ones avoids loss of statistical information due to the discretization. Moreover, the results of the TAN continuous model show a more spatially accurate distribution of the tortoise. The species is located in the Doñana Natural Park, and in semiarid habitats. The proposed continuous models based on MTEs are valid for the study of species predictive distribution modelling.},\\n bibtype = {article},\\n author = {Aguilera, P.A. and Fernández, A. and Reche, F. and Rumí, R.},\\n doi = {10.1016/j.envsoft.2010.04.016},\\n journal = {Environmental Modelling & Software},\\n number = {12}\\n}\",\"author_short\":[\"Aguilera,  P.\",\"Fernández,  A.\",\"Reche,  F.\",\"Rumí,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815210001222\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010\",\"role\":\"author\",\"keyword\":[\"Classification\",\"Conservation planning\",\"Hybrid Bayesian networks\",\"Mixtures of truncated exponentials\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics\",\"type\":\"article\",\"year\":\"2011\",\"pages\":\"163-172\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815210002355\",\"month\":\"2\",\"id\":\"b34304ce-36ef-3bbc-9b08-97f45089a527\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We develop a Bayesian network (BN) model that describes estuarine chlorophyll dynamics in the upper section of the Neuse River Estuary in North Carolina, using automated constraint based structure learning algorithms. We examine the functionality and usefulness of the structure learning algorithms in building model topology with real-time data under different scenarios. Generated BN models are evaluated and a final model is selected. Model results indicate that although the effect of water temperature and river flow on chlorophyll dynamics has remained unchanged following the implementation of the nitrogen Total Maximum Daily Load (TMDL) program; the response of chlorophyll levels to nutrient concentrations has been altered. The results stress the importance of incorporating expert defined constraints and links in conjunction with the automated structure learning algorithms to generate more plausible structures and minimize the sensitivity of the learning algorithms. This hybrid approach towards structure learning allows for the incorporation of existing knowledge while limiting the scope of the learning algorithms to defining the links between environmental variables for which the expert has little or no information.\",\"bibtype\":\"article\",\"author\":\"\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics},\\n type = {article},\\n year = {2011},\\n pages = {163-172},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210002355},\\n month = {2},\\n id = {b34304ce-36ef-3bbc-9b08-97f45089a527},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We develop a Bayesian network (BN) model that describes estuarine chlorophyll dynamics in the upper section of the Neuse River Estuary in North Carolina, using automated constraint based structure learning algorithms. We examine the functionality and usefulness of the structure learning algorithms in building model topology with real-time data under different scenarios. Generated BN models are evaluated and a final model is selected. Model results indicate that although the effect of water temperature and river flow on chlorophyll dynamics has remained unchanged following the implementation of the nitrogen Total Maximum Daily Load (TMDL) program; the response of chlorophyll levels to nutrient concentrations has been altered. The results stress the importance of incorporating expert defined constraints and links in conjunction with the automated structure learning algorithms to generate more plausible structures and minimize the sensitivity of the learning algorithms. This hybrid approach towards structure learning allows for the incorporation of existing knowledge while limiting the scope of the learning algorithms to defining the links between environmental variables for which the expert has little or no information.},\\n bibtype = {article},\\n author = {},\\n journal = {Environmental Modelling & Software},\\n number = {2}\\n}\",\"author_short\":[],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815210002355\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011\",\"role\":\"\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"BN,Bayesian network,CFU,DAG,Directed Acyclic Graph,FIB,Health risk assessment,MC,MCMC,MPN,MPRM,Markov chain Monte Carlo,Microbial risk,Modelling,Monte Carlo,QMRA,Uncertainty,colony-forming unit,faecal indicator bacteria,modular process risk model,most probable number,quantitative microbial risk assessment\",\"pages\":\"8-18\",\"volume\":\"80\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0160412015000719\",\"month\":\"3\",\"day\":\"28\",\"id\":\"f22a6dfb-58ab-3357-8b28-4075c62627b0\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"BACKGROUND: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.\\n\\nOBJECTIVES: This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.\\n\\nMETHODS: A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.\\n\\nDISCUSSION: The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.\\n\\nCONCLUSION: The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.\",\"bibtype\":\"article\",\"author\":\"Beaudequin, Denise and Harden, Fiona and Roiko, Anne and Stratton, Helen and Lemckert, Charles and Mengersen, Kerrie\",\"doi\":\"10.1016/j.envint.2015.03.013\",\"journal\":\"Environment international\",\"bibtex\":\"@article{\\n title = {Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.},\\n type = {article},\\n year = {2015},\\n keywords = {BN,Bayesian network,CFU,DAG,Directed Acyclic Graph,FIB,Health risk assessment,MC,MCMC,MPN,MPRM,Markov chain Monte Carlo,Microbial risk,Modelling,Monte Carlo,QMRA,Uncertainty,colony-forming unit,faecal indicator bacteria,modular process risk model,most probable number,quantitative microbial risk assessment},\\n pages = {8-18},\\n volume = {80},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0160412015000719},\\n month = {3},\\n day = {28},\\n id = {f22a6dfb-58ab-3357-8b28-4075c62627b0},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {BACKGROUND: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.\\n\\nOBJECTIVES: This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.\\n\\nMETHODS: A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.\\n\\nDISCUSSION: The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.\\n\\nCONCLUSION: The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.},\\n bibtype = {article},\\n author = {Beaudequin, Denise and Harden, Fiona and Roiko, Anne and Stratton, Helen and Lemckert, Charles and Mengersen, Kerrie},\\n doi = {10.1016/j.envint.2015.03.013},\\n journal = {Environment international}\\n}\",\"author_short\":[\"Beaudequin,  D.\",\"Harden,  F.\",\"Roiko,  A.\",\"Stratton,  H.\",\"Lemckert,  C.\",\"Mengersen,  K.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0160412015000719\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015\",\"role\":\"author\",\"keyword\":[\"BN\",\"Bayesian network\",\"CFU\",\"DAG\",\"Directed Acyclic Graph\",\"FIB\",\"Health risk assessment\",\"MC\",\"MCMC\",\"MPN\",\"MPRM\",\"Markov chain Monte Carlo\",\"Microbial risk\",\"Modelling\",\"Monte Carlo\",\"QMRA\",\"Uncertainty\",\"colony-forming unit\",\"faecal indicator bacteria\",\"modular process risk model\",\"most probable number\",\"quantitative microbial risk assessment\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian networks,Crop model,Economic model,Integrated assessment modelling,Participatory modelling,Water management\",\"pages\":\"144-157\",\"volume\":\"50\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213001989\",\"month\":\"12\",\"id\":\"1a722ac0-453f-34ff-8a7c-98fa9198e16f\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.\",\"bibtype\":\"article\",\"author\":\"Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John\",\"doi\":\"10.1016/j.envsoft.2013.09.007\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian networks,Crop model,Economic model,Integrated assessment modelling,Participatory modelling,Water management},\\n pages = {144-157},\\n volume = {50},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001989},\\n month = {12},\\n id = {1a722ac0-453f-34ff-8a7c-98fa9198e16f},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.},\\n bibtype = {article},\\n author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},\\n doi = {10.1016/j.envsoft.2013.09.007},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Carmona,  G.\",\"Varela-Ortega,  C.\",\"Bromley,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213001989\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Crop model\",\"Economic model\",\"Integrated assessment modelling\",\"Participatory modelling\",\"Water management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian Networks,Environmental factors,GHG emissions\",\"pages\":\"132-148\",\"volume\":\"35\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212000643\",\"month\":\"7\",\"id\":\"822361c4-6f80-3309-bbdc-c61ee09777aa\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm's capital income.\",\"bibtype\":\"article\",\"author\":\"Pérez-Miñana, E. and Krause, P.J. and Thornton, J.\",\"doi\":\"10.1016/j.envsoft.2012.02.016\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian Networks,Environmental factors,GHG emissions},\\n pages = {132-148},\\n volume = {35},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000643},\\n month = {7},\\n id = {822361c4-6f80-3309-bbdc-c61ee09777aa},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm's capital income.},\\n bibtype = {article},\\n author = {Pérez-Miñana, E. and Krause, P.J. and Thornton, J.},\\n doi = {10.1016/j.envsoft.2012.02.016},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Pérez-Miñana,  E.\",\"Krause,  P.\",\"Thornton,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212000643\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Environmental factors\",\"GHG emissions\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"BN,BUIZ,Bayesian Network,Bushland Urban Interface Zone,Fire management,Interface,PB,Prescribed Burning,Prescribed fire\",\"pages\":\"166-175\",\"volume\":\"52\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815213002326\",\"month\":\"2\",\"id\":\"5c2294fe-7c00-3d21-b487-245ae333d282\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Wildfires can result in significant economic and social losses. Prescribed fire is commonly applied to reduce fuel loads and thereby decrease future fire risk to life and property. Fuel treatments can occur in the landscape or adjacent to houses. Location of the prescribed burns can significantly alter the risk of house loss. Furthermore the cost of treating fuels in the landscape is far cheaper than treating fuels adjacent to the houses. Here we develop a Bayesian Network to examine the relative reduction in risk that can be achieved by prescribed burning in the landscape compared with a 500 m interface zone adjacent to houses. We then compare costs of management treatments to determine the most cost-effective method of reducing risk to houses. Burning in the interface zone resulted in the greatest reduction in risk of fires reaching the houses and the intensity of these fires. Fuel treatment in the interface zone allows for a direct transfer of benefits from the fuel treatment. Costs of treating fuels in the interface were significantly higher on a per hectare basis, but the extent of area requiring treatment was considerably lower. Results of this study demonstrate that treatment of fuels at the interface is not only the best means of reducing risk, it is also the most cost-effective.\",\"bibtype\":\"article\",\"author\":\"Penman, T.D. and Bradstock, R.A. and Price, O.F.\",\"doi\":\"10.1016/j.envsoft.2013.09.030\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia},\\n type = {article},\\n year = {2014},\\n keywords = {BN,BUIZ,Bayesian Network,Bushland Urban Interface Zone,Fire management,Interface,PB,Prescribed Burning,Prescribed fire},\\n pages = {166-175},\\n volume = {52},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002326},\\n month = {2},\\n id = {5c2294fe-7c00-3d21-b487-245ae333d282},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Wildfires can result in significant economic and social losses. Prescribed fire is commonly applied to reduce fuel loads and thereby decrease future fire risk to life and property. Fuel treatments can occur in the landscape or adjacent to houses. Location of the prescribed burns can significantly alter the risk of house loss. Furthermore the cost of treating fuels in the landscape is far cheaper than treating fuels adjacent to the houses. Here we develop a Bayesian Network to examine the relative reduction in risk that can be achieved by prescribed burning in the landscape compared with a 500 m interface zone adjacent to houses. We then compare costs of management treatments to determine the most cost-effective method of reducing risk to houses. Burning in the interface zone resulted in the greatest reduction in risk of fires reaching the houses and the intensity of these fires. Fuel treatment in the interface zone allows for a direct transfer of benefits from the fuel treatment. Costs of treating fuels in the interface were significantly higher on a per hectare basis, but the extent of area requiring treatment was considerably lower. Results of this study demonstrate that treatment of fuels at the interface is not only the best means of reducing risk, it is also the most cost-effective.},\\n bibtype = {article},\\n author = {Penman, T.D. and Bradstock, R.A. and Price, O.F.},\\n doi = {10.1016/j.envsoft.2013.09.030},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Penman,  T.\",\"Bradstock,  R.\",\"Price,  O.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815213002326\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014\",\"role\":\"author\",\"keyword\":[\"BN\",\"BUIZ\",\"Bayesian Network\",\"Bushland Urban Interface Zone\",\"Fire management\",\"Interface\",\"PB\",\"Prescribed Burning\",\"Prescribed fire\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network approach to model farmers' crop choice using socio-psychological measurements of expected benefits of ecosystem services\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Analytical Hierarchy Process,Bayesian network,Decision-making support,Ecosystem services,Theory of planned behavior\",\"pages\":\"227-234\",\"volume\":\"57\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S136481521400084X\",\"month\":\"7\",\"id\":\"e61d892b-2877-39a3-90d9-1b0a6970eb6c\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Models of ecosystem management typically measure the benefits of ecosystem services in terms of ecological or biophysical variables, which are influenced by management decisions and biophysical/ecological conditions. This study uses farmers' expected benefits of ecosystem services as input variables to model their decision between planting rice, annual crops or perennial crops. Based on the theory of planned behavior, a Bayesian network is constructed to model crop choice depending on attitudes toward the ecosystem services of biomass production, reduction of soil erosion, and water quality improvement. The relative importance of these decision-making criteria is quantified using the Analytical Hierarchy Process. Results indicate that Bayesian networks can use socio-psychological measurements to model decision-making. Especially as an extension to biophysical or economic models, they can serve as a powerful tool for grasping the more abstract socio-psychological dimensions of benefits of ecosystem services, and how they translate into the decisions of ecosystem managers.\",\"bibtype\":\"article\",\"author\":\"Poppenborg, Patrick and Koellner, Thomas\",\"doi\":\"10.1016/j.envsoft.2014.03.006\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {A Bayesian network approach to model farmers' crop choice using socio-psychological measurements of expected benefits of ecosystem services},\\n type = {article},\\n year = {2014},\\n keywords = {Analytical Hierarchy Process,Bayesian network,Decision-making support,Ecosystem services,Theory of planned behavior},\\n pages = {227-234},\\n volume = {57},\\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521400084X},\\n month = {7},\\n id = {e61d892b-2877-39a3-90d9-1b0a6970eb6c},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Models of ecosystem management typically measure the benefits of ecosystem services in terms of ecological or biophysical variables, which are influenced by management decisions and biophysical/ecological conditions. This study uses farmers' expected benefits of ecosystem services as input variables to model their decision between planting rice, annual crops or perennial crops. Based on the theory of planned behavior, a Bayesian network is constructed to model crop choice depending on attitudes toward the ecosystem services of biomass production, reduction of soil erosion, and water quality improvement. The relative importance of these decision-making criteria is quantified using the Analytical Hierarchy Process. Results indicate that Bayesian networks can use socio-psychological measurements to model decision-making. Especially as an extension to biophysical or economic models, they can serve as a powerful tool for grasping the more abstract socio-psychological dimensions of benefits of ecosystem services, and how they translate into the decisions of ecosystem managers.},\\n bibtype = {article},\\n author = {Poppenborg, Patrick and Koellner, Thomas},\\n doi = {10.1016/j.envsoft.2014.03.006},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Poppenborg,  P.\",\"Koellner,  T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S136481521400084X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014\",\"role\":\"author\",\"keyword\":[\"Analytical Hierarchy Process\",\"Bayesian network\",\"Decision-making support\",\"Ecosystem services\",\"Theory of planned behavior\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"BMP,Bayesian Network,Best Management Practice,Best management practice,Fertiliser,Grazing,Monte-Carlo,P,Phosphorus,TP,Total Phosphorus\",\"pages\":\"1079-1088\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815211000843\",\"month\":\"9\",\"id\":\"39b2c2ec-c120-3402-9509-c0efa9004de8\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. <10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results.\",\"bibtype\":\"article\",\"author\":\"Nash, David and Hannah, Murray\",\"doi\":\"10.1016/j.envsoft.2011.03.009\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices},\\n type = {article},\\n year = {2011},\\n keywords = {BMP,Bayesian Network,Best Management Practice,Best management practice,Fertiliser,Grazing,Monte-Carlo,P,Phosphorus,TP,Total Phosphorus},\\n pages = {1079-1088},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211000843},\\n month = {9},\\n id = {39b2c2ec-c120-3402-9509-c0efa9004de8},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. <10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results.},\\n bibtype = {article},\\n author = {Nash, David and Hannah, Murray},\\n doi = {10.1016/j.envsoft.2011.03.009},\\n journal = {Environmental Modelling & Software},\\n number = {9}\\n}\",\"author_short\":[\"Nash,  D.\",\"Hannah,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815211000843\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011\",\"role\":\"author\",\"keyword\":[\"BMP\",\"Bayesian Network\",\"Best Management Practice\",\"Best management practice\",\"Fertiliser\",\"Grazing\",\"Monte-Carlo\",\"P\",\"Phosphorus\",\"TP\",\"Total Phosphorus\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian networks in environmental modelling\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian networks,Environment,Model implementation,Review,Software\",\"pages\":\"1376-1388\",\"volume\":\"26\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815211001472\",\"month\":\"12\",\"id\":\"5fc3a716-77d9-3535-a52b-c3f36d379eee\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-03-12\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems. The goal of this review is to show how BNs are being used in environmental modelling. We are interested in the application of BNs, from January 1990 to December 2010, in the areas of the ISI Web of Knowledge related to Environmental Sciences. It is noted that only the 4.2% of the papers have been published under this item. The different steps that configure modelling via BNs have been revised: aim of the model, data pre-processing, model learning, validation and software. Our literature review indicates that BNs have barely been used for Environmental Science and their potential is, as yet, largely unexploited.\",\"bibtype\":\"article\",\"author\":\"Aguilera, P.A. and Fernández, A. and Fernández, R. and Rumí, R. and Salmerón, A.\",\"doi\":\"10.1016/j.envsoft.2011.06.004\",\"journal\":\"Environmental Modelling & Software\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Bayesian networks in environmental modelling},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian networks,Environment,Model implementation,Review,Software},\\n pages = {1376-1388},\\n volume = {26},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001472},\\n month = {12},\\n id = {5fc3a716-77d9-3535-a52b-c3f36d379eee},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-03-12},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems. The goal of this review is to show how BNs are being used in environmental modelling. We are interested in the application of BNs, from January 1990 to December 2010, in the areas of the ISI Web of Knowledge related to Environmental Sciences. It is noted that only the 4.2% of the papers have been published under this item. The different steps that configure modelling via BNs have been revised: aim of the model, data pre-processing, model learning, validation and software. Our literature review indicates that BNs have barely been used for Environmental Science and their potential is, as yet, largely unexploited.},\\n bibtype = {article},\\n author = {Aguilera, P.A. and Fernández, A. and Fernández, R. and Rumí, R. and Salmerón, A.},\\n doi = {10.1016/j.envsoft.2011.06.004},\\n journal = {Environmental Modelling & Software},\\n number = {12}\\n}\",\"author_short\":[\"Aguilera,  P.\",\"Fernández,  A.\",\"Fernández,  R.\",\"Rumí,  R.\",\"Salmerón,  A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815211001472\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Environment\",\"Model implementation\",\"Review\",\"Software\"],\"metadata\":{\"authorlinks\":{}},\"html\":\"\"},{\"title\":\"Commentary: IUCN classifications under uncertainty\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian networks,Fuzzy logic,IUCN,Red list,Threatened species,Uncertainty\",\"pages\":\"119-121\",\"volume\":\"38\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001648\",\"month\":\"12\",\"id\":\"5190ac37-462d-3614-8391-0495edf5bb3c\",\"created\":\"2015-04-11T19:52:28.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15–23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data.\",\"bibtype\":\"article\",\"author\":\"Akçakaya, H. Reşit and Ferson, Scott and Burgman, Mark A. and Keith, David A. and Mace, Georgina M. and Todd, Charles R.\",\"doi\":\"10.1016/j.envsoft.2012.05.009\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Commentary: IUCN classifications under uncertainty},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian networks,Fuzzy logic,IUCN,Red list,Threatened species,Uncertainty},\\n pages = {119-121},\\n volume = {38},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001648},\\n month = {12},\\n id = {5190ac37-462d-3614-8391-0495edf5bb3c},\\n created = {2015-04-11T19:52:28.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15–23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data.},\\n bibtype = {article},\\n author = {Akçakaya, H. Reşit and Ferson, Scott and Burgman, Mark A. and Keith, David A. and Mace, Georgina M. and Todd, Charles R.},\\n doi = {10.1016/j.envsoft.2012.05.009},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Akçakaya,  H., R.\",\"Ferson,  S.\",\"Burgman,  M., A.\",\"Keith,  D., A.\",\"Mace,  G., M.\",\"Todd,  C., R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212001648\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Fuzzy logic\",\"IUCN\",\"Red list\",\"Threatened species\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian networks,Cascade correlation,Kalman learning rule,Multi-layer perceptron,Sustainable forest management\",\"pages\":\"190-197\",\"volume\":\"2\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S2210537912000492\",\"month\":\"12\",\"id\":\"26050b06-9c88-35aa-95c6-34e2f10db391\",\"created\":\"2015-04-11T20:33:12.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Financial exploitation of forests comprises an important part of man activity. There are efforts being made to conserve the sustainable exploitation while simultaneously avoiding degradation of the environment. One tool used in these efforts is the modeling of tree features, such as total tree height, sawn-timber tree height, merchantable tree height, and total or sawn-timber tree volume, which yields an estimate of the forest in finance recoverable goods. Sustainable forest management design must be supported by the adjustment of computational techniques. The purpose of this paper is to assess a reliable modeling approach for estimating individual tree heights for the maturity of trees for logging through determining the applicability of different types of neural network models and identifying a neural network procedure for accurate estimation of these variables. These models serve as an alternative to the traditional regression approach. All types of model estimations are evaluated and compared in this paper. Back Propagation Artificial Neural Network (BPANN), Cascade Correlation Artificial Neural Network (CCANN), and Generalized Regression Neural Network (GRNN) models are developed to estimate individual tree heights for the logging of mature trees, such as sawn-timber height and merchantable height. The results reported in this research suggest that the selected BPANN and CCANN models are reliable and demonstrate their adequacy and potential for estimating sawn-timber and merchantable tree height. The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy. Moreover, the NN models were found to be superior to the tested nonlinear regression models.\",\"bibtype\":\"article\",\"author\":\"Diamantopoulou, Maria J.\",\"doi\":\"10.1016/j.suscom.2012.10.002\",\"journal\":\"Sustainable Computing: Informatics and Systems\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian networks,Cascade correlation,Kalman learning rule,Multi-layer perceptron,Sustainable forest management},\\n pages = {190-197},\\n volume = {2},\\n websites = {http://www.sciencedirect.com/science/article/pii/S2210537912000492},\\n month = {12},\\n id = {26050b06-9c88-35aa-95c6-34e2f10db391},\\n created = {2015-04-11T20:33:12.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Financial exploitation of forests comprises an important part of man activity. There are efforts being made to conserve the sustainable exploitation while simultaneously avoiding degradation of the environment. One tool used in these efforts is the modeling of tree features, such as total tree height, sawn-timber tree height, merchantable tree height, and total or sawn-timber tree volume, which yields an estimate of the forest in finance recoverable goods. Sustainable forest management design must be supported by the adjustment of computational techniques. The purpose of this paper is to assess a reliable modeling approach for estimating individual tree heights for the maturity of trees for logging through determining the applicability of different types of neural network models and identifying a neural network procedure for accurate estimation of these variables. These models serve as an alternative to the traditional regression approach. All types of model estimations are evaluated and compared in this paper. Back Propagation Artificial Neural Network (BPANN), Cascade Correlation Artificial Neural Network (CCANN), and Generalized Regression Neural Network (GRNN) models are developed to estimate individual tree heights for the logging of mature trees, such as sawn-timber height and merchantable height. The results reported in this research suggest that the selected BPANN and CCANN models are reliable and demonstrate their adequacy and potential for estimating sawn-timber and merchantable tree height. The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy. Moreover, the NN models were found to be superior to the tested nonlinear regression models.},\\n bibtype = {article},\\n author = {Diamantopoulou, Maria J.},\\n doi = {10.1016/j.suscom.2012.10.002},\\n journal = {Sustainable Computing: Informatics and Systems},\\n number = {4}\\n}\",\"author_short\":[\"Diamantopoulou,  M., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S2210537912000492\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Cascade correlation\",\"Kalman learning rule\",\"Multi-layer perceptron\",\"Sustainable forest management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Integrated Assessment of Scale Impacts of Watershed Intervention\",\"type\":\"book\",\"year\":\"2015\",\"source\":\"Integrated Assessment of Scale Impacts of Watershed Intervention\",\"keywords\":\"Bayesian network,capital strength,integrated modeling,livelihood capitals,resilience\",\"pages\":\"287-316\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/B9780128000670000098\",\"publisher\":\"Elsevier\",\"id\":\"d58a843e-6613-33cb-9a3f-60fa7c81d68e\",\"created\":\"2015-04-11T20:33:13.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.\",\"bibtype\":\"book\",\"author\":\"Merritt, Wendy and Patch, Brendan and Kumar Rout, Sanjit\",\"doi\":\"10.1016/B978-0-12-800067-0.00009-8\",\"bibtex\":\"@book{\\n title = {Integrated Assessment of Scale Impacts of Watershed Intervention},\\n type = {book},\\n year = {2015},\\n source = {Integrated Assessment of Scale Impacts of Watershed Intervention},\\n keywords = {Bayesian network,capital strength,integrated modeling,livelihood capitals,resilience},\\n pages = {287-316},\\n websites = {http://www.sciencedirect.com/science/article/pii/B9780128000670000098},\\n publisher = {Elsevier},\\n id = {d58a843e-6613-33cb-9a3f-60fa7c81d68e},\\n created = {2015-04-11T20:33:13.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.},\\n bibtype = {book},\\n author = {Merritt, Wendy and Patch, Brendan and Kumar Rout, Sanjit},\\n doi = {10.1016/B978-0-12-800067-0.00009-8}\\n}\",\"author_short\":[\"Merritt,  W.\",\"Patch,  B.\",\"Kumar Rout,  S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/B9780128000670000098\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"capital strength\",\"integrated modeling\",\"livelihood capitals\",\"resilience\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A mobility constraint model to infer sensor behaviour in forest fire risk monitoring\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian networks,Forest fire risk monitoring,Mobile wireless sensor network,Mobility constraints,Sensor behaviour,Spatial coverage\",\"pages\":\"81-95\",\"volume\":\"36\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0198971511000676\",\"month\":\"1\",\"id\":\"d61193c0-c196-318b-ba47-9e2d44e37b7d\",\"created\":\"2015-04-11T22:23:05.000Z\",\"accessed\":\"2015-03-06\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.\",\"bibtype\":\"article\",\"author\":\"Ballari, Daniela and Wachowicz, Monica and Bregt, Arnold K. and Manso-Callejo, Miguel\",\"doi\":\"10.1016/j.compenvurbsys.2011.06.004\",\"journal\":\"Computers, Environment and Urban Systems\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A mobility constraint model to infer sensor behaviour in forest fire risk monitoring},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian networks,Forest fire risk monitoring,Mobile wireless sensor network,Mobility constraints,Sensor behaviour,Spatial coverage},\\n pages = {81-95},\\n volume = {36},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971511000676},\\n month = {1},\\n id = {d61193c0-c196-318b-ba47-9e2d44e37b7d},\\n created = {2015-04-11T22:23:05.000Z},\\n accessed = {2015-03-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.},\\n bibtype = {article},\\n author = {Ballari, Daniela and Wachowicz, Monica and Bregt, Arnold K. and Manso-Callejo, Miguel},\\n doi = {10.1016/j.compenvurbsys.2011.06.004},\\n journal = {Computers, Environment and Urban Systems},\\n number = {1}\\n}\",\"author_short\":[\"Ballari,  D.\",\"Wachowicz,  M.\",\"Bregt,  A., K.\",\"Manso-Callejo,  M.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0198971511000676\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Forest fire risk monitoring\",\"Mobile wireless sensor network\",\"Mobility constraints\",\"Sensor behaviour\",\"Spatial coverage\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling uncertainty in agricultural image analysis\",\"type\":\"article\",\"year\":\"1997\",\"keywords\":\"Algorithm fusion,Bayesian networks,Image analysis,Uncertainty\",\"pages\":\"295-305\",\"volume\":\"17\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0168169997013227\",\"month\":\"6\",\"id\":\"112c3213-8659-3cee-b728-b0bb21b9bb65\",\"created\":\"2015-04-12T17:48:22.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"No absolute certainty can be given for information derived for images. In most cases image analysis uses single algorithms, or multiple single algorithms' results which are combined in an ad hoc manner, to derive certain information (e.g. edges and textures) to segment images into various regions of interest. However, more robust methods of data fusion can be developed which are based on mathematical foundations of probability theory. One such method combines results from single algorithms using a Bayesian network. This should improve the confidence in the derived image segmentation and gives a direct measure of the probability of each region to be classified correctly. Specific agricultural examples using a Bayesian data fusion approach are given.\",\"bibtype\":\"article\",\"author\":\"Onyango, Christine M. and Marchant, John A. and Zwiggelaar, Reyer\",\"doi\":\"10.1016/S0168-1699(97)01322-7\",\"journal\":\"Computers and Electronics in Agriculture\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Modelling uncertainty in agricultural image analysis},\\n type = {article},\\n year = {1997},\\n keywords = {Algorithm fusion,Bayesian networks,Image analysis,Uncertainty},\\n pages = {295-305},\\n volume = {17},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0168169997013227},\\n month = {6},\\n id = {112c3213-8659-3cee-b728-b0bb21b9bb65},\\n created = {2015-04-12T17:48:22.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {No absolute certainty can be given for information derived for images. In most cases image analysis uses single algorithms, or multiple single algorithms' results which are combined in an ad hoc manner, to derive certain information (e.g. edges and textures) to segment images into various regions of interest. However, more robust methods of data fusion can be developed which are based on mathematical foundations of probability theory. One such method combines results from single algorithms using a Bayesian network. This should improve the confidence in the derived image segmentation and gives a direct measure of the probability of each region to be classified correctly. Specific agricultural examples using a Bayesian data fusion approach are given.},\\n bibtype = {article},\\n author = {Onyango, Christine M. and Marchant, John A. and Zwiggelaar, Reyer},\\n doi = {10.1016/S0168-1699(97)01322-7},\\n journal = {Computers and Electronics in Agriculture},\\n number = {3}\\n}\",\"author_short\":[\"Onyango,  C., M.\",\"Marchant,  J., A.\",\"Zwiggelaar,  R.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0168169997013227\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997\",\"role\":\"author\",\"keyword\":[\"Algorithm fusion\",\"Bayesian networks\",\"Image analysis\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Modelling the benefits of habitat restoration in socio-ecological systems\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian Networks,Decision making,Expert opinion,Restoration,Revegetation,Socio-ecological systems,Species richness,Uncertainty\",\"pages\":\"60-67\",\"volume\":\"169\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0006320713003789\",\"month\":\"1\",\"id\":\"93e42a20-3418-36bf-b03f-8161bb374b3f\",\"created\":\"2015-04-12T18:51:30.000Z\",\"accessed\":\"2015-01-22\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions compared to those that do not take these factors into account. We demonstrate how Bayesian Networks can be used to integrate ecological and social data and expert opinion to model the cost-effectiveness of revegetation activities for restoring biodiversity in agricultural landscapes. We demonstrate our approach with a case-study in grassy woodlands of south-eastern Australia. In our case-study, cost-effectiveness is defined as the improvement in native reptile and beetle species richness achieved per dollar spent on a restoration action. Socio-ecological models predict that weed control, the planting of trees and shrubs, the addition of litter and timber, and the addition of rocks are likely to be the most cost-effective actions for improving reptile and beetle species richness. The cost-effectiveness of restoration actions is lower in remnant and revegetated areas than in cleared areas because of the higher marginal benefits arising from acting in degraded habitats. This result is contingent on having favourable landowner attitudes. Under the best-case landowner demographic scenarios the greatest biodiversity benefits are seen when cleared areas are restored. We find that current restoration investment practices may not be increasing faunal species richness in agricultural landscapes in the most cost-effective way, and that new restoration actions may be necessary. Integrated socio-ecological models support transparent and cost-effective conservation investment decisions. Application of these models highlights the importance of collecting both social and ecological data when attempting to understand and manage socio-ecological systems.\",\"bibtype\":\"article\",\"author\":\"Jellinek, Sacha and Rumpff, Libby and Driscoll, Don A. and Parris, Kirsten M. and Wintle, Brendan A.\",\"doi\":\"10.1016/j.biocon.2013.10.023\",\"journal\":\"Biological Conservation\",\"bibtex\":\"@article{\\n title = {Modelling the benefits of habitat restoration in socio-ecological systems},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian Networks,Decision making,Expert opinion,Restoration,Revegetation,Socio-ecological systems,Species richness,Uncertainty},\\n pages = {60-67},\\n volume = {169},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320713003789},\\n month = {1},\\n id = {93e42a20-3418-36bf-b03f-8161bb374b3f},\\n created = {2015-04-12T18:51:30.000Z},\\n accessed = {2015-01-22},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions compared to those that do not take these factors into account. We demonstrate how Bayesian Networks can be used to integrate ecological and social data and expert opinion to model the cost-effectiveness of revegetation activities for restoring biodiversity in agricultural landscapes. We demonstrate our approach with a case-study in grassy woodlands of south-eastern Australia. In our case-study, cost-effectiveness is defined as the improvement in native reptile and beetle species richness achieved per dollar spent on a restoration action. Socio-ecological models predict that weed control, the planting of trees and shrubs, the addition of litter and timber, and the addition of rocks are likely to be the most cost-effective actions for improving reptile and beetle species richness. The cost-effectiveness of restoration actions is lower in remnant and revegetated areas than in cleared areas because of the higher marginal benefits arising from acting in degraded habitats. This result is contingent on having favourable landowner attitudes. Under the best-case landowner demographic scenarios the greatest biodiversity benefits are seen when cleared areas are restored. We find that current restoration investment practices may not be increasing faunal species richness in agricultural landscapes in the most cost-effective way, and that new restoration actions may be necessary. Integrated socio-ecological models support transparent and cost-effective conservation investment decisions. Application of these models highlights the importance of collecting both social and ecological data when attempting to understand and manage socio-ecological systems.},\\n bibtype = {article},\\n author = {Jellinek, Sacha and Rumpff, Libby and Driscoll, Don A. and Parris, Kirsten M. and Wintle, Brendan A.},\\n doi = {10.1016/j.biocon.2013.10.023},\\n journal = {Biological Conservation}\\n}\",\"author_short\":[\"Jellinek,  S.\",\"Rumpff,  L.\",\"Driscoll,  D., A.\",\"Parris,  K., M.\",\"Wintle,  B., A.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0006320713003789\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian Networks\",\"Decision making\",\"Expert opinion\",\"Restoration\",\"Revegetation\",\"Socio-ecological systems\",\"Species richness\",\"Uncertainty\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening\",\"pages\":\"2565-2575\",\"volume\":\"221\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\",\"month\":\"10\",\"id\":\"4337bf37-9106-3918-a95f-74583cbba3ad\",\"created\":\"2015-04-12T19:14:40.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.\",\"bibtype\":\"article\",\"author\":\"Liedloff, Adam C. and Smith, Carl S.\",\"doi\":\"10.1016/j.ecolmodel.2010.07.022\",\"journal\":\"Ecological Modelling\",\"number\":\"21\",\"bibtex\":\"@article{\\n title = {Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour},\\n type = {article},\\n year = {2010},\\n keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},\\n pages = {2565-2575},\\n volume = {221},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},\\n month = {10},\\n id = {4337bf37-9106-3918-a95f-74583cbba3ad},\\n created = {2015-04-12T19:14:40.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},\\n bibtype = {article},\\n author = {Liedloff, Adam C. and Smith, Carl S.},\\n doi = {10.1016/j.ecolmodel.2010.07.022},\\n journal = {Ecological Modelling},\\n number = {21}\\n}\",\"author_short\":[\"Liedloff,  A., C.\",\"Smith,  C., S.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Fire management\",\"Flames\",\"Grazing management\",\"Probabilistic modelling\",\"Simulation modelling\",\"Tree density\",\"Woody thickening\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement\",\"type\":\"article\",\"year\":\"2001\",\"keywords\":\"Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling\",\"pages\":\"29-42\",\"volume\":\"153\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\",\"month\":\"10\",\"id\":\"2b9e25b4-1810-3167-ae7a-a2d6c0ba496a\",\"created\":\"2015-04-12T19:47:10.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.\",\"bibtype\":\"article\",\"author\":\"Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J\",\"doi\":\"10.1016/S0378-1127(01)00452-2\",\"journal\":\"Forest Ecology and Management\",\"number\":\"1-3\",\"bibtex\":\"@article{\\n title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},\\n type = {article},\\n year = {2001},\\n keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},\\n pages = {29-42},\\n volume = {153},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},\\n month = {10},\\n id = {2b9e25b4-1810-3167-ae7a-a2d6c0ba496a},\\n created = {2015-04-12T19:47:10.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},\\n bibtype = {article},\\n author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},\\n doi = {10.1016/S0378-1127(01)00452-2},\\n journal = {Forest Ecology and Management},\\n number = {1-3}\\n}\",\"author_short\":[\"Marcot,  B., G.\",\"Holthausen,  R., S.\",\"Raphael,  M., G.\",\"Rowland,  M., M.\",\"Wisdom,  M., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\",\"role\":\"author\",\"keyword\":[\"Bayesian belief networks\",\"Bayesian statistics\",\"Columbia River\",\"Fish modeling\",\"Interior Columbia basin\",\"Population viability\",\"Wildlife modeling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks\",\"type\":\"article\",\"year\":\"2007\",\"keywords\":\"Bayesian networks,Endangered species,Hypotheses\",\"pages\":\"37-59\",\"volume\":\"201\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\",\"month\":\"2\",\"id\":\"c6a17f4b-1f28-3b4b-9550-5d882a385c0c\",\"created\":\"2015-04-12T20:17:32.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.\",\"bibtype\":\"article\",\"author\":\"Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.\",\"doi\":\"10.1016/j.ecolmodel.2006.07.032\",\"journal\":\"Ecological Modelling\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},\\n type = {article},\\n year = {2007},\\n keywords = {Bayesian networks,Endangered species,Hypotheses},\\n pages = {37-59},\\n volume = {201},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},\\n month = {2},\\n id = {c6a17f4b-1f28-3b4b-9550-5d882a385c0c},\\n created = {2015-04-12T20:17:32.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},\\n bibtype = {article},\\n author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},\\n doi = {10.1016/j.ecolmodel.2006.07.032},\\n journal = {Ecological Modelling},\\n number = {1}\\n}\",\"author_short\":[\"Pollino,  C., A.\",\"White,  A., K.\",\"Hart,  B., T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Endangered species\",\"Hypotheses\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"State-and-transition modelling for Adaptive Management of native woodlands\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Adaptive Management,Bayesian network,Native vegetation,Process model,Restoration,State-and-transition\",\"pages\":\"1224-1236\",\"volume\":\"144\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0006320710004763\",\"month\":\"4\",\"id\":\"eb2a4f53-5347-397e-90c4-cb09a8a9d2f0\",\"created\":\"2015-04-12T20:17:32.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Adaptive Management (AM) is widely advocated as an approach to dealing with uncertainty in natural resource management as it provides an explicit framework for motivating, designing and interpreting the results of monitoring. One of the major factors impeding implementation is the failure to use appropriate process models; a core element of AM. Process models represent beliefs about the properties and dynamics of an ecological system and ecosystem responses to management. Quantitative models of ecosystem response help resolve ambiguity about the efficacy of management and facilitate iterative updating of knowledge using monitoring data. We report on the use of a state-and-transition model (STM) in the Adaptive Management of native woodland vegetation in south-eastern Australia. The STM is implemented as a Bayesian network, making it simple to communicate and update with new data as they arise. Application of the model is demonstrated using case-study and simulation data. We show how the model may be used to predict the probability of achieving desirable state transitions at restoration sites and how monitoring of those sites can be used to update the model (learn) and adapt (review restoration strategies). After just one monitoring/learning cycle, 7years after the first investments, we found that updated models predict markedly different transition probabilities compared with initial models based on expert opinion. This has strong implications for the apparent cost-efficiency of restoration strategies. The STM approach provides a sound theoretical basis for restoration decisions, while the Bayesian network implementation provides a workable framework for using the STM adaptively.\",\"bibtype\":\"article\",\"author\":\"Rumpff, L. and Duncan, D.H. and Vesk, P.A. and Keith, D.A. and Wintle, B.A.\",\"doi\":\"10.1016/j.biocon.2010.10.026\",\"journal\":\"Biological Conservation\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {State-and-transition modelling for Adaptive Management of native woodlands},\\n type = {article},\\n year = {2011},\\n keywords = {Adaptive Management,Bayesian network,Native vegetation,Process model,Restoration,State-and-transition},\\n pages = {1224-1236},\\n volume = {144},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320710004763},\\n month = {4},\\n id = {eb2a4f53-5347-397e-90c4-cb09a8a9d2f0},\\n created = {2015-04-12T20:17:32.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Adaptive Management (AM) is widely advocated as an approach to dealing with uncertainty in natural resource management as it provides an explicit framework for motivating, designing and interpreting the results of monitoring. One of the major factors impeding implementation is the failure to use appropriate process models; a core element of AM. Process models represent beliefs about the properties and dynamics of an ecological system and ecosystem responses to management. Quantitative models of ecosystem response help resolve ambiguity about the efficacy of management and facilitate iterative updating of knowledge using monitoring data. We report on the use of a state-and-transition model (STM) in the Adaptive Management of native woodland vegetation in south-eastern Australia. The STM is implemented as a Bayesian network, making it simple to communicate and update with new data as they arise. Application of the model is demonstrated using case-study and simulation data. We show how the model may be used to predict the probability of achieving desirable state transitions at restoration sites and how monitoring of those sites can be used to update the model (learn) and adapt (review restoration strategies). After just one monitoring/learning cycle, 7years after the first investments, we found that updated models predict markedly different transition probabilities compared with initial models based on expert opinion. This has strong implications for the apparent cost-efficiency of restoration strategies. The STM approach provides a sound theoretical basis for restoration decisions, while the Bayesian network implementation provides a workable framework for using the STM adaptively.},\\n bibtype = {article},\\n author = {Rumpff, L. and Duncan, D.H. and Vesk, P.A. and Keith, D.A. and Wintle, B.A.},\\n doi = {10.1016/j.biocon.2010.10.026},\\n journal = {Biological Conservation},\\n number = {4}\\n}\",\"author_short\":[\"Rumpff,  L.\",\"Duncan,  D.\",\"Vesk,  P.\",\"Keith,  D.\",\"Wintle,  B.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0006320710004763\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011\",\"role\":\"author\",\"keyword\":[\"Adaptive Management\",\"Bayesian network\",\"Native vegetation\",\"Process model\",\"Restoration\",\"State-and-transition\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A systems approach to unravel complex water management institutions\",\"type\":\"article\",\"year\":\"2008\",\"keywords\":\"Bayesian network,Complex systems,India,Institutional analysis,Integrated management\",\"pages\":\"202-215\",\"volume\":\"5\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\",\"month\":\"9\",\"id\":\"7ae5fbce-67db-300e-8963-c3bf52f746a5\",\"created\":\"2015-04-12T20:17:32.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.\",\"bibtype\":\"article\",\"author\":\"Saravanan, V.S.\",\"doi\":\"10.1016/j.ecocom.2008.04.003\",\"journal\":\"Ecological Complexity\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {A systems approach to unravel complex water management institutions},\\n type = {article},\\n year = {2008},\\n keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},\\n pages = {202-215},\\n volume = {5},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},\\n month = {9},\\n id = {7ae5fbce-67db-300e-8963-c3bf52f746a5},\\n created = {2015-04-12T20:17:32.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},\\n bibtype = {article},\\n author = {Saravanan, V.S.},\\n doi = {10.1016/j.ecocom.2008.04.003},\\n journal = {Ecological Complexity},\\n number = {3}\\n}\",\"author_short\":[\"Saravanan,  V.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Complex systems\",\"India\",\"Institutional analysis\",\"Integrated management\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian networks and the quest for reserve adequacy\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Bayesian network,Interior least tern,Persistence,Piping plover,Reserve adequacy,Reserve selection,Stochastic dynamic programming,Whooping crane\",\"pages\":\"178-186\",\"volume\":\"152\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0006320712001577\",\"month\":\"8\",\"id\":\"62641700-0260-3c6e-ac80-3a1604b60fdd\",\"created\":\"2015-04-12T20:17:32.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. We describe a method that integrates correlates of persistence for multiple species into a single currency – site quality. Site quality is, in turn, an explicit measure of performance used in optimization. We develop a Bayesian network to assess site quality, which assigns an expected value to a property based on criteria arrayed into a causal diagram. We then use stochastic dynamic programming to determine whether an organization should acquire or reject a site placed on the public market. Our framework for assessing sites and making land acquisition decisions represents a compromise between the use of generic spatial design criteria and more intensive computational tools, like spatially-explicit population models. There is certainly a loss of precision by using site quality as a surrogate for more direct measures of persistence. However, we believe this simplification is defensible when sufficient data, expertise, or other resources are lacking.\",\"bibtype\":\"article\",\"author\":\"Schapaugh, Adam W. and Tyre, Andrew J.\",\"doi\":\"10.1016/j.biocon.2012.03.014\",\"journal\":\"Biological Conservation\",\"bibtex\":\"@article{\\n title = {Bayesian networks and the quest for reserve adequacy},\\n type = {article},\\n year = {2012},\\n keywords = {Bayesian network,Interior least tern,Persistence,Piping plover,Reserve adequacy,Reserve selection,Stochastic dynamic programming,Whooping crane},\\n pages = {178-186},\\n volume = {152},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320712001577},\\n month = {8},\\n id = {62641700-0260-3c6e-ac80-3a1604b60fdd},\\n created = {2015-04-12T20:17:32.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. We describe a method that integrates correlates of persistence for multiple species into a single currency – site quality. Site quality is, in turn, an explicit measure of performance used in optimization. We develop a Bayesian network to assess site quality, which assigns an expected value to a property based on criteria arrayed into a causal diagram. We then use stochastic dynamic programming to determine whether an organization should acquire or reject a site placed on the public market. Our framework for assessing sites and making land acquisition decisions represents a compromise between the use of generic spatial design criteria and more intensive computational tools, like spatially-explicit population models. There is certainly a loss of precision by using site quality as a surrogate for more direct measures of persistence. However, we believe this simplification is defensible when sufficient data, expertise, or other resources are lacking.},\\n bibtype = {article},\\n author = {Schapaugh, Adam W. and Tyre, Andrew J.},\\n doi = {10.1016/j.biocon.2012.03.014},\\n journal = {Biological Conservation}\\n}\",\"author_short\":[\"Schapaugh,  A., W.\",\"Tyre,  A., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0006320712001577\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Interior least tern\",\"Persistence\",\"Piping plover\",\"Reserve adequacy\",\"Reserve selection\",\"Stochastic dynamic programming\",\"Whooping crane\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Analysis of topographic and vegetative factors with data mining for landslide verification\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index\",\"pages\":\"669-677\",\"volume\":\"61\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\",\"month\":\"12\",\"id\":\"a79bd6e1-4460-3443-86c7-1e0dc4e4cd8c\",\"created\":\"2015-04-12T20:17:33.000Z\",\"accessed\":\"2015-03-03\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.\",\"bibtype\":\"article\",\"author\":\"Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang\",\"doi\":\"10.1016/j.ecoleng.2013.07.070\",\"journal\":\"Ecological Engineering\",\"bibtex\":\"@article{\\n title = {Analysis of topographic and vegetative factors with data mining for landslide verification},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},\\n pages = {669-677},\\n volume = {61},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},\\n month = {12},\\n id = {a79bd6e1-4460-3443-86c7-1e0dc4e4cd8c},\\n created = {2015-04-12T20:17:33.000Z},\\n accessed = {2015-03-03},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},\\n bibtype = {article},\\n author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},\\n doi = {10.1016/j.ecoleng.2013.07.070},\\n journal = {Ecological Engineering}\\n}\",\"author_short\":[\"Tsai,  F.\",\"Lai,  J.\",\"Chen,  W., W.\",\"Lin,  T.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian Network\",\"Data mining\",\"Decision Tree\",\"Landslide\",\"Slope stability\",\"Vegetation index\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"EBI: An index for delivery of ecosystem service bundles\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs\",\"pages\":\"252-265\",\"volume\":\"37\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\",\"month\":\"2\",\"id\":\"bd5cb454-3186-32c5-8404-381786b4598b\",\"created\":\"2015-04-12T20:17:33.000Z\",\"accessed\":\"2015-02-04\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.\",\"bibtype\":\"article\",\"author\":\"Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.\",\"doi\":\"10.1016/j.ecolind.2013.04.006\",\"journal\":\"Ecological Indicators\",\"bibtex\":\"@article{\\n title = {EBI: An index for delivery of ecosystem service bundles},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},\\n pages = {252-265},\\n volume = {37},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},\\n month = {2},\\n id = {bd5cb454-3186-32c5-8404-381786b4598b},\\n created = {2015-04-12T20:17:33.000Z},\\n accessed = {2015-02-04},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},\\n bibtype = {article},\\n author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},\\n doi = {10.1016/j.ecolind.2013.04.006},\\n journal = {Ecological Indicators}\\n}\",\"author_short\":[\"Van der Biest,  K.\",\"D’Hondt,  R.\",\"Jacobs,  S.\",\"Landuyt,  D.\",\"Staes,  J.\",\"Goethals,  P.\",\"Meire,  P.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Biophysical potential\",\"Climate regulation\",\"Ecosystem services\",\"Land use planning\",\"Provisioning services\",\"Trade-offs\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Combining state and transition models with dynamic Bayesian networks\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics\",\"pages\":\"555-566\",\"volume\":\"222\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\",\"month\":\"2\",\"id\":\"2168ced9-6983-35c2-99f2-f939103c2901\",\"created\":\"2015-04-12T20:17:35.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.\",\"bibtype\":\"article\",\"author\":\"Nicholson, Ann E. and Flores, M. Julia\",\"doi\":\"10.1016/j.ecolmodel.2010.10.010\",\"journal\":\"Ecological Modelling\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Combining state and transition models with dynamic Bayesian networks},\\n type = {article},\\n year = {2011},\\n keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},\\n pages = {555-566},\\n volume = {222},\\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},\\n month = {2},\\n id = {2168ced9-6983-35c2-99f2-f939103c2901},\\n created = {2015-04-12T20:17:35.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},\\n bibtype = {article},\\n author = {Nicholson, Ann E. and Flores, M. Julia},\\n doi = {10.1016/j.ecolmodel.2010.10.010},\\n journal = {Ecological Modelling},\\n number = {3}\\n}\",\"author_short\":[\"Nicholson,  A., E.\",\"Flores,  M., J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\",\"role\":\"author\",\"keyword\":[\"Bayesian networks\",\"Dynamic Bayesian networks\",\"Rangeland management\",\"State-and-transition models\",\"System dynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Prediction analysis of a wastewater treatment system using a Bayesian network\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis\",\"pages\":\"140-150\",\"volume\":\"40\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\",\"id\":\"70c3be7f-ee3a-352b-9820-4656d9bbc625\",\"created\":\"2015-04-22T21:19:07.000Z\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.\",\"bibtype\":\"article\",\"author\":\"Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng\",\"doi\":\"10.1016/j.envsoft.2012.08.011\",\"journal\":\"Environmental Modelling & Software\",\"bibtex\":\"@article{\\n title = {Prediction analysis of a wastewater treatment system using a Bayesian network},\\n type = {article},\\n year = {2013},\\n keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},\\n pages = {140-150},\\n volume = {40},\\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},\\n id = {70c3be7f-ee3a-352b-9820-4656d9bbc625},\\n created = {2015-04-22T21:19:07.000Z},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},\\n bibtype = {article},\\n author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},\\n doi = {10.1016/j.envsoft.2012.08.011},\\n journal = {Environmental Modelling & Software}\\n}\",\"author_short\":[\"Li,  D.\",\"Yang,  H., Z.\",\"Liang,  X., F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Inference\",\"Modified sequencing batch reactor\",\"Prediction analysis\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia.\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"Climate change,Decision support system,Habitat condition,Ramsar wetland\",\"pages\":\"127-138\",\"volume\":\"157\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0301479715300244\",\"month\":\"4\",\"day\":\"17\",\"id\":\"6ac1efdc-afed-397c-96c2-d95ddc982173\",\"created\":\"2015-04-29T18:49:46.000Z\",\"accessed\":\"2015-04-29\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"abstract\":\"Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.\",\"bibtype\":\"article\",\"author\":\"Fu, Baihua and Pollino, Carmel A and Cuddy, Susan M and Andrews, Felix\",\"doi\":\"10.1016/j.jenvman.2015.04.021\",\"journal\":\"Journal of environmental management\",\"bibtex\":\"@article{\\n title = {Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia.},\\n type = {article},\\n year = {2015},\\n keywords = {Climate change,Decision support system,Habitat condition,Ramsar wetland},\\n pages = {127-138},\\n volume = {157},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479715300244},\\n month = {4},\\n day = {17},\\n id = {6ac1efdc-afed-397c-96c2-d95ddc982173},\\n created = {2015-04-29T18:49:46.000Z},\\n accessed = {2015-04-29},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.},\\n bibtype = {article},\\n author = {Fu, Baihua and Pollino, Carmel A and Cuddy, Susan M and Andrews, Felix},\\n doi = {10.1016/j.jenvman.2015.04.021},\\n journal = {Journal of environmental management}\\n}\",\"author_short\":[\"Fu,  B.\",\"Pollino,  C., A.\",\"Cuddy,  S., M.\",\"Andrews,  F.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0301479715300244\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015\",\"role\":\"author\",\"keyword\":[\"Climate change\",\"Decision support system\",\"Habitat condition\",\"Ramsar wetland\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird\",\"pages\":\"38-50\",\"volume\":\"276\",\"websites\":\"https://darchive.mblwhoilibrary.org/handle/1912/7233\",\"month\":\"3\",\"publisher\":\"Elsevier\",\"day\":\"31\",\"id\":\"801a4e65-dfa4-3867-b5eb-f3b6cd49d872\",\"created\":\"2015-05-07T19:12:09.000Z\",\"accessed\":\"2015-04-11\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"language\":\"en_US\",\"private_publication\":false,\"abstract\":\"© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 276 (2014): 38–50, doi:10.1016/j.ecolmodel.2014.01.005.\",\"bibtype\":\"article\",\"author\":\"Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.\",\"doi\":\"10.1016/j.ecolmodel.2014.01.005\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},\\n type = {article},\\n year = {2014},\\n keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},\\n pages = {38-50},\\n volume = {276},\\n websites = {https://darchive.mblwhoilibrary.org/handle/1912/7233},\\n month = {3},\\n publisher = {Elsevier},\\n day = {31},\\n id = {801a4e65-dfa4-3867-b5eb-f3b6cd49d872},\\n created = {2015-05-07T19:12:09.000Z},\\n accessed = {2015-04-11},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n language = {en_US},\\n private_publication = {false},\\n abstract = {© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 276 (2014): 38–50, doi:10.1016/j.ecolmodel.2014.01.005.},\\n bibtype = {article},\\n author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},\\n doi = {10.1016/j.ecolmodel.2014.01.005},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Gieder,  K., D.\",\"Karpanty,  S., M.\",\"Fraser,  J., D.\",\"Catlin,  D., H.\",\"Gutierrez,  B., T.\",\"Plant,  N., G.\",\"Turecek,  A., M.\",\"Robert Thieler,  E.\"],\"urls\":{\"Website\":\"https://darchive.mblwhoilibrary.org/handle/1912/7233\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\",\"role\":\"author\",\"keyword\":[\"Bayesian network\",\"Development\",\"Habitat\",\"Piping plover\",\"Sea-level rise\",\"Shorebird\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"1-11\",\"websites\":\"http://link.springer.com/10.1007/s10666-016-9524-4\",\"month\":\"7\",\"publisher\":\"Springer International Publishing\",\"day\":\"31\",\"id\":\"bb10d0e8-6dd8-39b4-af81-7a48d1a145c7\",\"created\":\"2016-08-06T13:36:25.000Z\",\"accessed\":\"2016-08-06\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-03-14T14:27:45.955Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":\"true\",\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Sujak, Agnieszka and Kusz, Andrzej and Rymarz, Marcin and Kitowski, Ignacy\",\"doi\":\"10.1007/s10666-016-9524-4\",\"journal\":\"Environmental Modeling & Assessment\",\"bibtex\":\"@article{\\n title = {Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species},\\n type = {article},\\n year = {2016},\\n pages = {1-11},\\n websites = {http://link.springer.com/10.1007/s10666-016-9524-4},\\n month = {7},\\n publisher = {Springer International Publishing},\\n day = {31},\\n id = {bb10d0e8-6dd8-39b4-af81-7a48d1a145c7},\\n created = {2016-08-06T13:36:25.000Z},\\n accessed = {2016-08-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-03-14T14:27:45.955Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Sujak, Agnieszka and Kusz, Andrzej and Rymarz, Marcin and Kitowski, Ignacy},\\n doi = {10.1007/s10666-016-9524-4},\\n journal = {Environmental Modeling & Assessment}\\n}\",\"author_short\":[\"Sujak,  A.\",\"Kusz,  A.\",\"Rymarz,  M.\",\"Kitowski,  I.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s10666-016-9524-4\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing a new Bayesian Risk Index for risk evaluation of soil contamination\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"167-177\",\"volume\":\"603\",\"websites\":\"http://www.sciencedirect.com/science/article/pii/S0048969717314729\",\"id\":\"baf70cd6-06b3-3c79-a490-4a4ffdb101b2\",\"created\":\"2017-06-21T13:23:38.837Z\",\"accessed\":\"2017-06-21\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-06-21T13:23:38.837Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs.\",\"bibtype\":\"article\",\"author\":\"Albuquerque, M.T.D. and Gerassis, S. and Sierra, C. and Taboada, J. and Martín, J.E. and Antunes, I.M.H.R. and Gallego, J.R.\",\"doi\":\"10.1016/j.scitotenv.2017.06.068\",\"journal\":\"Science of The Total Environment\",\"bibtex\":\"@article{\\n title = {Developing a new Bayesian Risk Index for risk evaluation of soil contamination},\\n type = {article},\\n year = {2017},\\n pages = {167-177},\\n volume = {603},\\n websites = {http://www.sciencedirect.com/science/article/pii/S0048969717314729},\\n id = {baf70cd6-06b3-3c79-a490-4a4ffdb101b2},\\n created = {2017-06-21T13:23:38.837Z},\\n accessed = {2017-06-21},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-06-21T13:23:38.837Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs.},\\n bibtype = {article},\\n author = {Albuquerque, M.T.D. and Gerassis, S. and Sierra, C. and Taboada, J. and Martín, J.E. and Antunes, I.M.H.R. and Gallego, J.R.},\\n doi = {10.1016/j.scitotenv.2017.06.068},\\n journal = {Science of The Total Environment}\\n}\",\"author_short\":[\"Albuquerque,  M.\",\"Gerassis,  S.\",\"Sierra,  C.\",\"Taboada,  J.\",\"Martín,  J.\",\"Antunes,  I.\",\"Gallego,  J.\"],\"urls\":{\"Website\":\"http://www.sciencedirect.com/science/article/pii/S0048969717314729\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Applications of Bayesian belief networks in water resource management: A systematic review\",\"type\":\"article\",\"year\":\"2016\",\"volume\":\"85\",\"id\":\"a2a41975-a65d-35f4-9b19-8d9fbb2f94b1\",\"created\":\"2017-08-23T21:31:39.274Z\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-08-23T21:31:39.274Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.\",\"bibtype\":\"article\",\"author\":\"Phan, Thuc D. and Smart, James C R and Capon, Samantha J. and Hadwen, Wade L. and Sahin, Oz\",\"doi\":\"10.1016/j.envsoft.2016.08.006\",\"journal\":\"Environmental Modelling and Software\",\"bibtex\":\"@article{\\n title = {Applications of Bayesian belief networks in water resource management: A systematic review},\\n type = {article},\\n year = {2016},\\n volume = {85},\\n id = {a2a41975-a65d-35f4-9b19-8d9fbb2f94b1},\\n created = {2017-08-23T21:31:39.274Z},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-08-23T21:31:39.274Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.},\\n bibtype = {article},\\n author = {Phan, Thuc D. and Smart, James C R and Capon, Samantha J. and Hadwen, Wade L. and Sahin, Oz},\\n doi = {10.1016/j.envsoft.2016.08.006},\\n journal = {Environmental Modelling and Software}\\n}\",\"author_short\":[\"Phan,  T., D.\",\"Smart,  J., C., R.\",\"Capon,  S., J.\",\"Hadwen,  W., L.\",\"Sahin,  O.\"],\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"phan-smart-capon-hadwen-sahin-applicationsofbayesianbeliefnetworksinwaterresourcemanagementasystematicreview-2016\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Bayesian belief network models to analyse and predict ecological water quality in rivers\",\"type\":\"article\",\"year\":\"2015\",\"volume\":\"312\",\"id\":\"30b72578-1e45-327e-9a12-23a0d68e9ace\",\"created\":\"2017-08-23T21:38:25.174Z\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-08-23T21:38:25.174Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Economic growth is often based on the intensification of crop production, energy consumption and urbanization. In many cases, this leads to the degradation of aquatic ecosystems. Modelling water resources and the related identification of key drivers of change are essential to improve and protect water quality in river basins. This study evaluates the potential of Bayesian belief network models to predict the ecological water quality in a typical multifunctional and tropical river basin. Field data, expert knowledge and literature data were used to develop a set of Bayesian belief network models. The developed models were evaluated based on weighted Cohen's Kappa (??<inf>w</inf>), percentage of correctly classified instances (CCI) and spherical payoff. On top, a sensitivity analysis and practical simulation tests of the two most reliable models were performed. Cross-validation based on ??<inf>w</inf> (Model 1: 0.44??0.08; Model 2: 0.44??0.11) and CCI (Model 1: 36.3??2.3; Model 2: 41.6??2.3) indicated that the performance was reliable and stable. Model 1 comprised of input variables main land use, elevation, sediment type, chlorophyll, flow velocity, dissolved oxygen, and chemical oxygen demand; whereas Model 2 did not include dissolved oxygen and chemical oxygen demand. Although the predictive performance of Model 2 was slightly higher than that of Model 1, simulation outcomes of Model 1 were more coherent. Additionally, more management options could be evaluated with Model 1. As the model's ability to simulate management outcomes is of utmost importance in model selection, Model 1 is recommended as a tool to support decision-making in river management. Model predictions and sensitivity analysis indicated that flow velocity is the major variable determining ecological water quality and suggested that construction of additional dams and water abstraction within the basin would have an adverse effect on water quality. Although a case study in a single river basin is presented, the modelling approach can be of general use on any other river basin.\",\"bibtype\":\"article\",\"author\":\"Forio, Marie Anne Eurie and Landuyt, Dries and Bennetsen, Elina and Lock, Koen and Nguyen, Thi Hanh Tien and Ambarita, Minar Naomi Damanik and Musonge, Peace Liz Sasha and Boets, Pieter and Everaert, Gert and Dominguez-Granda, Luis and Goethals, Peter L M\",\"doi\":\"10.1016/j.ecolmodel.2015.05.025\",\"journal\":\"Ecological Modelling\",\"bibtex\":\"@article{\\n title = {Bayesian belief network models to analyse and predict ecological water quality in rivers},\\n type = {article},\\n year = {2015},\\n volume = {312},\\n id = {30b72578-1e45-327e-9a12-23a0d68e9ace},\\n created = {2017-08-23T21:38:25.174Z},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-08-23T21:38:25.174Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Economic growth is often based on the intensification of crop production, energy consumption and urbanization. In many cases, this leads to the degradation of aquatic ecosystems. Modelling water resources and the related identification of key drivers of change are essential to improve and protect water quality in river basins. This study evaluates the potential of Bayesian belief network models to predict the ecological water quality in a typical multifunctional and tropical river basin. Field data, expert knowledge and literature data were used to develop a set of Bayesian belief network models. The developed models were evaluated based on weighted Cohen's Kappa (??<inf>w</inf>), percentage of correctly classified instances (CCI) and spherical payoff. On top, a sensitivity analysis and practical simulation tests of the two most reliable models were performed. Cross-validation based on ??<inf>w</inf> (Model 1: 0.44??0.08; Model 2: 0.44??0.11) and CCI (Model 1: 36.3??2.3; Model 2: 41.6??2.3) indicated that the performance was reliable and stable. Model 1 comprised of input variables main land use, elevation, sediment type, chlorophyll, flow velocity, dissolved oxygen, and chemical oxygen demand; whereas Model 2 did not include dissolved oxygen and chemical oxygen demand. Although the predictive performance of Model 2 was slightly higher than that of Model 1, simulation outcomes of Model 1 were more coherent. Additionally, more management options could be evaluated with Model 1. As the model's ability to simulate management outcomes is of utmost importance in model selection, Model 1 is recommended as a tool to support decision-making in river management. Model predictions and sensitivity analysis indicated that flow velocity is the major variable determining ecological water quality and suggested that construction of additional dams and water abstraction within the basin would have an adverse effect on water quality. Although a case study in a single river basin is presented, the modelling approach can be of general use on any other river basin.},\\n bibtype = {article},\\n author = {Forio, Marie Anne Eurie and Landuyt, Dries and Bennetsen, Elina and Lock, Koen and Nguyen, Thi Hanh Tien and Ambarita, Minar Naomi Damanik and Musonge, Peace Liz Sasha and Boets, Pieter and Everaert, Gert and Dominguez-Granda, Luis and Goethals, Peter L M},\\n doi = {10.1016/j.ecolmodel.2015.05.025},\\n journal = {Ecological Modelling}\\n}\",\"author_short\":[\"Forio,  M., A., E.\",\"Landuyt,  D.\",\"Bennetsen,  E.\",\"Lock,  K.\",\"Nguyen,  T., H., T.\",\"Ambarita,  M., N., D.\",\"Musonge,  P., L., S.\",\"Boets,  P.\",\"Everaert,  G.\",\"Dominguez-Granda,  L.\",\"Goethals,  P., L., M.\"],\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"forio-landuyt-bennetsen-lock-nguyen-ambarita-musonge-boets-etal-bayesianbeliefnetworkmodelstoanalyseandpredictecologicalwaterqualityinrivers-2015\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study\",\"type\":\"article\",\"year\":\"2016\",\"volume\":\"60\",\"id\":\"b2cdd9ec-2d60-358e-92fb-57b1191a95eb\",\"created\":\"2017-08-23T21:40:59.207Z\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2017-08-23T21:40:59.207Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.\",\"bibtype\":\"article\",\"author\":\"Yet, Barbaros and Constantinou, Anthony and Fenton, Norman and Neil, Martin and Luedeling, Eike and Shepherd, Keith\",\"doi\":\"10.1016/j.eswa.2016.05.005\",\"journal\":\"Expert Systems with Applications\",\"bibtex\":\"@article{\\n title = {A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study},\\n type = {article},\\n year = {2016},\\n volume = {60},\\n id = {b2cdd9ec-2d60-358e-92fb-57b1191a95eb},\\n created = {2017-08-23T21:40:59.207Z},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2017-08-23T21:40:59.207Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.},\\n bibtype = {article},\\n author = {Yet, Barbaros and Constantinou, Anthony and Fenton, Norman and Neil, Martin and Luedeling, Eike and Shepherd, Keith},\\n doi = {10.1016/j.eswa.2016.05.005},\\n journal = {Expert Systems with Applications}\\n}\",\"author_short\":[\"Yet,  B.\",\"Constantinou,  A.\",\"Fenton,  N.\",\"Neil,  M.\",\"Luedeling,  E.\",\"Shepherd,  K.\"],\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"yet-constantinou-fenton-neil-luedeling-shepherd-abayesiannetworkframeworkforprojectcostbenefitandriskanalysiswithanagriculturaldevelopmentcasestudy-2016\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Representing causal knowledge in environmental policy interventions: Advantages and opportunities for 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In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.\",\"bibtype\":\"article\",\"author\":\"Boente, C. and Albuquerque, M.T.D. and Gerassis, S. and Rodríguez-Valdés, E. and Gallego, J.R.\",\"doi\":\"10.1016/J.CHEMOSPHERE.2018.11.172\",\"journal\":\"Chemosphere\",\"bibtex\":\"@article{\\n title = {A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve},\\n type = {article},\\n year = {2019},\\n pages = {767-777},\\n volume = {218},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0045653518322677#!},\\n month = {3},\\n publisher = {Pergamon},\\n day = {1},\\n id = {7a8f52b9-c000-37ca-ba69-ae2b997ebac5},\\n created = {2018-12-07T01:00:37.818Z},\\n accessed = {2018-12-06},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2018-12-07T01:00:37.818Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {true},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The impact of mining activities on the environment is vast. In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.},\\n bibtype = {article},\\n author = {Boente, C. and Albuquerque, M.T.D. and Gerassis, S. and Rodríguez-Valdés, E. and Gallego, J.R.},\\n doi = {10.1016/J.CHEMOSPHERE.2018.11.172},\\n journal = {Chemosphere}\\n}\",\"author_short\":[\"Boente,  C.\",\"Albuquerque,  M.\",\"Gerassis,  S.\",\"Rodríguez-Valdés,  E.\",\"Gallego,  J.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0045653518322677#!\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Dynamic Bayesian 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B.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/14a26397-d240-ea77-7647-7b3b0ab26a2e/full_text.pdf.pdf\",\"Website\":\"https://ieeexplore.ieee.org/document/9020145/\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":4,\"html\":\"\"},{\"type\":\"inbook\",\"year\":\"2020\",\"pages\":\"347-370\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-42553-1_14\",\"publisher\":\"Springer, 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L.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"},\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"davis-good-hunter-johnson-mengersen--2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Bayesian networks,Causal modeling,Conceptual site models,Ecological risk assessment,Ecological risk management,Environmental solutions,Qualitative influence diagrams\",\"pages\":\"111478\",\"volume\":\"278\",\"month\":\"1\",\"publisher\":\"Academic Press\",\"day\":\"15\",\"id\":\"6099340e-e5ff-3c41-88fd-2153eec18491\",\"created\":\"2020-11-02T19:20:01.320Z\",\"accessed\":\"2020-11-02\",\"file_attached\":false,\"profile_id\":\"95e10851-cdf3-31de-9f82-1ab629e601b0\",\"group_id\":\"71a29c65-85d2-3809-a3a1-fe4a94dc78d2\",\"last_modified\":\"2020-11-02T19:20:01.423Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.\",\"bibtype\":\"article\",\"author\":\"Carriger, John F. and Parker, Randy A.\",\"doi\":\"10.1016/j.jenvman.2020.111478\",\"journal\":\"Journal of Environmental Management\",\"bibtex\":\"@article{\\n title = {Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support},\\n type = {article},\\n year = {2021},\\n keywords = {Bayesian networks,Causal modeling,Conceptual site models,Ecological risk assessment,Ecological risk management,Environmental solutions,Qualitative influence diagrams},\\n pages = {111478},\\n volume = {278},\\n month = {1},\\n publisher = {Academic Press},\\n day = {15},\\n id = {6099340e-e5ff-3c41-88fd-2153eec18491},\\n created = {2020-11-02T19:20:01.320Z},\\n accessed = {2020-11-02},\\n file_attached = {false},\\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\\n last_modified = {2020-11-02T19:20:01.423Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.},\\n bibtype = {article},\\n author = {Carriger, John F. and Parker, Randy A.},\\n doi = {10.1016/j.jenvman.2020.111478},\\n journal = {Journal of Environmental Management}\\n}\",\"author_short\":[\"Carriger,  J., F.\",\"Parker,  R., A.\"],\"biburl\":\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0\",\"bibbaseid\":\"carriger-parker-conceptualbayesiannetworksforcontaminatedsiteecologicalriskassessmentandremediationsupport-2021\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Bayesian networks\",\"Causal modeling\",\"Conceptual site models\",\"Ecological risk assessment\",\"Ecological risk management\",\"Environmental solutions\",\"Qualitative influence diagrams\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"}],\n      metadata: {\"authorlinks\":{}},\n      ownerID: undefined\n    };\n  </script>\n\n  <script type=\"text/javascript\">\n  var site$;\n  if (typeof $ != 'undefined') {\n    console.log('existing jquery: storing and then restoring');\n    site$ = $;\n    $ = null;\n  }\n  </script>\n\n  <script src=\"https://ajax.googleapis.com/ajax/libs/jquery/2.2.4/jquery.min.js\">\n  </script>\n  <script type=\"text/javascript\">\n  if (site$) {\n    console.log('existing jquery: avoiding conflict and restoring');\n    bb$ = $.noConflict(true);\n    $ = site$;\n  } else {\n    bb$ = $;\n  }\n  </script>\n\n  <script src=\"//bibbase.org/js/bibbase.min.js\"\n          type=\"text/javascript\">\n  </script>\n\n  <script type=\"text/javascript\"\n          src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML\">\n  </script>\n  <script type=\"text/x-mathjax-config\">\n    MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]},\n                        skipTags: [\"body\"],\n                        processClass: \"bibbase_paper\"});\n  </script>\n\n  <style>\n  @media print {\n    .dontprint {\n        display: none !important;\n    }\n\n  .bibbase_group {\n    background-color: #E0E0E0;\n    font-style: italic;\n    font-size: larger;\n    text-shadow: 0px 0px 3px #FFFFFF;\n    border-radius: 4px 4px 4px 4px;\n    -moz-border-radius: 4px 4px 4px 4px;\n    -webkit-border-radius: 4px;\n    padding: 5px 40px 5px;\n    margin-top: 10px;\n    margin-bottom: 5px;\n    cursor: pointer;\n  }\n\n  .bibbase_paper {\n    margin-bottom: 5px;\n  }\n\n  }\n  </style>\n\n  \n  <div style=\"float: right; margin-right: 10px; margin-top: 10px; text-align: right; font-size: 12px\">\n    generated by\n    <a href=\"//bibbase.org\"\n       onclick=\"trackOutboundLink('bibbase', 'logo clicked', window.location.href, '//bibbase.org'); return false;\">\n      <img src=\"//bibbase.org/img/logo.svg\"\n           style=\"vertical-align: middle; margin-left: 3px; height: 16px;\"/\n           alt=\"bibbase.org\"\n           title=\"BibBase – The easiest way to maintain your publications page.\"\n        ></a>\n    \n  </div>\n  \n\n  <div id=\"bibbase_header\" class=\"dontprint\" style=\"\">\n\n    <ul class=\"nav nav-pills\" style=\"margin: 0px;\">\n\n      <li class=\"dropdown\" id=\"groupby_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\">\n          Group by\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li class=\"groupby year\"><a onclick=\"groupby('year')\">\n            Year</a>\n        </li>\n        <li class=\"groupby author\"><a onclick=\"groupby('author_short')\">\n            Author</a>\n        </li>\n        <li class=\"groupby type\"><a onclick=\"groupby('type')\">\n            Type</a>\n        </li>\n        <li class=\"groupby keyword\"><a onclick=\"groupby('keyword')\">\n            Keyword</a>\n        </li>\n        <li class=\"groupby downloads\"><a onclick=\"groupby('downloads')\">\n            Downloads</a>\n        </li>\n      </ul>\n      </li>\n\n\n      <li class=\"dropdown\" id=\"menu_dropdown\">\n      <a class=\"dropdown-toggle\"\n         data-toggle=\"dropdown\"\n         href=\"#\" alt=\"controls\">\n          <i class=\"fa fa-reorder\" alt=\"controls\"></i>\n          <b class=\"caret\"></b>\n      </a>\n      <ul class=\"dropdown-menu\">\n        <li>\n          <a onclick=\"toggleAll()\">\n            <i class=\"fa fa-chevron-down fa-fw\"></i> Expand/Collapse All\n          </a>\n        </li>\n        <li>\n          <a download=\"all.bib\" href=\"data:text/bibtex;base64,@article{
 title = {Modelling land-use decisions under conditions of uncertainty},
 type = {article},
 year = {2007},
 keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},
 pages = {461-476},
 volume = {31},
 websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},
 month = {7},
 id = {436883e2-d0c0-3ff3-9a43-47ea1496df8e},
 created = {2015-04-11T15:16:23.000Z},
 accessed = {2015-03-18},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},
 bibtype = {article},
 author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},
 doi = {10.1016/j.compenvurbsys.2007.02.002},
 journal = {Computers, Environment and Urban Systems},
 number = {4}
}

@article{
 title = {Belief network models of land manager decisions and land use change},
 type = {article},
 year = {2002},
 keywords = {conflict resolution, conservation, decision models},
 pages = {1-23},
 volume = {65},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},
 month = {5},
 id = {644a8604-5091-3090-9bf5-2d5e8e303042},
 created = {2015-04-11T15:16:23.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},
 bibtype = {article},
 author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},
 doi = {10.1006/jema.2001.0507},
 journal = {Journal of Environmental Management},
 number = {1}
}

@article{
 title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},
 pages = {54-66},
 volume = {147},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},
 month = {1},
 id = {305c6eb9-3c9b-3b2d-a33e-c97dffec1133},
 created = {2015-04-11T15:16:23.000Z},
 accessed = {2015-01-27},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},
 bibtype = {article},
 author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},
 doi = {10.1016/j.agwat.2014.07.023},
 journal = {Agricultural Water Management}
}

@article{
 title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},
 pages = {54-66},
 volume = {147},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},
 month = {1},
 id = {99b5d3a4-66ef-3453-83db-36352710606f},
 created = {2015-04-11T15:16:24.000Z},
 accessed = {2015-01-27},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},
 bibtype = {article},
 author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},
 doi = {10.1016/j.agwat.2014.07.023},
 journal = {Agricultural Water Management}
}

@article{
 title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},
 pages = {64-78},
 volume = {299},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},
 month = {3},
 id = {c5616b49-da10-3235-865a-d74393655fca},
 created = {2015-04-11T15:30:36.000Z},
 accessed = {2015-01-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},
 bibtype = {article},
 author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},
 doi = {10.1016/j.ecolmodel.2014.12.004},
 journal = {Ecological Modelling}
}

@article{
 title = {Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach},
 type = {article},
 year = {2009},
 keywords = {Bayesian belief network,Diadema antillarum,Dictyota spp.,Grazing pressure,Macroalgal dynamics,Nutrients,Scaridae},
 pages = {1305-1314},
 volume = {220},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380009001525},
 month = {5},
 id = {7cf595bd-9144-3165-be59-04863302f07c},
 created = {2015-04-11T15:45:45.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.},
 bibtype = {article},
 author = {Renken, Henk and Mumby, Peter J.},
 doi = {10.1016/j.ecolmodel.2009.02.022},
 journal = {Ecological Modelling},
 number = {9-10}
}

@article{
 title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},
 pages = {64-78},
 volume = {299},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},
 month = {3},
 id = {b02b5d31-9b7f-3d35-a559-3c76e87b962e},
 created = {2015-04-11T15:45:45.000Z},
 accessed = {2015-01-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},
 bibtype = {article},
 author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},
 doi = {10.1016/j.ecolmodel.2014.12.004},
 journal = {Ecological Modelling}
}

@article{
 title = {A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland},
 type = {article},
 year = {2010},
 keywords = {Bayesian belief network,Geographic information system,Probabilistic inference,Swaziland,Wildfire},
 pages = {199-208},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002035},
 month = {2},
 id = {777ffc68-b80c-3b09-b39c-50d6de96dc04},
 created = {2015-04-11T15:45:45.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001–2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.},
 bibtype = {article},
 author = {Dlamini, Wisdom M.},
 doi = {10.1016/j.envsoft.2009.08.002},
 journal = {Environmental Modelling & Software},
 number = {2}
}

@article{
 title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},
 type = {article},
 year = {2013},
 keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},
 pages = {113-121},
 volume = {44},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},
 month = {6},
 id = {a54c3232-2de1-345c-9420-c718b2f27607},
 created = {2015-04-11T15:45:45.000Z},
 accessed = {2015-02-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},
 bibtype = {article},
 author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},
 doi = {10.1016/j.envsoft.2012.07.008},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},
 type = {article},
 year = {2013},
 keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},
 pages = {90-103},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},
 month = {8},
 id = {ecee1c33-4441-35b5-b2e5-d008f50d97d0},
 created = {2015-04-11T15:45:45.000Z},
 accessed = {2015-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},
 bibtype = {article},
 author = {Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},
 doi = {10.1016/j.envsoft.2013.03.001},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {A review of Bayesian belief networks in ecosystem service modelling},
 type = {article},
 year = {2013},
 keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},
 pages = {1-11},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},
 month = {8},
 id = {cde4bf8d-fd72-3d55-bba7-f0059de57b6a},
 created = {2015-04-11T15:50:45.000Z},
 accessed = {2015-02-10},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},
 bibtype = {article},
 author = {Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},
 doi = {10.1016/j.envsoft.2013.03.011},
 journal = {Environmental Modelling & Software}
}

@book{
 title = {Encyclopedia of Ecology},
 type = {book},
 year = {2008},
 source = {Encyclopedia of Ecology},
 keywords = {Artificial intelligence,Bayesian networks,Belief networks,Causal analysis,Causality,Graphical models,Hierarchical Bayes,Inference,Influence diagrams,Learning,Prediction,Probability networks},
 pages = {307-317},
 websites = {http://www.sciencedirect.com/science/article/pii/B9780080454054001440},
 publisher = {Elsevier},
 id = {af635c49-de74-3eb9-ae1c-c6a1593ce15f},
 created = {2015-04-11T15:50:45.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {By succinctly and effectively translating causal assertions between variables into patterns of probabilistic dependence, Bayesian networks (BNs) facilitate logical and holistic reasoning under uncertainty in complex systems. Such reasoning is necessary for accurate analysis, synthesis, prediction, diagnosis, and decision making. A definition of BNs is first provided and a simple ecological example is introduced that will be used throughout the remainder of the article to illustrate basic concepts. Methods for constructing BNs are next described, including specification of model structure and conditional probabilities, both deliberately and automatically from case data. This is followed by a description of how BNs can be used for prediction, inference, explanation, intervention, and decision. Finally, some special cases of BNs are presented including hierarchical, dynamic, and integrated models. These show how BNs can be used to integrate across scales, disciplines, and levels of complexity.},
 bibtype = {book},
 author = {Borsuk, M.E.},
 doi = {10.1016/B978-008045405-4.00144-0}
}

@article{
 title = {Modelling land-use decisions under conditions of uncertainty},
 type = {article},
 year = {2007},
 keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},
 pages = {461-476},
 volume = {31},
 websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},
 month = {7},
 id = {60cdd308-554e-3906-bbf0-382586eb071c},
 created = {2015-04-11T17:37:59.000Z},
 accessed = {2015-03-18},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},
 bibtype = {article},
 author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},
 doi = {10.1016/j.compenvurbsys.2007.02.002},
 journal = {Computers, Environment and Urban Systems},
 number = {4}
}

@article{
 title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},
 pages = {54-66},
 volume = {147},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},
 month = {1},
 id = {811f579b-70c3-3d8f-99a4-0247f35ac0f5},
 created = {2015-04-11T17:37:59.000Z},
 accessed = {2015-01-27},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},
 bibtype = {article},
 author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},
 doi = {10.1016/j.agwat.2014.07.023},
 journal = {Agricultural Water Management}
}

@article{
 title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},
 type = {article},
 year = {2015},
 keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},
 pages = {64-78},
 volume = {299},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},
 month = {3},
 id = {5ff020c8-12b9-33e0-b574-0d4c42063017},
 created = {2015-04-11T17:43:54.000Z},
 accessed = {2015-01-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},
 bibtype = {article},
 author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},
 doi = {10.1016/j.ecolmodel.2014.12.004},
 journal = {Ecological Modelling}
}

@article{
 title = {Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis.},
 type = {article},
 year = {2013},
 keywords = {Bayes Theorem,Ecosystem,Empirical Research,Fresh Water,Fresh Water: chemistry,Nitrogen,Nitrogen: analysis,Wetlands},
 pages = {91-9},
 volume = {124},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479713002016},
 month = {7},
 day = {30},
 id = {c5517933-9eb6-37af-a3d4-a2d37a79f7f2},
 created = {2015-04-11T17:43:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Increased nitrogen (N) inputs to freshwater wetlands potentially affect the interaction between nitrous oxide (N2O) emissions and outflow water quality. The purpose of this study is to evaluate the influence of N inputs on N removal, as well as the interaction between N2O emissions and outflow water quality, using a Bayesian Belief Network (BBN). The BBN was developed by linking wetland classification, biogeochemical processes, and environmental factors. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was implemented using 30 wetlands (88% of the case file) and evaluated using a single test file containing 4 wetlands (12% of the case file). The BBN implies it is not average annual total N load entering the wetland, but the N removal efficiency that influences the interactions between N2O emissions and outflow water quality. Even though the network has a very low error rate indicating a high predictive accuracy, additional testing and larger training and testing datasets would increase confidence in the model's ability to provide robust predictions and to reduce the uncertainty resulting from an incomplete dataset and knowledge gaps regarding the interactions between N2O emissions and outflow water quality.},
 bibtype = {article},
 author = {Spence, Porché L and Jordan, Stephen J},
 doi = {10.1016/j.jenvman.2013.03.029},
 journal = {Journal of environmental management}
}

@article{
 title = {Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis},
 type = {article},
 year = {2008},
 keywords = {Bayesian belief network,conditional probability,knowledge,moss greening produce,preference,texture analysis},
 pages = {45-50},
 volume = {1},
 websites = {http://www.sciencedirect.com/science/article/pii/S1881836608800018},
 id = {56b90f2e-e48c-3fe7-b9aa-39d9e2f838fb},
 created = {2015-04-11T17:43:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.},
 bibtype = {article},
 author = {Ushada, Mirwan and Murase, Haruhiko},
 doi = {10.1016/S1881-8366(08)80001-8},
 journal = {Engineering in Agriculture, Environment and Food},
 number = {2}
}

@article{
 title = {Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip},
 type = {article},
 year = {2004},
 keywords = {Bayesian belief networks,Desalination,Gaza Strip,Optimization,Reverse osmosis,Uncertainty},
 pages = {191-201},
 volume = {161},
 websites = {http://www.sciencedirect.com/science/article/pii/S0011916404900549},
 month = {2},
 id = {6bb987ae-3066-32eb-afbb-2564d7beae75},
 created = {2015-04-11T17:43:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In the Gaza Strip, the available freshwater sources are severely polluted and overused. Desalination of seawater through reverse osmosis (RO) has become the most realistic option to meet a rapidly growing water demand. It is estimated that the Gaza Strip will need to develop a seawater desalination capacity of about 120,000 m3/d by the year 2008, and an additional 30,000 m3/d by the year 2016 in order to maintain a fresh water balance in the coastal aquifer and to fulfill the water demand for different uses in a sustainable manner. Cost and reliability of a large RO facility are still subject to much uncertainty. The cost of seawater desalination by RO systems varies with facility size and lifetime, financing conditions, intake type and pre-treatment requirements, power requirements, recovery rate, chemicals cost, spare parts cost, and membrane replacement cost. The permeate salinity is a function of feed water temperature, recovery rate, and permeate flux. The quantity of water produced depends mainly on plant size, recovery rate, and operating load factor. Many of these parameters are subject to a great deal of uncertainty. The objective of this work is to develop a probabilistic model for the simulation of seawater reverse osmosis processes using a Bayesian belief network (BBN) approach. This model represents a new application of probabilistic modeling tools to a large-scale complex system. The model is used to: (1) characterize the different uncertainties involved in the RO process; (2) optimize the RO process reliability and cost; and (3) study how uncertainty in unit capital cost, unit operation and maintenance (O&M) cost, and permeate quality is related to different input variables. The model utilizes information from journal articles, books, expert opinions, and technical reports related to the study area, and can be used to support operators and decision makers in the design of RO systems and formulation of operational policies. The structure of the model is not specific to the Gaza Strip and can be easily populated with data from any large-scale RO plant in any part of the world.},
 bibtype = {article},
 author = {Ghabayen, Said and McKee, Mac and Kemblowski, Mariush},
 doi = {10.1016/S0011-9164(04)90054-9},
 journal = {Desalination},
 number = {2}
}

@article{
 title = {Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin},
 type = {article},
 year = {2001},
 keywords = {Aquatic habitat,Bayesian belief network,Columbia River basin,Fish,Salmon,Trout},
 pages = {43-62},
 volume = {153},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004534},
 month = {10},
 id = {30411cd0-977e-336b-92a0-7fd355045e17},
 created = {2015-04-11T17:55:09.000Z},
 accessed = {2015-03-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Aquatic species throughout the interior Columbia River basin are at risk. Evaluation of the potential effects of federal land management on aquatic ecosystems across this region is an important but challenging task. Issues include the size and complexity of the systems, uncertainty in important processes and existing states, flexibility and consistency in the analytical framework, and an ability to quantify results. We focused on salmonid fishes and their habitats as indicators of conditions in aquatic ecosystems and used Bayesian belief networks as a formal, quantitative framework to address the issues in our evaluation of land management alternatives proposed for the interior Columbia River basin. Because empirical information is limited at the scales relevant to our analysis, an ability to combine both empirical and more subjective information was key to the analysis. The representation of linkages through conditional probabilities made uncertainty explicit. We constructed two general networks. One represented the influence of landscape characteristics and existing and predicted management activities on aquatic habitats. A second represented the influence of habitat, existing biotic conditions, and for two anadromous species, ocean and migratory conditions, on the status of six widely distributed salmonid fishes. In the long term (100 years) all three land management alternatives were expected to produce positive changes in the status and distribution of the salmonids and their habitats. Trends were stronger for habitat than for the status of salmonids because of greater uncertainty in linking the fish and habitat networks and constraints outside spawning and rearing habitat on federal lands in the study area. Trends were stronger for resident salmonids than anadromous forms because of additional effects of the migratory corridor assumed for the latter. Alternative S2, which approached ecosystem restoration more conservatively, generally produced the strongest positive changes, and alternative S3, designed to promote more aggressive restoration, the weakest. Averaged across the basin, differences among the alternatives were small. Differences were greater at finer temporal and spatial scales. In the short term (10 years) alternative S3 was expected to lead to further degradation in some areas. By formalizing our understanding and assumptions in these networks, we provided a framework for exploring differences in the management alternatives that is more quantifiable, spatially explicit, and flexible than previous approaches.},
 bibtype = {article},
 author = {Rieman, Bruce and Peterson, James T and Clayton, James and Howell, Philip and Thurow, Russell and Thompson, William and Lee, Danny},
 doi = {10.1016/S0378-1127(01)00453-4},
 journal = {Forest Ecology and Management},
 number = {1-3}
}

@article{
 title = {The construction of causal networks to estimate coral bleaching intensity},
 type = {article},
 year = {2013},
 keywords = {AGRRA,Atlantic and Gulf Rapid Reef Assessment,BN,BNPC,BSST,Bayesian network,Bayesian networks,Belief Network Power Constructor,CI,CPT,Coral bleaching,Coral reef,DAG,EM,Environmental variability,K490,MEI,MaxSST,PCA,PPT,Remote sensing,SST,SSTAc5d,South Atlantic coral reefs,U,V,best sea surface temperature,conditional independence,conditional probabilities table,diffuse light attenuation coefficient at 490 nm,directed acyclic graph,expectation–maximization,maximum sea surface temperature,mean surface wind fields,meridional wind,multivariate El Niño index,principal component analysis,rain precipitation,sea surface temperature,sea surface temperature accumulated in five days,zonal wind,|W|},
 pages = {157-167},
 volume = {42},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000121},
 month = {4},
 id = {4a097128-e62a-3c7b-ad37-6b51838d86f0},
 created = {2015-04-11T17:55:10.000Z},
 accessed = {2015-02-27},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Current metrics for predicting bleaching episodes, e.g. NOAA's Coral Reef Watch Program, do not seem to apply well to Brazil's marginal reefs located in Bahia state and alternative predictive approaches must be sought for effective long term management. Bleaching occurrences at Abrolhos have been observed since the 1990s but with a much lower frequency/extent than for other reef systems worldwide. We constructed a Bayesian Belief Network (BN) to back-predict the intensity of bleaching events and learn how local and regional scale forcing factors interact to enhance or alleviate coral bleaching specific to Abrolhos. Bleaching intensity data were collected for several reef sites across Bahia state coast (∼12°–20°S; 37°–40°W) during the austral summer 1994–2005 and compared to environmental data: sea surface temperature (SST), diffuse light attenuation coefficient at 490 nm (K490), rain precipitation, wind velocities, and El Niño Southern Oscillation (ENSO) proxies. Conditional independence tests were calculated to produce four specialized BNs, each with specific factors that likely regulate bleaching intensity. All specialized BNs identified that a five-day accumulated SST proxy (SSTAc5d) was the exclusive parent node for coral bleaching producing a total predictive rate of 88% based on SSTAc5d state. When SSTAc5d was simulated as unknown, the Thermal-Eolic Resultant BN kept the total predictive rate of 88%. Our approach has produced initial means to predict beaching intensity at Abrolhos. However, the robustness of the model required for management purposes must be further (and regularly) operationally tested with new in situ and remote sensing data.},
 bibtype = {article},
 author = {Krug, Lilian Anne and Gherardi, Douglas Francisco Marcolino and Stech, José Luís and Leão, Zelinda Margarida Andrade Nery and Kikuchi, Ruy Kenji Papa and Hruschka, Estevam Rafael and Suggett, David John},
 doi = {10.1016/j.envsoft.2013.01.003},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Belief network models of land manager decisions and land use change},
 type = {article},
 year = {2002},
 keywords = {conflict resolution, conservation, decision models},
 pages = {1-23},
 volume = {65},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},
 month = {5},
 id = {b0ff7057-ddd3-325a-b3b4-c0b07cdab630},
 created = {2015-04-11T17:55:11.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},
 bibtype = {article},
 author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},
 doi = {10.1006/jema.2001.0507},
 journal = {Journal of Environmental Management},
 number = {1}
}

@article{
 title = {A belief network approach to optimization and parameter estimation: application to resource and environmental management},
 type = {article},
 year = {1998},
 keywords = {Bayesian methods,Belief networks,Environmental policies,Hybrid models,Optimization,Parameter estimation,Probabilistic models,Resource management,Water quality},
 pages = {135-163},
 volume = {101},
 websites = {http://www.sciencedirect.com/science/article/pii/S0004370298000101},
 month = {5},
 id = {a8d856d9-f8bc-359d-8fb6-63d912a186ee},
 created = {2015-04-11T18:33:33.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {An approach to use Bayesian belief networks in optimization is presented, with an illustration on resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of that model. The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various policy options. Also multiobjective optimization is possible. The approach is illustrated with an example on cost-effective management of river water quality.},
 bibtype = {article},
 author = {Vans, Olli},
 doi = {10.1016/S0004-3702(98)00010-1},
 journal = {Artificial Intelligence},
 number = {1-2}
}

@article{
 title = {Reflections on the use of Bayesian belief networks for adaptive management.},
 type = {article},
 year = {2008},
 keywords = {Bayes Theorem,European Union,Water Supply},
 pages = {1025-36},
 volume = {88},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479707001922},
 month = {9},
 id = {40d1bc21-002a-3bc1-a529-ccbcbef80351},
 created = {2015-04-11T18:33:33.000Z},
 accessed = {2015-03-20},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers' experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.},
 bibtype = {article},
 author = {Henriksen, Hans Jørgen and Barlebo, Heidi Christiansen},
 doi = {10.1016/j.jenvman.2007.05.009},
 journal = {Journal of environmental management},
 number = {4}
}

@article{
 title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},
 type = {article},
 year = {2013},
 keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},
 pages = {90-103},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},
 month = {8},
 id = {aad23f85-469d-3656-8244-34b843ea5b87},
 created = {2015-04-11T18:33:34.000Z},
 accessed = {2015-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},
 bibtype = {article},
 author = {Portoghese, Ivan and D'Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},
 doi = {10.1016/j.envsoft.2013.03.001},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks},
 type = {article},
 year = {2008},
 keywords = {Adaptive management,Bayesian belief network,Decision support,Queensland,Rangeland management,State and transition model},
 pages = {23-34},
 volume = {99},
 websites = {http://www.sciencedirect.com/science/article/pii/S0308521X08000966},
 month = {12},
 id = {60306c81-7a67-3eae-b843-225b6347b7c0},
 created = {2015-04-11T18:33:34.000Z},
 accessed = {2015-04-01},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {State and transition models provide a simple and versatile way of describing vegetation dynamics in rangelands. However, state and transition models are traditionally descriptive, which has limited their practical application to rangeland management decision support. This paper demonstrates an approach to rangeland management decision support that combines a state and transition model with a Bayesian belief network to provide a relatively simple and updatable rangeland dynamics model that can accommodate uncertainty and be used for scenario, diagnostic, and sensitivity analysis. A state and transition model, developed by the authors for subtropical grassland in south-east Queensland, Australia, is used as an example. From the state and transition model, an influence diagram was built to show the possible transitions among states and the factors influencing each transition. The influence diagram was populated with probabilities to produce a predictive model in the form of a Bayesian belief network. The behaviour of the model was tested using scenario and sensitivity analysis, revealing that selective grazing, grazing pressure, and soil nutrition were believed to influence most transitions, while fire frequency and the frequency of good wet seasons were also important in some transitions. Overall, the integration of a state and transition model with a Bayesian belief network provided a useful way to utilise the knowledge embedded in a state and transition model for predictive purposes. Using a Bayesian belief network in the modelling approach allowed uncertainty and variability to be explicitly accommodated in the modelling process, and expert knowledge to be utilised in model development. The methods used also supported learning from monitoring data, thereby supporting adaptive rangeland management.},
 bibtype = {article},
 author = {Bashari, H. and Smith, C. and Bosch, O.J.H.},
 doi = {10.1016/j.agsy.2008.09.003},
 journal = {Agricultural Systems},
 number = {1}
}

@article{
 title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},
 type = {article},
 year = {2013},
 keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},
 pages = {113-121},
 volume = {44},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},
 month = {6},
 id = {ae659db2-aa4d-3a21-bab2-5227c2e85480},
 created = {2015-04-11T18:33:35.000Z},
 accessed = {2015-02-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},
 bibtype = {article},
 author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},
 doi = {10.1016/j.envsoft.2012.07.008},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain},
 type = {article},
 year = {2010},
 keywords = {Aquifer,Bayesian belief networks,Groundwater modelling,Integrated assessment,Mancha Occidental,Participatory modelling},
 pages = {1439-1449},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481520800220X},
 month = {11},
 id = {27f510ec-0ee6-3836-ba11-331e4c3ce528},
 created = {2015-04-11T18:33:35.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Participatory methods provide an increasingly accepted path to integrated assessment. This paper reflects on the role of two participatory modelling initiatives implemented in a highly conflictive setting: the Mancha Occidental aquifer, Spain. The methodologies are described within the context of the case study, examining their potential relevance to integrated assessment from a conceptual standpoint. The strengths and weaknesses of each approach are analysed in absolute and relative terms, attending to the different stages of the modelling process. The focus then shifts to explore the implications of this work within the context of participatory integrated assessment and scenario analysis. This serves the purpose of establishing the reasons why the tools have been useful in the eyes of stakeholders, and how the case-specific findings of this project may be relevant to other settings.},
 bibtype = {article},
 author = {Martínez-Santos, P. and Henriksen, H.J. and Zorrilla, P. and Martínez-Alfaro, P.E.},
 doi = {10.1016/j.envsoft.2008.11.011},
 journal = {Environmental Modelling & Software},
 number = {11}
}

@article{
 title = {An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination},
 type = {article},
 year = {2009},
 keywords = {Bayesian belief network,Evolutionary optimization,Multi-objective,Uncertainty,Water resources management},
 pages = {303-310},
 volume = {24},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001527},
 month = {3},
 id = {a9ab7039-fc72-3b3b-a9fb-d02b3c6fb47d},
 created = {2015-04-11T18:33:35.000Z},
 accessed = {2015-02-19},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.},
 bibtype = {article},
 author = {Farmani, Raziyeh and Henriksen, Hans Jørgen and Savic, Dragan},
 doi = {10.1016/j.envsoft.2008.08.005},
 journal = {Environmental Modelling & Software},
 number = {3}
}

@article{
 title = {Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.},
 type = {article},
 year = {2013},
 keywords = {Bayes Theorem,Geographic Information Systems,Groundwater,Models, Theoretical},
 pages = {136-46},
 volume = {115},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479712005968},
 month = {1},
 day = {30},
 id = {eb1d6109-7a14-3dea-87f7-7d525816fa8b},
 created = {2015-04-11T18:33:36.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches.},
 bibtype = {article},
 author = {Giordano, Raffaele and D'Agostino, Daniela and Apollonio, Ciro and Lamaddalena, Nicola and Vurro, Michele},
 doi = {10.1016/j.jenvman.2012.11.011},
 journal = {Journal of environmental management}
}

@article{
 title = {Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network},
 type = {article},
 year = {2011},
 keywords = {Artificial neural networks,Bayesian belief networks,Knowledge extraction,Net ecosystem metabolism},
 pages = {1199-1210},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001022},
 month = {10},
 id = {9abb4fc4-588f-32bf-9854-9b2c13bed6e9},
 created = {2015-04-11T18:33:36.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.},
 bibtype = {article},
 author = {Young, William A. and Millie, David F. and Weckman, Gary R. and Anderson, Jerone S. and Klarer, David M. and Fahnenstiel, Gary L.},
 doi = {10.1016/j.envsoft.2011.04.004},
 journal = {Environmental Modelling & Software},
 number = {10}
}

@article{
 title = {A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland},
 type = {article},
 year = {2013},
 keywords = {Bayesian Belief Networks,Clean-up costs,Maritime traffic,Oil spill,Risk analysis,The Gulf of Finland},
 pages = {61-71},
 volume = {76},
 websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13005821},
 month = {11},
 id = {f778c0e8-482c-32c1-8276-b92a0d3e2c33},
 created = {2015-04-11T18:33:36.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).},
 bibtype = {article},
 author = {Montewka, Jakub and Weckström, Mia and Kujala, Pentti},
 doi = {10.1016/j.marpolbul.2013.09.031},
 journal = {Marine Pollution Bulletin},
 number = {1-2}
}

@article{
 title = {A review of Bayesian belief networks in ecosystem service modelling},
 type = {article},
 year = {2013},
 keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},
 pages = {1-11},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},
 month = {8},
 id = {0229274b-5eb8-3c13-82dd-e9f5691ae50a},
 created = {2015-04-11T18:46:32.000Z},
 accessed = {2015-02-10},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},
 bibtype = {article},
 author = {Landuyt, Dries and Broekx, Steven and D'hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},
 doi = {10.1016/j.envsoft.2013.03.011},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example},
 type = {article},
 year = {2013},
 keywords = {Bayesian Belief Network,Expert knowledge,Risk assessment,Soil Framework directive,Soil compaction,Uncertainty},
 pages = {56-68},
 volume = {132},
 websites = {http://www.sciencedirect.com/science/article/pii/S0167198713000925},
 month = {8},
 id = {ec8cccf5-6295-358f-8c7f-855694c983ee},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil's vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland.},
 bibtype = {article},
 author = {Troldborg, Mads and Aalders, Inge and Towers, Willie and Hallett, Paul D. and McKenzie, Blair M. and Bengough, A. Glyn and Lilly, Allan and Ball, Bruce C. and Hough, Rupert L.},
 doi = {10.1016/j.still.2013.05.005},
 journal = {Soil and Tillage Research}
}

@article{
 title = {Good practice in Bayesian network modelling},
 type = {article},
 year = {2012},
 keywords = {Bayes network,Bayesian belief network,Ecological models,Good modelling practice,Integration,Model evaluation},
 pages = {134-145},
 volume = {37},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001041},
 month = {11},
 id = {2b4fbce7-9e6c-3add-a5bb-c5edf47da7ec},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs) are increasingly being used to model environmental systems, in order to: integrate multiple issues and system components; utilise information from different sources; and handle missing data and uncertainty. BNs also have a modular architecture that facilitates iterative model development. For a model to be of value in generating and sharing knowledge or providing decision support, it must be built using good modelling practice. This paper provides guidelines to developing and evaluating Bayesian network models of environmental systems, and presents a case study habitat suitability model for juvenile Astacopsis gouldi, the giant freshwater crayfish of Tasmania. The guidelines entail clearly defining the model objectives and scope, and using a conceptual model of the system to form the structure of the BN, which should be parsimonious yet capture all key components and processes. After the states and conditional probabilities of all variables are defined, the BN should be assessed by a suite of quantitative and qualitative forms of model evaluation. All the assumptions, uncertainties, descriptions and reasoning for each node and linkage, data and information sources, and evaluation results must be clearly documented. Following these standards will enable the modelling process and the model itself to be transparent, credible and robust, within its given limitations.},
 bibtype = {article},
 author = {Chen, Serena H. and Pollino, Carmel A.},
 doi = {10.1016/j.envsoft.2012.03.012},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes},
 type = {article},
 year = {1996},
 keywords = {Bayesian belief networks,causal belief networks,diagnosis,expert systems,rulebased systems,uncertainty,wastewater treatment},
 pages = {265-273},
 volume = {10},
 websites = {http://www.sciencedirect.com/science/article/pii/0954181096000039},
 month = {8},
 id = {ac924305-ac28-37c9-90aa-5e5f4444ce33},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The need for computer-based diagnostic tools in wastewater management is outlined. Rule-based and probabilistic approaches to the development of diagnostic expert systems are critically reviewed, and it is demonstrated that the rule-based approach has serious limitations which make it unsuitable for diagnostic tasks under conditions of uncertainty. It is shown that Bayesian belief networks (BBNs), a probabilistic approach, has none of these limitations and is well-suited to diagnosis under uncertainty. The theory and application of BBNs are outlined and illustrated by a simple example based on a wastewater treatment plant. A brief case study is presented of the development of a full-scale BBN for the diagnosis of faults in a wastewater treatment plant. It is concluded that BBNs are far superior to rule-based systems in their ability to diagnose faults in complex systems like wastewater treatment processes, whose behaviour is inherently uncertain.},
 bibtype = {article},
 author = {Chong, H.G. and Walley, W.J.},
 doi = {10.1016/0954-1810(96)00003-9},
 journal = {Artificial Intelligence in Engineering},
 number = {3}
}

@article{
 title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},
 type = {article},
 year = {2001},
 keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},
 pages = {29-42},
 volume = {153},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},
 month = {10},
 id = {2a076313-dfae-38fb-b4b2-d549d498e92e},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},
 bibtype = {article},
 author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},
 doi = {10.1016/S0378-1127(01)00452-2},
 journal = {Forest Ecology and Management},
 number = {1-3}
}

@article{
 title = {Using the integrated ecosystem assessment framework to build consensus and transfer information to managers},
 type = {article},
 year = {2014},
 keywords = {Bayesian Belief Networks,Conceptual ecological models,EBM-DPSER,Ecosystem-based management,Integrated ecosystem assessments,South Florida},
 pages = {11-25},
 volume = {44},
 websites = {http://www.sciencedirect.com/science/article/pii/S1470160X14001265},
 month = {9},
 id = {91133e08-bba3-37b8-abb3-99a57aca3fa1},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-03-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Ecosystem-based management is widely regarded as a method to improve the way we manage our coastal marine resources and ecosystems. Effective ecosystem-based management relies upon synthesizing our scientific knowledge and transferring this knowledge into management actions. Integrated ecosystem assessment is a framework to conduct this scientific synthesis and transfer information to resource managers. Portions of the framework were applied to build consensus on the focal ecosystem components and processes that are characteristic of a sustainable South Florida coastal ecosystem that is producing ecosystem services at the level society desires. Consensus was developed through facilitated meetings that aimed to conceptualize the ecosystem, develop ecosystem indicators, and conduct risk analysis. Resource managers, researchers, academics, and non-governmental organizations participated in these meetings and contributed to the synthesis of science and a myriad of science communications to transfer information to decision makers and the public. A proof of concept Bayesian Belief Network was developed to explore integrating the results of this assessment into an interactive management scenario evaluation tool. The four year effort resulted in the development of a research and management coordination network in South Florida that should provide the foundation for implementing ecosystem-based resource management across multiple agencies.},
 bibtype = {article},
 author = {Fletcher, Pamela J. and Kelble, Christopher R. and Nuttle, William K. and Kiker, Gregory A.},
 doi = {10.1016/j.ecolind.2014.03.024},
 journal = {Ecological Indicators}
}

@article{
 title = {Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway},
 type = {article},
 year = {2014},
 keywords = {Bayesian Belief Networks,Coastal management,Hydrography,Jellyfish,Periphylla,Stakeholders},
 pages = {72-83},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S0308597X13002893},
 month = {5},
 id = {a11badc8-0e7a-3e78-8a55-673f7d1c98b4},
 created = {2015-04-11T18:46:33.000Z},
 accessed = {2015-04-01},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The following article outlines of an assessment of the adaptive capacity of stakeholder groups in the Trondheimsfjord region to the impacts related to local changes in Periphylla periphylla (jellyfish) concentrations. This paper addresses the interaction between the socio-ecological system and the marine ecosystem and the management challenges inherent therein by focusing on a serious management problem that is occurring in several Norwegian fjords. This is the recent superabundance of the lower trophic level jellyfish species P. periphylla, which competes with commercial Norwegian fish species for a wide variety of pelagic organisms including redfeed (Calanus finmarchicus), a key species in the coastal ecosystem and a particularly important food item for all codfishes in coastal waters. P. periphylla has, however, also some properties that might make it a valuable new resource in Norwegian waters, namely its potential for being a new and abundant source of collagen. The question addressed here is how to manage this jellyfish species in a manner that is rational from both socio-political and ecological perspectives, exploring stakeholder perceptions concerning their adaptation options and capacity to implement these options to this new resource and management mitigation options based on a set of stakeholder driven future scenarios.},
 bibtype = {article},
 author = {Gjelsvik Tiller, Rachel and Mork, Jarle and Richards, Russell and Eisenhauer, Lionel and Liu, Yajie and Nakken, Jens-Fredrik and Borgersen, Åshild.L},
 doi = {10.1016/j.marpol.2013.12.006},
 journal = {Marine Policy}
}

@article{
 title = {Green spaces in the direct living environment and social contacts of the aging population},
 type = {article},
 year = {2014},
 keywords = {Aging,Bayesian belief network,Green spaces,Living environment,Social contacts},
 pages = {44-54},
 volume = {129},
 websites = {http://www.sciencedirect.com/science/article/pii/S016920461400125X},
 month = {9},
 id = {f4ed9030-bc5b-34a8-bf10-1e2619ae784d},
 created = {2015-04-11T18:46:34.000Z},
 accessed = {2014-11-28},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Green spaces in the living environment may provide a meeting place and support social contacts. When people get older they, in general, are less mobile and have more limited activity spaces. At the same time they are faced with smaller social networks due to social and health related changes. Green spaces in their direct living environment are therefore important to support their needs. The aim of this study was to better understand the nature of the relationship between various types of green spaces in the direct living environment and the extent and nature of social contacts of the aging generation, taking into account socio-demographics and other physical and social environmental characteristics. Data for this study were obtained from a survey about living surroundings from a national representative sample of 1501 persons in the age category of 60 years and over in the Netherlands conducted in 2009. The survey included both subjective and objective measurements of the direct living environment of the respondents. Specifically, a Bayesian belief network was used to formulate and estimate the direct and indirect relationships between the selected variables. Results show that social contacts among neighbors are mainly influenced by the availability of trees and grass and the perceived level of green. Green spaces support social contacts in the neighborhood. However, the safety and maintenance of the green spaces are also important; high quality green spaces support social contacts between neighbors and strengthen communities for the aging population.},
 bibtype = {article},
 author = {Kemperman, Astrid and Timmermans, Harry},
 doi = {10.1016/j.landurbplan.2014.05.003},
 journal = {Landscape and Urban Planning}
}

@article{
 title = {A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.},
 type = {article},
 year = {2014},
 keywords = {Bayes Theorem,Climate,Climate Change,Ecosystem,Estuaries,Eutrophication,Models, Theoretical,North Carolina,Water Quality},
 pages = {107-15},
 volume = {83},
 websites = {http://www.sciencedirect.com/science/article/pii/S0025326X14002148},
 month = {6},
 day = {15},
 id = {6210ae43-abaf-357b-9e72-dc054e812bcb},
 created = {2015-04-11T18:56:31.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions.},
 bibtype = {article},
 author = {Nojavan A, Farnaz and Qian, Song S and Paerl, Hans W and Reckhow, Kenneth H and Albright, Elizabeth A},
 doi = {10.1016/j.marpolbul.2014.04.011},
 journal = {Marine pollution bulletin},
 number = {1}
}

@article{
 title = {Bayesian decision analysis for environmental and resource management},
 type = {article},
 year = {1997},
 keywords = {Bayesian inference,belief networks,decision analysis,influence diagrams,risk,uncertainty,value of information},
 pages = {177-185},
 volume = {12},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481529700008X},
 month = {1},
 id = {1fbcbc94-b930-34e8-afeb-2528dc5c3fac},
 created = {2015-04-11T18:56:32.000Z},
 accessed = {2015-03-03},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {During the last two decades, much of the theoretical and practical advances in Bayesian decision analysis have been closely linked to the adaptation of emerging new computational — usually Artificial Intelligence — techniques and to progress in computer software, respectively. This paper documents and discusses experience on the use of two recent network model approaches, influence diagrams and belief networks, and relates those approaches to decision trees. They both allow probabilistic, Bayesian studies with classical decision analytic concepts such as risk attitude analysis, value of information and control, multi-attribute analysis, and various structural analyses. The theory of influence diagrams dates back to the early 1980s, and a variety of commercial software are on market. Belief network is a more recent concept that is under process of finding its way to applications. Illustration on environmental and resource management is provided with examples on freshwater and fisheries studies.},
 bibtype = {article},
 author = {Varis, Olli},
 doi = {10.1016/S1364-8152(97)00008-X},
 journal = {Environmental Modelling & Software},
 number = {2-3}
}

@article{
 title = {Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs},
 type = {article},
 year = {2014},
 keywords = {Bayesian belief network,Climate change,Conservation planning,Coral reef,Expert elicitation,Risk assessment},
 pages = {64-72},
 volume = {27},
 websites = {http://www.sciencedirect.com/science/article/pii/S0959378014000843},
 month = {7},
 id = {e6a03683-84ae-3be6-807c-9dfc0103c216},
 created = {2015-04-11T19:07:35.000Z},
 accessed = {2015-01-15},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian belief networks are finding increasing application in adaptive ecosystem management where data are limited and uncertainty is high. The combined effect of multiple stressors is one area where considerable uncertainty exists. Our study area, the Great Barrier Reef is simultaneously data-rich – concerning the physical and biological environment – and data-poor – concerning the effects of interacting stressors. We used a formal expert-elicitation process to obtain estimates of outcomes associated with a variety of scenarios that combined stressors both within and outside the control of local managers. There was much stronger consensus about certain stressor effects – such as between temperature anomalies and bleaching – than others, such as the relationship between water quality and coral cover. In general, the expert outlook for the Great Barrier Reef is pessimistic, with the potential for climate change effects potentially to overshadow the effects of local management actions.},
 bibtype = {article},
 author = {Ban, Stephen S. and Pressey, Robert L. and Graham, Nicholas A.J.},
 doi = {10.1016/j.gloenvcha.2014.04.018},
 journal = {Global Environmental Change}
}

@article{
 title = {Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia},
 type = {article},
 year = {2010},
 keywords = {Adaptive management,Adaptive modelling,Bayesian Belief Network,Great Barrier Reef,Learning support,Water quality},
 pages = {1291-1301},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002618},
 month = {11},
 id = {9e63a1d1-b78a-3e51-8c45-3f012125a461},
 created = {2015-04-11T19:07:35.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The development and use of a Bayesian Belief Network (BBN) model, within an adaptive management process for the management of water quality in the Mackay Whitsunday region of Queensland, Australia is described. The management goal is firstly to set achievable targets for water quality entering the Great Barrier Reef lagoon from the Mackay Whitsunday natural resource management region and then secondly to define and implement a strategy to achieve these targets. The BBN serves as an adaptive framework that managers and scientists may use to articulate what they know about the managed system. It then provides a tool to guide where, when and what interventions (including research) are most likely to achieve management outcomes. Importantly the BBN provides a platform for collective learning. BBN estimates of total suspended sediment (TSS) loads and event mean concentrations (EMCs) were compared to observed data and results from current best practice models. The BBN estimates were reasonable relative to empirical observations. Example results from the BBN are thereafter used to illustrate the use of the model in estimating the likelihood of exceeding water quality targets with and without proposed actions to improve water quality. Example results are also used to illustrate what spatial or land use elements might contribute most to exceeding water quality targets. Finally key limitations of the tool are discussed and important learnings from the process are highlighted.},
 bibtype = {article},
 author = {Lynam, Tim and Drewry, John and Higham, Will and Mitchell, Carl},
 doi = {10.1016/j.envsoft.2009.09.013},
 journal = {Environmental Modelling & Software},
 number = {11}
}

@article{
 title = {Hailfinder: A Bayesian system for forecasting severe weather},
 type = {article},
 year = {1996},
 keywords = {Bayesian,Belief networks,Elicitation,Intelligent systems,Meteorology,System design,Weather forecasting},
 pages = {57-71},
 volume = {12},
 websites = {http://www.sciencedirect.com/science/article/pii/0169207095006648},
 month = {3},
 id = {edb592f0-50e3-39c0-98f3-18b2f3c8b066},
 created = {2015-04-11T19:07:35.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.},
 bibtype = {article},
 author = {Abramson, Bruce and Brown, John and Edwards, Ward and Murphy, Allan and Winkler, Robert L.},
 doi = {10.1016/0169-2070(95)00664-8},
 journal = {International Journal of Forecasting},
 number = {1}
}

@article{
 title = {Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks},
 type = {article},
 year = {2014},
 keywords = {Afforestation,Bayesian belief network,China,Forest transition,Land use change,SLCP},
 pages = {248-258},
 volume = {36},
 websites = {http://www.sciencedirect.com/science/article/pii/S0264837713001555},
 month = {1},
 id = {952422ca-1136-3fed-b247-7519a9b7cd81},
 created = {2015-04-11T19:07:36.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Strict enforcement of forest protection and massive afforestation campaigns have contributed to a significant increase in China's forest cover during the last 20 years. At the same time, demographic changes in rural areas due to changes in reproduction patterns and the emigration of younger population segments have affected land-use strategies. We identified proximate causes and underlying drivers that influence the decisions of farm households to plant trees on former cropland with Bayesian networks (BNs). BNs allow the incorporation of causal relationships in data analysis and can combine qualitative stakeholder knowledge with quantitative data. We defined the structure of the network with expert knowledge and in-depth discussions with land users. The network was calibrated and validated with data from a survey of 509 rural households in two upland areas of Yunnan Province in Southwest China. The results substantiate the influence of land endowments, labor availability and forest policies for switching from cropland to tree planting. State forest policies have constituted the main underlying driver to the forest transition in the past, but private afforestation activities increasingly dominate the expansion of tree cover. Farmers plant trees on private incentives mainly to cash in on the improved economic opportunities provided by tree crops, but tree planting also constitutes an important strategy to adjust to growing labor scarcities.},
 bibtype = {article},
 author = {Frayer, Jens and Sun, Zhanli and Müller, Daniel and Munroe, Darla K. and Xu, Jianchu},
 doi = {10.1016/j.landusepol.2013.08.005},
 journal = {Land Use Policy}
}

@article{
 title = {Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling},
 type = {article},
 year = {2009},
 keywords = {Bayesian belief network (BBN),Black Sea,DPSIR,Eutrophication,Marine socio-ecological systems},
 pages = {2927-2939},
 volume = {220},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380008004420},
 month = {11},
 id = {9204e42d-e51a-375c-b9b1-7c0626665bcf},
 created = {2015-04-11T19:07:36.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.},
 bibtype = {article},
 author = {Langmead, Olivia and McQuatters-Gollop, Abigail and Mee, Laurence D. and Friedrich, Jana and Gilbert, Alison J. and Gomoiu, Marian-Traian and Jackson, Emma L. and Knudsen, Ståle and Minicheva, Galina and Todorova, Valentina},
 doi = {10.1016/j.ecolmodel.2008.09.011},
 journal = {Ecological Modelling},
 number = {21}
}

@article{
 title = {Reducing the risk of house loss due to wildfires},
 type = {article},
 year = {2015},
 keywords = {Bayesian Network,Community engagement,Fire management,Planning,Suppression,Wildfire},
 pages = {12-25},
 volume = {67},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003776},
 month = {5},
 id = {dd85fb82-33ed-3112-9eaa-a0b2c1b5186e},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors.},
 bibtype = {article},
 author = {Penman, T.D. and Nicholson, A.E. and Bradstock, R.A. and Collins, L. and Penman, S.H. and Price, O.F.},
 doi = {10.1016/j.envsoft.2014.12.020},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation},
 type = {article},
 year = {2011},
 keywords = {Adoption,Bayesian Networks,Natural resource management,Policy development},
 pages = {52-65},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000915},
 month = {1},
 id = {d2c4459f-07d8-3c2d-bbfd-ea3722ab6385},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Influencing the management of private landholders is a key element of improving the condition of Australia’s natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.},
 bibtype = {article},
 author = {Ticehurst, J.L and Curtis, A. and Merritt, W.S.},
 doi = {10.1016/j.envsoft.2010.03.032},
 journal = {Environmental Modelling & Software},
 number = {1}
}

@article{
 title = {A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay},
 type = {article},
 year = {2014},
 keywords = {Bayesian hierarchical modeling,Bayesian network,Dreissenid invasion,Observation error,Phosphorus targets,Saginaw Bay,Water quality criteria},
 pages = {90-100},
 volume = {57},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214000619},
 month = {7},
 id = {ec29901c-feb6-3c2b-acdb-e93991455248},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-02-18},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.},
 bibtype = {article},
 author = {Cha, YoonKyung and Stow, Craig A.},
 doi = {10.1016/j.envsoft.2014.02.010},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Prediction analysis of a wastewater treatment system using a Bayesian network},
 type = {article},
 year = {2013},
 keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},
 pages = {140-150},
 volume = {40},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},
 month = {2},
 id = {07511849-6753-38c4-9bdb-aeb95cf6d63c},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},
 bibtype = {article},
 author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},
 doi = {10.1016/j.envsoft.2012.08.011},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach},
 type = {article},
 year = {2015},
 keywords = {Aquatic ecology,Bayesian networks,Discretization,Ecological community,Macroinvertebrates,TITAN,Thresholds},
 pages = {36-45},
 volume = {66},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003764},
 month = {4},
 id = {e08492c9-2d60-3b06-bd97-9fccb755eef8},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-01-22},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The TITAN-based method may be used together with expert opinion.},
 bibtype = {article},
 author = {Lucena-Moya, Paloma and Brawata, Renee and Kath, Jarrod and Harrison, Evan and ElSawah, Sondoss and Dyer, Fiona},
 doi = {10.1016/j.envsoft.2014.12.019},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change},
 type = {article},
 year = {2014},
 keywords = {Bayesian networks,Land use decisions,Land use modeling,Participatory modeling},
 pages = {222-233},
 volume = {52},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002570},
 month = {2},
 id = {49e939ec-75cf-3c6b-a23e-c8bfb76b0ac8},
 created = {2015-04-11T19:51:55.000Z},
 accessed = {2015-02-23},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors' knowledge into a spatially explicit BN. A structured experts' process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors' characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.},
 bibtype = {article},
 author = {Celio, Enrico and Koellner, Thomas and Grêt-Regamey, Adrienne},
 doi = {10.1016/j.envsoft.2013.10.014},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},
 type = {article},
 year = {2007},
 keywords = {Bayesian networks,Endangered species,Hypotheses},
 pages = {37-59},
 volume = {201},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},
 month = {2},
 id = {5d0ffe0d-cdb0-326f-9f54-ba86da63d807},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},
 bibtype = {article},
 author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},
 doi = {10.1016/j.ecolmodel.2006.07.032},
 journal = {Ecological Modelling},
 number = {1}
}

@article{
 title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},
 type = {article},
 year = {2010},
 keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},
 pages = {641-651},
 volume = {221},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},
 month = {2},
 id = {efbda3bc-67d8-309a-8188-fee0c8a80d3b},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},
 bibtype = {article},
 author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},
 doi = {10.1016/j.ecolmodel.2009.11.012},
 journal = {Ecological Modelling},
 number = {4}
}

@article{
 title = {A meta-assessment for elasmobranchs based on dietary data and Bayesian networks},
 type = {article},
 year = {2002},
 keywords = {Bayesian networks,Elasmobranchs,Fisheries management,Food webs,Threatened species},
 pages = {197-211},
 volume = {1},
 websites = {http://www.sciencedirect.com/science/article/pii/S1470160X02000055},
 month = {3},
 id = {6cfb406e-23d4-39ad-8c18-503cdcd07905},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.},
 bibtype = {article},
 author = {Hammond, T.R and Ellis, J.R},
 doi = {10.1016/S1470-160X(02)00005-5},
 journal = {Ecological Indicators},
 number = {3}
}

@article{
 title = {Analysis of topographic and vegetative factors with data mining for landslide verification},
 type = {article},
 year = {2013},
 keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},
 pages = {669-677},
 volume = {61},
 websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},
 month = {12},
 id = {d9301f8a-f1f0-3dd7-b8fe-36b17a45dd03},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-03-03},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},
 bibtype = {article},
 author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},
 doi = {10.1016/j.ecoleng.2013.07.070},
 journal = {Ecological Engineering}
}

@article{
 title = {Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA},
 type = {article},
 year = {2014},
 keywords = {Bayesian networks,Conservation,Land use planning,Land use suitability,Natural resource management,Stakeholder engagement},
 pages = {42-57},
 volume = {291},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380014003056},
 month = {11},
 id = {8adb7754-2183-324d-8933-8e5102931288},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-01-27},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, USA, we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socio-economic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30m×30m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.},
 bibtype = {article},
 author = {},
 doi = {10.1016/j.ecolmodel.2014.06.023},
 journal = {Ecological Modelling}
}

@article{
 title = {Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin},
 type = {article},
 year = {2008},
 keywords = {Bayesian networks,Benefit–cost analysis,Decision analysis,Eutrophication,Influence diagrams,Uncertainty,Water Framework Directive},
 pages = {91-104},
 volume = {66},
 websites = {http://www.sciencedirect.com/science/article/pii/S0921800908000827},
 month = {5},
 id = {8eea9de3-e133-3100-8084-d4f26e98112b},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-02-19},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing cost-effectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.},
 bibtype = {article},
 author = {Barton, D.N. and Saloranta, T. and Moe, S.J. and Eggestad, H.O. and Kuikka, S.},
 doi = {10.1016/j.ecolecon.2008.02.012},
 journal = {Ecological Economics},
 number = {1}
}

@article{
 title = {Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)},
 type = {article},
 year = {2013},
 keywords = {Bayesian network,Decision support,Integrated catchment management,Iran,Sustainability assessment,Vegetation management},
 pages = {48-54},
 volume = {268},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380013003967},
 month = {10},
 id = {1927d58f-21fe-3e7f-9be6-314f51358ff8},
 created = {2015-04-11T19:51:57.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.},
 bibtype = {article},
 author = {Keshtkar, A.R. and Salajegheh, A. and Sadoddin, A. and Allan, M.G.},
 doi = {10.1016/j.ecolmodel.2013.08.003},
 journal = {Ecological Modelling}
}

@article{
 title = {Metrics for evaluating performance and uncertainty of Bayesian network models},
 type = {article},
 year = {2012},
 keywords = {AIC,AUC,Akaike information criterion,BIC,BN,Bayesian information criterion,Bayesian network,Bayesian network model,CPT,Error rates,GCM,GHG,Model performance,Model validation,PPCI,PPCIMIN,PPD,PPPCIMAX,Probability analysis,ROC,SP,Sensitivity analysis,TSS,Uncertainty,VR,area under the (receiver operating) curve,conditional probability table,global circulation model,greenhouse gas,maximum PPCI value given one or more state probabi,minimum PPCI value given one or more state probabi,posterior probability certainty index,posterior probability distribution,receiver operating characteristic (curve),spherical payoff,true skill statistic,variance reduction},
 pages = {50-62},
 volume = {230},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380012000245},
 month = {4},
 id = {3348523f-73e2-388c-a877-9d4052212f08},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-02-18},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model variables, links, node states, conditional probabilities, and node cliques); assessing prediction performance (confusion tables, covariate- and conditional probability-weighted confusion error rates, area under receiver operating characteristic curves, k-fold cross-validation, spherical payoff, Schwarz’ Bayesian information criterion, true skill statistic, Cohen's kappa); and evaluating uncertainty of model posterior probability distributions (Bayesian credible interval, posterior probability certainty index, certainty envelope, Gini coefficient). Examples are presented of applying the metrics to 3 real-world models of wildlife population analysis and management. Using such metrics can vitally bolster model credibility, acceptance, and appropriate application, particularly when informing management decisions.},
 bibtype = {article},
 author = {Marcot, Bruce G.},
 doi = {10.1016/j.ecolmodel.2012.01.013},
 journal = {Ecological Modelling}
}

@article{
 title = {Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model},
 type = {article},
 year = {2008},
 keywords = {Amphibian monitoring,Ascaphus truei,Bayesian networks,Dicamptodon tenebrosus,Hierarchical Bayesian models,Rhyacotriton spp.},
 pages = {210-218},
 volume = {214},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380008000768},
 month = {6},
 id = {b9c62cf5-6e60-39c6-8883-19a93b8353aa},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs) are a probabilistic modeling platform that connect variables through a series of conditional dependences. We demonstrate their utility for broad-scale conservation of amphibian populations where different types of information may be available within the region. Wildlife conservation decisions for most species are made jointly with other objectives and are tightly constrained by finances. Bayesian networks allow the use of all available information in predictions, and can provide managers with the best available information for making decisions. Habitat models were developed as a hierarchical Bayesian (HB) model for aquatic amphibian populations in the temperate Oregon Coast Range, USA. Predictions for new streams sections were made jointly using a Bayesian network to allow the inclusion of different types of available information. Missing habitat variables were modeled based on habitat survey information. Uncertainty in the true (but unknown) habitat variables were incorporated into the prediction intervals. Further, the probabilistic approach allowed us to incorporate survey information for co-occurring species to help make better predictions. Such species information was connected through the Bayesian network by the conditional dependence that arises from shared habitat variables. The utility of Bayesian networks was shown for these populations for broad-scale risk management. In contrast to deterministic models, the probabilistic nature of Bayesian networks is a natural platform for incorporating uncertainty in predictions and inference.},
 bibtype = {article},
 author = {Wilson, Duncan S. and Stoddard, Margo A. and Puettmann, Klaus J.},
 doi = {10.1016/j.ecolmodel.2008.02.003},
 journal = {Ecological Modelling},
 number = {2-4}
}

@article{
 title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},
 pages = {38-50},
 volume = {276},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380014000398},
 month = {3},
 id = {7ae94537-1682-30b1-b604-7af959748642},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modeling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model's dataset. We found that model predictions were more successful when the ranges of physical conditions included in model development were varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modeling impacts of sea-level rise or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.},
 bibtype = {article},
 author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},
 doi = {10.1016/j.ecolmodel.2014.01.005},
 journal = {Ecological Modelling}
}

@article{
 title = {EBI: An index for delivery of ecosystem service bundles},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},
 pages = {252-265},
 volume = {37},
 websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},
 month = {2},
 id = {4950ea88-8fbd-3696-874a-efb0cce29b0c},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-02-04},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},
 bibtype = {article},
 author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},
 doi = {10.1016/j.ecolind.2013.04.006},
 journal = {Ecological Indicators}
}

@article{
 title = {Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips},
 type = {article},
 year = {2015},
 keywords = {Bayesian networks,Ecosystem services,Interdisciplinary research,Valuation},
 pages = {15-27},
 volume = {110},
 websites = {http://www.sciencedirect.com/science/article/pii/S0921800914003711},
 month = {2},
 id = {8062ddd5-b97f-32bd-9a5d-7de30cdc0186},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-01-21},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services from riparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context.},
 bibtype = {article},
 author = {McVittie, Alistair and Norton, Lisa and Martin-Ortega, Julia and Siameti, Ioanna and Glenk, Klaus and Aalders, Inge},
 doi = {10.1016/j.ecolecon.2014.12.004},
 journal = {Ecological Economics}
}

@article{
 title = {Combining state and transition models with dynamic Bayesian networks},
 type = {article},
 year = {2011},
 keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},
 pages = {555-566},
 volume = {222},
 websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},
 month = {2},
 id = {a7a054c9-1e05-3e86-8633-252c31c686f8},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},
 bibtype = {article},
 author = {Nicholson, Ann E. and Flores, M. Julia},
 doi = {10.1016/j.ecolmodel.2010.10.010},
 journal = {Ecological Modelling},
 number = {3}
}

@article{
 title = {Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species},
 type = {article},
 year = {2015},
 keywords = {Bayesian networks,Fisheries management,Kernel density estimation,Pelagic fish,Recruitment forecasting,Supervised classification},
 pages = {35-42},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S1574954114001563},
 month = {1},
 id = {7a2bc8b9-dad4-3812-bab1-52f4f01aaf66},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.},
 bibtype = {article},
 author = {Fernandes, Jose A. and Irigoien, Xabier and Lozano, Jose A. and Inza, Iñaki and Goikoetxea, Nerea and Pérez, Aritz},
 doi = {10.1016/j.ecoinf.2014.11.004},
 journal = {Ecological Informatics}
}

@article{
 title = {A systems approach to unravel complex water management institutions},
 type = {article},
 year = {2008},
 keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},
 pages = {202-215},
 volume = {5},
 websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},
 month = {9},
 id = {03e1c5c5-ca0e-39f7-aac8-77dfa167f9e9},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},
 bibtype = {article},
 author = {Saravanan, V.S.},
 doi = {10.1016/j.ecocom.2008.04.003},
 journal = {Ecological Complexity},
 number = {3}
}

@article{
 title = {Mining monitored data for decision-making with a Bayesian network model},
 type = {article},
 year = {2013},
 keywords = {Bayesian networks,Cyanobacteria,Data mining,Elicitation,Reservoir management,Water quality},
 pages = {26-36},
 volume = {249},
 websites = {http://www.sciencedirect.com/science/article/pii/S030438001200333X},
 month = {1},
 id = {27102ba9-ac77-3ba5-87dd-7283b4291c45},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-08},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers. Monitored data were arranged in a consistently formatted database from which the model could ‘learn’ probabilistic relationships between model elements such as pumped nutrient load, lake water column nutrient concentrations, and Anabaena concentrations. This ‘minimal model’ produced useful insights into ecosystem relationships and provided a basic model for later development. Subsequent modelling and elicitation of conditional probabilities from experts strengthened components of the model for which there is little data available. The approach to incorporating elicited data is described and some simple scenario testing is also presented. Management outcomes resulting from application of the model are presented.},
 bibtype = {article},
 author = {Williams, B.J. and Cole, B.},
 doi = {10.1016/j.ecolmodel.2012.07.008},
 journal = {Ecological Modelling}
}

@article{
 title = {Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour},
 type = {article},
 year = {2010},
 keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},
 pages = {2565-2575},
 volume = {221},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},
 month = {10},
 id = {90ca0fff-a0db-3b88-a996-692a49ce2441},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},
 bibtype = {article},
 author = {Liedloff, Adam C. and Smith, Carl S.},
 doi = {10.1016/j.ecolmodel.2010.07.022},
 journal = {Ecological Modelling},
 number = {21}
}

@article{
 title = {A data mining approach to predictive vegetation mapping using probabilistic graphical models},
 type = {article},
 year = {2011},
 keywords = {Bayesian network,Data mining,Expectation-maximization,Graphical model,Predictive vegetation mapping},
 pages = {111-124},
 volume = {6},
 websites = {http://www.sciencedirect.com/science/article/pii/S1574954111000045},
 month = {3},
 id = {11a286ee-60c8-38cb-a2a6-634a98587984},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2015-02-16},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.},
 bibtype = {article},
 author = {Dlamini, Wisdom M.},
 doi = {10.1016/j.ecoinf.2010.12.005},
 journal = {Ecological Informatics},
 number = {2}
}

@article{
 title = {Advantages and challenges of Bayesian networks in environmental modelling},
 type = {article},
 year = {2007},
 pages = {312-318},
 volume = {203},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380006006089},
 month = {5},
 id = {983df284-5049-3b1c-92dd-fc5e567896b1},
 created = {2015-04-11T19:51:58.000Z},
 accessed = {2014-07-14},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs) are an increasingly popular method of modelling uncertain and complex domains such as ecosystems and environmental management. At best, they provide a robust and mathematically coherent framework for the analysis of this kind of problems. However, there are certain pitfalls as well. In this paper, I summarise the pros and cons of the use of Bayesian networks especially in the context of environmental modelling and management. I will also give references to relevant publications, and introduce some software products that can be used to build Bayesian networks.},
 bibtype = {article},
 author = {},
 journal = {Ecological Modelling},
 number = {3-4}
}

@article{
 title = {Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil},
 type = {article},
 year = {2013},
 keywords = {Bayesian network modelling,Biodiesel,Expert opinion,Family farming,Social inclusion,Systems thinking},
 pages = {81-95},
 volume = {121},
 websites = {http://www.sciencedirect.com/science/article/pii/S0308521X13000887},
 month = {10},
 id = {484e0845-a9f8-3bb7-a2a4-1fbd4a6c552a},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-03-10},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This study focuses on family farmer engagement in the Brazilian national programme for Production and use of Biodiesel (PNPB). The Brazilian government has been promoting the role of family farmers as producers of biomass for biodiesel since 2004; however, fewer than expected family farmers have decided to produce biomass for biodiesel. The North of Minas Gerais is one region where a biodiesel plant has been strategically located to source castor beans grown by family farmers. The target family farm type in this region specializes in beef and/or dairy production with low input pasture (approximately 30ha per farm), maize intercropped with beans (approximately 1ha per farm) and sugarcane (approximately 1ha per farm). We selected this region for a case study to explore management decisions of farmers, industry and policy makers that influence family farmer engagement with biodiesel production through cultivation of castor beans. To evaluate outcomes for family farmers engaging with the PNPB, we focused on how cultivation of castor beans impacts family farmers in terms of income levels, income stability and levels of milk production. We used an application of systems thinking known as Bayesian network modelling (BNM). BNM was chosen for its suitability to integrate different types of knowledge and to include quantitative and qualitative variables. The study was built on a body of scientific literature explaining why family farmers have not been cultivating castor beans for biodiesel production and a body of experiential knowledge of local actors (farmers, extension officers, policy makers, biodiesel manufacturers and researchers in North of Minas Gerais). The complete BNM consisted of a ‘cause and effect’ diagram where the strengths of the causal relationships were quantified with elicited opinions from surveyed local actors. We used the complete BNM to explore scenarios that could improve outcomes for family farmers and consequently increase their level of engagement. For example, we addressed subsidy structures of the PNPB, crop management, farm-level trade-offs and value-chain innovations. We demonstrate that decisions to support family farmer engagement with biodiesel are not singular. Engagement by family farmers requires simultaneously: improvements in technical crop management, reductions in farm-level cash constraints and innovations in the production chain such that engagement of family farmers goes beyond cultivation of one more low-value crop. Finally we discuss some methodological issues from this application of BNM to farming systems research.},
 bibtype = {article},
 author = {Florin, Madeleine J. and van Ittersum, Martin K. and van de Ven, Gerrie W.J.},
 doi = {10.1016/j.agsy.2013.07.002},
 journal = {Agricultural Systems}
}

@article{
 title = {Participatory decision support for agricultural management. A case study from Sri Lanka},
 type = {article},
 year = {2003},
 keywords = {Agricultural management,Agricultural policy,Bayesian network,Decision support system,Integrated management,Sri Lanka,Stakeholder participation},
 pages = {457-482},
 volume = {76},
 websites = {http://www.sciencedirect.com/science/article/pii/S0308521X02000069},
 month = {5},
 id = {ea7f2f84-1ccf-376d-a2da-1cfe7620b78a},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Agricultural policy makers were helped to construct and use a decision support system (DSS) to identify problems and assess potential solutions for a river basin in Sri Lanka. Through building the DSS themselves, policy makers should reach better decisions. The main aim of the study was to test whether this could be done using a tool called a Bayesian network (BN) which is accessible to non-specialists and able to provide a generic, flexible framework for the construction of DSS. Results from a workshop indicated that the approach showed promise, providing a common framework for discussion and allowing policy makers to structure complex systems from a multi-disciplinary perspective. The need for a multi-disciplinary perspective was clearly demonstrated. The study also suggested improvements to the ways in which BNs can be used in practice. Further workshops with farmers highlighted the importance of involving them in the planning process and suggested more effective ways of doing this while using BNs.},
 bibtype = {article},
 author = {Cain, J.D and Jinapala, K and Makin, I.W and Somaratna, P.G and Ariyaratna, B.R and Perera, L.R},
 doi = {10.1016/S0308-521X(02)00006-9},
 journal = {Agricultural Systems},
 number = {2}
}

@article{
 title = {Negotiating participatory irrigation management in the Indian Himalayas},
 type = {article},
 year = {2010},
 keywords = {Bayesian network,Institutional integration,Integrated water management,Policy modelling,South Asia},
 pages = {651-658},
 volume = {97},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378377409003576},
 month = {5},
 id = {03d55546-ca56-351b-b7a8-66ee6994cadc},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Participatory irrigation management (PIM) reforms are implemented in India to facilitate farmers’ participation in irrigation management, through water user groups. Although thousands of user groups have been formed, a closer examination reveals inefficient water use, social power capture by rural elites in the name of participation, inadequate support from government institutions and government's inability to alleviate poverty. Currently, there is inadequate understanding of the linkage between socio-cultural, institutional and ecological factors affecting the outcome of the PIM reforms in India. Drawing from a case study village in the Shiwalik region of the Indian Himalayas, the paper identifies the role of diverse actors to exploit historic and ecological factors to derail the PIM reforms to frame water management problems. Using a combination of research methods and with application of a Bayesian network, the paper explores the inter-linkages between socio-cultural, institutional and ecological factors in derailing the PIM reforms. The paper reveals that PIM policies are never implemented, but integrated through the negotiation with other diverse policies and socio-cultural settings in (re)shaping water resources management. The analysis demonstrates that water is managed by multifaceted governance arrangements. In this governance arrangement state-centric or market-oriented or community-centered institutional arrangements are not superior to each other, rather they incrementally and cumulatively superimpose to (re)shape water resources management. In this process, integration represents a complex blend of statutory and socially embedded actors bringing with them diverse rules to negotiate, along with contextual factors. The findings call for laying out broad principles/ideologies in the policy statements of the statutory public actors that allow other actors to integrate, adapt and make policy processes dynamic. To facilitate this processes, the paper calls for statutory public actors to regulate water distribution, build capacity of actors and offer diverse forums for actors share and debate on the available information to take informed water-related decisions for a sustainable future.},
 bibtype = {article},
 author = {Saravanan, V.S.},
 doi = {10.1016/j.agwat.2009.12.003},
 journal = {Agricultural Water Management},
 number = {5}
}

@article{
 title = {Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks},
 type = {article},
 year = {2005},
 keywords = {Bayesian Networks,Irrigated land,Overexploitation,Stakeholders},
 pages = {21-36},
 volume = {77},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378377405000818},
 month = {8},
 id = {eeeb90f3-7bd6-33de-87b5-af5d9033a066},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Included into the objectives of the EU Water Framework Directive (Directive 2000/60/EC) there are the correct management of the water resources and the involvement of the stakeholders in the decision process. Bayesian Networks, mathematical models based on the probability theory, have been used recently to solve environmental problems. This methodology meets the relevant requirements to the effect that it is fully comprehensive and integrated, as it deals with the water resource as a whole and encourages the participation of all those people and groups who are somehow involved in its use or management. A Bayesian Network was developed by means of stakeholders participation which is intended to be useful in the decision-making process related to water resource management in the Hydrogeological Unit “Eastern Mancha”. The main problem in the region is the risk of overexploitation of the local aquifer, brought about by a considerable increase, over the last 25 years, in the surface area of irrigated arable land. The results offered by the tool show that the current situation is non-sustainable concerning the aquifer exploitation. There are several ways to solve this situation. The first one could be decreasing the current volume of ground water for irrigation, but this solution would not be welcome by the farmers due to losses of income. The second one is replacing groundwater for irrigation by surface water, where the main problem would be the considerable expenses in infrastructures.},
 bibtype = {article},
 author = {Martín de Santa Olalla, F.J. and Domínguez, A. and Artigao, A. and Fabeiro, C. and Ortega, J.F.},
 doi = {10.1016/j.agwat.2004.09.029},
 journal = {Agricultural Water Management},
 number = {1-3}
}

@article{
 title = {A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision.},
 type = {article},
 year = {2014},
 keywords = {Accidents,Accidents: statistics & numerical data,Environment,Models, Chemical,Models, Statistical,Petroleum,Petroleum Pollution,Petroleum Pollution: statistics & numerical data,Risk Assessment,Ships,Ships: statistics & numerical data,Water Pollution, Chemical,Water Pollution, Chemical: statistics & numerical},
 pages = {130-44},
 volume = {79},
 websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13007595},
 month = {2},
 day = {15},
 id = {44afabf0-e88c-34f0-9569-aaf076fb3d2c},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.},
 bibtype = {article},
 author = {Goerlandt, Floris and Montewka, Jakub},
 doi = {10.1016/j.marpolbul.2013.12.026},
 journal = {Marine pollution bulletin},
 number = {1-2}
}

@article{
 title = {Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks},
 type = {article},
 year = {2010},
 keywords = {Baltic salmon,Bayesian network,Commitment,Expert knowledge,Implementation uncertainty,Management plan,Stakeholders},
 pages = {477-486},
 volume = {34},
 websites = {http://www.sciencedirect.com/science/article/pii/S0308597X09001626},
 month = {5},
 id = {a30b55db-89e3-3dc7-852c-22231aaba337},
 created = {2015-04-11T19:52:01.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.},
 bibtype = {article},
 author = {Haapasaari, Päivi and Karjalainen, Timo P.},
 doi = {10.1016/j.marpol.2009.10.002},
 journal = {Marine Policy},
 number = {3}
}

@article{
 title = {A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland.},
 type = {article},
 year = {2011},
 keywords = {Animals,Aquatic Organisms,Aquatic Organisms: drug effects,Bayes Theorem,Computer Simulation,Environmental Monitoring,Environmental Monitoring: methods,Finland,Fresh Water,Fresh Water: chemistry,Models, Theoretical,Oceans and Seas,Petroleum,Petroleum Pollution,Petroleum: toxicity,Plants,Plants: drug effects,Population Dynamics,Reproduction,Species Specificity,Water Pollutants, Chemical,Water Pollutants, Chemical: chemistry,Water Pollutants, Chemical: toxicity},
 pages = {2822-35},
 volume = {62},
 websites = {http://www.sciencedirect.com/science/article/pii/S0025326X11004693},
 month = {12},
 id = {0cfe363b-d1c2-36b8-9ee4-3c0b8f3d308d},
 created = {2015-04-11T19:52:02.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.},
 bibtype = {article},
 author = {Lecklin, Tiina and Ryömä, Riitta and Kuikka, Sakari},
 doi = {10.1016/j.marpolbul.2011.08.045},
 journal = {Marine pollution bulletin},
 number = {12}
}

@article{
 title = {Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation},
 type = {article},
 year = {2011},
 keywords = {Bayesian networks,Conservation,Development,GIS,Land use,Smart Growth},
 pages = {190-203},
 volume = {101},
 websites = {http://www.sciencedirect.com/science/article/pii/S0169204611000697},
 month = {5},
 id = {3d0bde03-c6af-3992-8432-3c72eef0f719},
 created = {2015-04-11T19:52:02.000Z},
 accessed = {2015-01-14},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine's Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales.},
 bibtype = {article},
 author = {McCloskey, Jon T. and Lilieholm, Robert J. and Cronan, Christopher},
 doi = {10.1016/j.landurbplan.2011.02.011},
 journal = {Landscape and Urban Planning},
 number = {2}
}

@article{
 title = {Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Coffee,Expert knowledge,Remote sensing,Rwanda,Very high resolution imagery},
 pages = {331-340},
 volume = {33},
 websites = {http://www.sciencedirect.com/science/article/pii/S0303243414001251},
 month = {12},
 id = {792bc970-bcee-3e78-bee7-7361ff38848e},
 created = {2015-04-11T19:52:03.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2=0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.},
 bibtype = {article},
 author = {Mukashema, A. and Veldkamp, A. and Vrieling, A.},
 doi = {10.1016/j.jag.2014.05.005},
 journal = {International Journal of Applied Earth Observation and Geoinformation}
}

@article{
 title = {A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines},
 type = {article},
 year = {2015},
 keywords = {Bayesian network,Germplasm supply,Nursery accreditation,Nursery organisation},
 pages = {29-41},
 volume = {47},
 websites = {http://www.sciencedirect.com/science/article/pii/S0264837715000824},
 month = {9},
 id = {595f7fe3-90b0-35a3-98f2-c555ac0599e7},
 created = {2015-04-11T19:52:02.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The limited supply of high quality planting materials for a wide species base is a major reason for the limited success of reforestation programmes or projects in many developing countries. This paper reports the research that was undertaken to improve the supply of high quality planting materials for agroforestry, tree farming and reforestation in the Philippines. A systems approach was used to identify mechanisms to improve the operational effectiveness of the forest nursery sector. A Bayesian Belief Network of the forest nursery sector was developed to examine the interactions between the key components of the forest nursery sector, identify key leverage points for intervention and explore potential impacts of possible policy interventions. Although improving the operational effectiveness of individual, communal and government nurseries will result in high operational effectiveness of the forest nursery sector, the operational effectiveness of government nurseries is likely to have a negative impact on the market for seedlings from smallholder nurseries i.e. individual and communal nurseries, thus impeding the sustainability of smallholder nurseries. Increasing the supply of high quality germplasm for a wide variety of species, improving the technical capabilities of smallholder nursery operators in seedling production and increasing the market demand of high quality seedlings from smallholder nurseries are the most important requirements for improving the operational effectiveness of the forest nursery sector. However, government nurseries can play a crucial role in improving the effectiveness of the forest nursery sector by diversifying their production to focus on species that are in demand by smallholder farmers and which cannot be supplied by individual or communal nurseries. Failing to do this will result in the current situation continuing in which government nursery sector competes with private and communal nurseries.},
 bibtype = {article},
 author = {Gregorio, Nestor and Herbohn, John and Harrison, Steve and Smith, Carl},
 doi = {10.1016/j.landusepol.2015.03.009},
 journal = {Land Use Policy}
}

@article{
 title = {Bi-directional risk assessment in carbon capture and storage with Bayesian Networks},
 type = {article},
 year = {2015},
 keywords = {Bayesian Networks,CCS,Risk assessment},
 pages = {150-159},
 volume = {35},
 websites = {http://www.sciencedirect.com/science/article/pii/S1750583615000262},
 month = {4},
 id = {4e33b138-ca45-3429-8b20-cd35252bbabf},
 created = {2015-04-11T19:52:03.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The complex system required for carbon capture and storage (CCS) encompasses numerous sub-systems with inter-dependencies and large parameter uncertainties that propagate throughout the system. Exploring and understanding these inter-dependencies and uncertainties is invaluable for developing robust risk information. Bayesian Networks (BN), a decision support tool, are being increasingly used in the broader risk assessment community and show promise for use in CCS. BNs explore the dependencies and uncertainties within a system and have the potential to provide a better understanding of risk than more traditional tools such as logic trees or other less integrated approaches. Working with experts from within the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), we have developed a generic BN structure for the storage sub-system of CCS which can be used to guide the development of BNs for other CCS applications and for use in both diagnostic and predictive analysis. This bi-directionality provides one of the more important benefits of BNs; it allows for (1) traditional bottom-up risk assessment where the likely consequences based on the expected state of the system can be calculated and also (2) top-down, or outcome oriented risk, where the state of the system leading to a particular outcome, such as the likelihood of 2% leakage in 1000 years, is determined. This allows for a comprehensive sensitivity analysis which highlights important contributors to the risk and also where additional knowledge may benefit the project and reduce uncertainty. A robust expert elicitation procedure, for both the development of the network structure and the determination of event probabilities, is an integral part of the use of any such BN tool in CCS. Finally, we show the direct application of a smaller CCS BN by the CO2CRC.},
 bibtype = {article},
 author = {Gerstenberger, M.C. and Christophersen, A. and Buxton, R. and Nicol, A.},
 doi = {10.1016/j.ijggc.2015.01.010},
 journal = {International Journal of Greenhouse Gas Control}
}

@article{
 title = {Assessing pricing assumptions for weather index insurance in a changing climate},
 type = {article},
 year = {2014},
 keywords = {Adaptation,Bayesian Networks,Climate modeling,India,Uncertainty},
 pages = {76-91},
 volume = {1},
 websites = {http://www.sciencedirect.com/science/article/pii/S2212096314000023},
 id = {10344d5f-c88c-3aaf-869a-863ec53e1c06},
 created = {2015-04-11T19:52:11.000Z},
 accessed = {2015-03-17},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not these products are themselves resilient to climate change has not been well studied. Given climate variability and climate change, an over-reliance on historical climate observations to guide the design of such products can result in premiums which mislead policyholders and insurers alike, about the magnitude of underlying risks. Here, a method to incorporate different sources of climate data into the product design phase is presented. Bayesian Networks are constructed to demonstrate how insurers can assess the product viability from a climate perspective, using past observations and simulations of future climate. Sensitivity analyses illustrate the dependence of pricing decisions on both the choice of information, and the method for incorporating such data. The methods and their sensitivities are illustrated using a case study analysing the provision of index-based crop insurance in Kolhapur, India. We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data.},
 bibtype = {article},
 author = {Daron, J.D. and Stainforth, D.A.},
 doi = {10.1016/j.crm.2014.01.001},
 journal = {Climate Risk Management}
}

@article{
 title = {The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis},
 type = {article},
 year = {2001},
 keywords = {Bayesian networks,Computer vision,Ecosystem analysis,Hydrologic modeling,Image analysis,Image feature extraction,Image segmentation,Knowledge integration,Monitoring urban growth},
 pages = {435-444},
 volume = {5},
 websites = {http://www.sciencedirect.com/science/article/pii/S1093019101000958},
 month = {11},
 id = {40ab50eb-80b4-34d8-882d-a222c43f65d0},
 created = {2015-04-11T19:52:11.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, we discuss the use of hierarchical tree-structured Bayesian networks for integrating knowledge concerning contextual relationships between environmentally relevant features extracted from digital imagery at multiple resolution scales. In our model, conditional probability distributions over continuous valued observations are parameterized using a mixture of multivariate Gaussian distributions. Separate classifiers for pixels and groups of pixels are used as sub-components of the overall model. The Bayesian formalism allows models to be composed in a systematic and statistically sound manner. We illustrate how this approach can be used to resolve ambiguity leading to classification errors and thus improve techniques for the classification of land use from aerial imagery. We present an example relevant to ecosystem analysis, the monitoring of urban growth and the automatic generation of input parameters for hydrologic models.},
 bibtype = {article},
 author = {Pal, Chris and Swayne, Dave and Frey, Brendan},
 doi = {10.1016/S1093-0191(01)00095-8},
 journal = {Advances in Environmental Research},
 number = {4}
}

@article{
 title = {Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development},
 type = {article},
 year = {2012},
 keywords = {Bayesian Network,Integrated Modelling,Sustainability Appraisal,Urban River Corridor},
 pages = {687-697},
 volume = {13},
 websites = {http://www.sciencedirect.com/science/article/pii/S1878029612000631},
 id = {2267e51e-912e-347d-ac26-635682b9676f},
 created = {2015-04-11T19:52:14.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Sustainability Appraisal (SA) is mandatory under the relevant legislation of UK (DCLG, 2008a) and applies to the preparation of Regional Spatial Strategies, Development Plans and Supplementary Planning documents. SA is a complex task that involves integration of social, environmental and economic considerations into formal plans and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical assessment can facilitate discussion, but these can only partially inform decision makers as many important aspects of sustainability are abstract and not quantifiable. Such abstract criteria however can be modelled using a Bayesian Network (BN), combining expert opinions, empirical evidence and other information such as model simulation, survey etc. This paper discusses the work of the URSULA project at the University of Sheffield, in which a participative and integrative approach to urban river corridor development, incorporating the principal of sustainability was used. The project used a case study site in Sheffield, UK, and three alternative scenarios were developed, incorporating a number of possible riverside design features. Scenarios were fully designed and visualised using a variety of different media and a sustainability appraisal was undertaken using a broad range of environmental, social and economic indicators. Experts’ assessment logics were captured through mind mapping and further expert elicitation was used to develop an integrated model for SA. The BN approach allows model complexity to be reduced to a level appropriate for an assessment process, whilst still taking complex system interactions implicitly into account. The integrated SA model is being used to develop better design by optimising different design elements in order to deliver an optimum (re)-development plan.},
 bibtype = {article},
 author = {Kumar, Vikas and Rouquette, J.R. and Lerner, D.N.},
 doi = {10.1016/j.proenv.2012.01.062},
 journal = {Procedia Environmental Sciences}
}

@article{
 title = {A Trust Model Based on Cloud Model and Bayesian Networks},
 type = {article},
 year = {2011},
 keywords = {cloud model ;Bayesian network,context aware,trust model,unceratinty},
 pages = {452-459},
 volume = {11},
 websites = {http://www.sciencedirect.com/science/article/pii/S1878029611008954},
 id = {832ba102-96b9-3e71-917e-fe967b5c591a},
 created = {2015-04-11T19:52:14.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.},
 bibtype = {article},
 author = {Jin, Bo and Wang, Yong and Liu, Zhenyan and Xue, Jingfeng},
 doi = {10.1016/j.proenv.2011.12.072},
 journal = {Procedia Environmental Sciences}
}

@article{
 title = {Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste},
 type = {article},
 year = {2012},
 keywords = {Bayesian Networks,Destruc*tion equipment,Health assessment,Health status,High-risk hazardous chemical wastes},
 pages = {192-201},
 volume = {16},
 websites = {http://www.sciencedirect.com/science/article/pii/S1878029612005658},
 id = {42ee5947-da27-3dba-9e58-0291cce06870},
 created = {2015-04-11T19:52:14.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.},
 bibtype = {article},
 author = {Zhang, Hongyuan and Zhang, Jing and Liu, Xuecheng and Yan, Guohui and Liu, Yanzhao},
 doi = {10.1016/j.proenv.2012.10.027},
 journal = {Procedia Environmental Sciences}
}

@article{
 title = {Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates},
 type = {article},
 year = {2011},
 keywords = {EM-algorithm,Gaussian Bayesian networks (GBNs),Moderate Resolution Imaging Spectroradiometer (MOD,leaf area index (LAI)},
 pages = {74-79},
 volume = {7},
 websites = {http://www.sciencedirect.com/science/article/pii/S1878029611001411},
 id = {499bacd1-d3b3-347b-8c68-3547a1cb097a},
 created = {2015-04-11T19:52:14.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Leaf area index (LAI) is a biophysical variable that is related to atmosphere-biosphere exchange of CO2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products (LAI MODIS). The LAI MODIS has been used to improve the physiological principles predicting growth (3-PG) model within a Bayesian Network (BN) set-up. The MODIS time series, however, contains gaps caused by persistent clouds, cloud contamination, and other retrieval problems. We therefore formulated the EM-algorithm to estimate the missing MODIS LAI values. The EM-algorithm is applied to three different cases: successive and not successive two winter seasons, and not successive missing MODIS LAI during the time study of 26 successive months at which the performance of the BN is assessed. Results show that the MODIS LAI is estimated such that the maximum value of the mean absolute error between the original MODIS LAI and the estimated MODIS LAI by EM-algorithm is 0.16. This is a low value, and shows the success of our approach. Moreover, the BN output improves when the EM-algorithm is carried out to estimate the inconsecutive missing MODIS LAI such that the root mean square error reduces from 1.57 to 1.49. We conclude that the EM-algorithm within a BN can handle the missing MODIS LAI values and that it improves estimation of the LAI.},
 bibtype = {article},
 author = {Mustafaa, Y.T. and Tolpekin, V. and Stein, A.},
 doi = {10.1016/j.proenv.2011.07.014},
 journal = {Procedia Environmental Sciences}
}

@article{
 title = {An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation},
 type = {article},
 year = {2010},
 keywords = {Bayesian network,Cyanobacteria,DOOBN,Dynamic,IBN,Lyngbya majuscula,OOBN,Object oriented},
 pages = {27-37},
 volume = {69},
 websites = {http://www.sciencedirect.com/science/article/pii/S0141113609001032},
 month = {2},
 id = {32672e3a-e7fd-34b5-befa-92b0a26378f9},
 created = {2015-04-11T19:52:18.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Blooms of the cyanobacteria Lyngbya majuscula have occurred for decades around the world. However, with the increase in size and frequency of these blooms, coupled with the toxicity of such algae and their increased biomass, they have become substantial environmental and health issues. It is therefore imperative to develop a better understanding of the scientific and management factors impacting on Lyngbya bloom initiation. This paper suggests an Integrated Bayesian Network (IBN) approach that facilitates the merger of the research being conducted by various parties on Lyngbya. Pivotal to this approach are two Bayesian networks modelling the management and scientific factors of bloom initiation. The research found that Bayesian Networks (BN) and specifically Object Oriented BNs (OOBN) and Dynamic OOBNs facilitate an integrated approach to modelling ecological issues of concern. The merger of multiple models which explore different aspects of the problem through an IBN approach can apply to many multi-faceted environmental problems.},
 bibtype = {article},
 author = {Johnson, Sandra and Fielding, Fiona and Hamilton, Grant and Mengersen, Kerrie},
 doi = {10.1016/j.marenvres.2009.07.004},
 journal = {Marine Environmental Research},
 number = {1}
}

@article{
 title = {Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China},
 type = {article},
 year = {2013},
 keywords = {Bayesian Network,China,Exports,Modelling,Nitrogen,Vegetable},
 pages = {170-181},
 volume = {46},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000716},
 month = {8},
 id = {43f34b8d-12ab-3de0-bfef-40b25d3b2108},
 created = {2015-04-11T19:52:19.000Z},
 accessed = {2015-02-26},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Vegetable farms are one of many nitrogen (N) sources adversely affecting Lake Taihu in eastern China. Given the lack of quantitative “cause and effect” relationships and data relating to these systems, we developed a conceptual Bayesian network to investigate and demonstrate causal relationships and the effects of different mitigation strategies on N exports from vegetable farms in the Lake Taihu region. Structurally, the network comprised one primary transport factor, one primary source factor and three post-mobilisation strategies, and three output factors. In general the network suggests that N exports are more sensitive to transport factors (i.e. runoff volumes) than source factors (i.e. fertiliser application rates) although the cumulative effects of excessive fertiliser were not considered. Post-mobilisation mitigations such as wetlands and ecoditches appear to be particularly effective in decreasing N exports however their implementation on a regional scale may be limited by land availability. While optimising N inputs would be prudent, the network suggests that better irrigation practice, including improved irrigation scheduling, using less imported water and optimising rainfall utilisation would be more effective in achieving environmental goals than simply limiting N supply.},
 bibtype = {article},
 author = {Nash, David and Waters, David and Buldu, Andres and Wu, Yuming and Lin, Yaping and Yang, Weiqiu and Song, Yuzhi and Shu, Jianhua and Qin, Wei and Hannah, Murray},
 doi = {10.1016/j.envsoft.2013.03.008},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management.},
 type = {article},
 year = {2012},
 keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Decision Making,England,Environment,Knowledge,Models, Theoretical,Water},
 pages = {116-27},
 volume = {96},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479711003975},
 month = {4},
 day = {15},
 id = {1bf4dbe7-b7d0-3be6-833a-826220dea6f5},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.},
 bibtype = {article},
 author = {Holzkämper, Annelie and Kumar, Vikas and Surridge, Ben W J and Paetzold, Achim and Lerner, David N},
 doi = {10.1016/j.jenvman.2011.10.016},
 journal = {Journal of environmental management},
 number = {1}
}

@article{
 title = {Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.},
 type = {article},
 year = {2009},
 keywords = {Algorithms,Bayes Theorem,Biological Evolution,Conservation of Natural Resources,Ecosystem,Environment,Geography,Models, Theoretical,Probability,Scotland,Software},
 pages = {236-50},
 volume = {90},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479707003465},
 month = {1},
 id = {dd17dce9-55c0-3c0d-8b3c-e0151478561c},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.},
 bibtype = {article},
 author = {Aitkenhead, M J and Aalders, I H},
 doi = {10.1016/j.jenvman.2007.09.010},
 journal = {Journal of environmental management},
 number = {1}
}

@article{
 title = {Facing uncertainty in ecosystem services-based resource management.},
 type = {article},
 year = {2013},
 keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Ecosystem,Uncertainty},
 pages = {S145-54},
 volume = {127 Suppl},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479712003921},
 month = {9},
 id = {fa8ccc4c-6586-33a7-afda-0ca728827b7c},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-03-26},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.},
 bibtype = {article},
 author = {Grêt-Regamey, Adrienne and Brunner, Sibyl H and Altwegg, Jürg and Bebi, Peter},
 doi = {10.1016/j.jenvman.2012.07.028},
 journal = {Journal of environmental management}
}

@article{
 title = {Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain.},
 type = {article},
 year = {2013},
 keywords = {Agriculture,Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Consumer Participation,Decision Making,Income,Models, Economic,Models, Theoretical,Questionnaires,Rivers,Spain,Uncertainty},
 pages = {400-12},
 volume = {128},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479713003472},
 month = {10},
 day = {15},
 id = {a4674948-9d5e-3785-a9c3-ed8069a4f597},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-03-20},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each other's views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.},
 bibtype = {article},
 author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},
 doi = {10.1016/j.jenvman.2013.05.019},
 journal = {Journal of environmental management}
}

@article{
 title = {Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.},
 type = {article},
 year = {2014},
 keywords = {Bayes Theorem,Dairying,Environment,Industry},
 pages = {184-92},
 volume = {133},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479713007548},
 month = {1},
 day = {15},
 id = {e81c4063-dfc3-35dc-b60b-a148baecaf10},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-02-28},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.},
 bibtype = {article},
 author = {Buys, L and Mengersen, K and Johnson, S and van Buuren, N and Chauvin, A},
 doi = {10.1016/j.jenvman.2013.12.013},
 journal = {Journal of environmental management}
}

@article{
 title = {Bayesian Networks as a screening tool for exposure assessment.},
 type = {article},
 year = {2013},
 keywords = {Australia,Bayes Theorem,Environmental Exposure,Environmental Exposure: analysis,Risk Assessment,Risk Assessment: methods,Soil Pollutants,Soil Pollutants: analysis},
 pages = {68-76},
 volume = {123},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479713001709},
 month = {7},
 day = {15},
 id = {d1800489-6042-3851-87b8-ec9256ddcf34},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A tiered approach to contamination exposure assessment is currently adopted in many countries. Increasing the site-specific information in exposure assessments is generally recommended when guideline values for contaminants in soil are exceeded. This work details a Bayesian Network (BN) approach to developing a site-specific environmental exposure assessment that focuses on the simple mapping and assessment of assumptions and the effect of new data on assessment outcomes. The BN approach was applied to a floodplain system in New South Wales, Australia, where site-specific information about elevated antimony (Sb) concentrations and distribution in soils was available. Guidelines for exposure assessment in Australia are used as a template for this site, although the approach is generic. The BN-based assessment used an iterative approach starting with limited soil Sb data (41 samples ranging from 0 to 18 mg kg-(1) Sb) and extending the model with more detailed Sb data (145 samples ranging from 0 to 40 mg kg-(1) Sb). The analyses identified dominant exposure pathways and assessed the sensitivity of these pathways to changes in assumptions and the level of site-specific information available. In particular, there was a 10.8% probability of exceeding the tolerable daily intake of Sb in the case study when the limited soil Sb data was used, which increased to 26.2% with the more detailed sampling regime. There was also a 47% decrease in the probability of overexposure to Sb when the dermal bioavailability of arsenic (a similar metalloid) was used as a surrogate measure instead of a default bioavailability of 100%. We conclude that the BN approach to soil exposure assessment has merit both in the context of Australian and international soil exposure assessments.},
 bibtype = {article},
 author = {Tighe, Matthew and Pollino, Carmel A and Wilson, Susan C},
 doi = {10.1016/j.jenvman.2013.03.018},
 journal = {Journal of environmental management}
}

@article{
 title = {Classifying environmentally significant urban land uses with satellite imagery.},
 type = {article},
 year = {2008},
 keywords = {Bayes Theorem,California,Cities,Commerce,Environment,Housing,Industry,Recreation,Satellite Communications,Transportation,Water,Water Supply},
 pages = {181-92},
 volume = {86},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479706003975},
 month = {1},
 id = {2cca927c-aedc-3a85-9720-a78cdd55dc8a},
 created = {2015-04-11T19:52:20.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.},
 bibtype = {article},
 author = {Park, Mi-Hyun and Stenstrom, Michael K},
 doi = {10.1016/j.jenvman.2006.12.010},
 journal = {Journal of environmental management},
 number = {1}
}

@article{
 title = {Reforestation planning using Bayesian networks},
 type = {article},
 year = {2009},
 keywords = {Bayesian networks,Environmental variables,GIS,Machine learning,Reforestation},
 pages = {1285-1292},
 volume = {24},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001224},
 month = {11},
 id = {e3ab2c9a-49e3-3ad0-8389-7ef8721d92ad},
 created = {2015-04-11T19:52:26.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The aim of this research was to construct a reforestation model for woodland located in the basin of the river Liébana (NW Spain). This is essentially a pattern recognition problem: the class labels are types of woodland, and the variables for each point are environmental coordinates (referring to altitude, slope, rainfall, lithology, etc.). The model trained using data for existing wooded areas will serve as a guideline for the reforestation of deforested areas. Nonetheless, with a view to tackling reforestation from a more informed perspective, of interest is an interpretable model of relationships existing not just between woodland type and environmental variables but also between and among the environmental variables themselves. For this reason we used Bayesian networks, as a tool that is capable of constructing a causal model of the relationships existing between all the variables represented in the model. The prediction results obtained were compared with those for classical linear techniques, neural networks and support vector machines.},
 bibtype = {article},
 author = {Ordóñez Galán, C. and Matías, J.M. and Rivas, T. and Bastante, F.G.},
 doi = {10.1016/j.envsoft.2009.05.009},
 journal = {Environmental Modelling & Software},
 number = {11}
}

@article{
 title = {Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships},
 type = {article},
 year = {2014},
 keywords = {Continuous Bayesian networks,Landscape,Mixtures of truncated exponentials,Regression,Socioeconomic structure},
 pages = {127-137},
 volume = {57},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481521400067X},
 month = {7},
 id = {b8a790cb-d7e6-3755-a346-7ee7d5969aed},
 created = {2015-04-11T19:52:26.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape–socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling.},
 bibtype = {article},
 author = {Ropero, R.F. and Aguilera, P.A. and Fernández, A. and Rumí, R.},
 doi = {10.1016/j.envsoft.2014.02.016},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Bayesian networks in planning a large aquifer in Eastern Mancha, Spain},
 type = {article},
 year = {2007},
 keywords = {Aquifer,Bayesian networks,Integrated management,Irrigated land,Stakeholders},
 pages = {1089-1100},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481520600137X},
 month = {8},
 id = {f5832962-d077-3d3c-bc27-5c021c6ad676},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The Eastern Mancha Aquifer is located in the south-east of the Iberian Peninsula and is included in the hydrogeological unit of the same name. This aquifer is the main source of water for urban, industrial and agricultural supply within its area of influence. Over the past 30years, the transformation of dry crop lands in the area of this Unit into irrigated crop lands, through groundwater capture, has caused precise declines in piezometric levels of the aquifer, as extraction volumes have exceeded recharge water volumes. This work illustrates the results obtained by using Bayesian networks in the sustainable planning of the Eastern Mancha aquifer. The actions through which this goal can be met are the partial substitution of groundwater with surface water, the improvement of irrigation efficiency and the adequate control of water use.},
 bibtype = {article},
 author = {Martín de Santa Olalla, Francisco and Dominguez, Alfonso and Ortega, Fernando and Artigao, Alfonso and Fabeiro, Concepción},
 doi = {10.1016/j.envsoft.2006.05.020},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {An integrated approach to linking economic valuation and catchment modelling},
 type = {article},
 year = {2011},
 keywords = {Bayesian networks,Catchment scale modelling,Choice experiments,Environmental values,Integrated water resources management,Knowledge integration,Model development},
 pages = {92-102},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000940},
 month = {1},
 id = {afa3520f-faa3-30b8-b122-20ad1cbb0bf7},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-03-02},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.},
 bibtype = {article},
 author = {Kragt, M.E. and Newham, L.T.H. and Bennett, J. and Jakeman, A.J.},
 doi = {10.1016/j.envsoft.2010.04.002},
 journal = {Environmental Modelling & Software},
 number = {1}
}

@article{
 title = {Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment},
 type = {article},
 year = {2007},
 keywords = {Bayesian network,Ecological risk assessment,Ecology,Fish},
 pages = {1140-1152},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000788},
 month = {8},
 id = {c1d8f2b7-97e4-3a66-beda-57aa9fd2f928},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).},
 bibtype = {article},
 author = {Pollino, Carmel A. and Woodberry, Owen and Nicholson, Ann and Korb, Kevin and Hart, Barry T.},
 doi = {10.1016/j.envsoft.2006.03.006},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning},
 type = {article},
 year = {2005},
 keywords = {Bayesian network,Integrated water resource management,Stakeholder participation,Uncertainty},
 pages = {231-242},
 volume = {20},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815204000404},
 month = {2},
 id = {ffad8d16-04b8-3fd8-9c56-255e6e9249a2},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Integrated management is the key to the sustainable development of Europe's water resources. This means that decisions need to be taken in the light of not only environmental considerations, but also their economic, social, and political impacts; it also requires the active participation of stakeholders in the decision making process. The problem is to find a practical way to achieve these aims. One approach is to use Bayesian networks (Bns): networks allow a range of different factors to be linked together, based on probabilistic dependencies, and at the same time provide a framework within which the contributions of stakeholders can be taken into account. A further strength is that Bns explicitly include the element of uncertainty related to any strategy or decision. The links are based on whatever data are available. This may be an extensive data set, output from a model or, in the absence of data, can be based on expert opinion. Networks are being developed for four catchments in Europe as part of the MERIT project; these are in the UK, Denmark, Italy and Spain. In each case stakeholder groups are contributing to the design of the networks that are used as a focus for the consultation process. As an example, the application to water management of a UK basin is discussed.},
 bibtype = {article},
 author = {Bromley, J. and Jackson, N.A. and Clymer, O.J. and Giacomello, A.M. and Jensen, F.V.},
 doi = {10.1016/j.envsoft.2003.12.021},
 journal = {Environmental Modelling & Software},
 number = {2}
}

@article{
 title = {Modelling uncertainty in social–natural interactions},
 type = {article},
 year = {2014},
 keywords = {Hybrid Bayesian networks,Mixtures of truncated exponentials,Socio-ecological system,Systemic change,Water flows},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002096},
 month = {8},
 id = {a3a3542a-81ec-34e9-8a4a-84bd654a598e},
 created = {2015-04-11T19:52:26.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Socio-ecological systems can be represented as a complex network of causal interactions. Modelling such systems requires methodologies that are able to take uncertainty into account. Due to their probabilistic nature, Bayesian networks are a powerful tool for representing complex systems where interactions between variables are subject to uncertainty. In this paper, we study the interactions between social and natural subsystems (land use and water flow components) using hybrid Bayesian networks based on the Mixture of Truncated Exponentials model. This study aims to provide a new methodology to model systemic change in a socio-ecological context. Two endogenous changes – agricultural intensification and the maintenance of traditional cropland – are proposed. Intensification of the agricultural practices leads to a rise in the rate of immigration to the area, as well as to greater water losses through evaporation. By contrast, maintenance of traditional cropland hardly changes the social structure, while increasing evapotranspiration rates and improving the control over runoff water. These results indicate that hybrid Bayesian networks are an excellent tool for modelling social–natural interactions.},
 bibtype = {article},
 author = {Ropero, R.F. and Rumí, R. and Aguilera, P.A.},
 doi = {10.1016/j.envsoft.2014.07.008},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Bayesian Networks and participatory modelling in water resource management},
 type = {article},
 year = {2007},
 keywords = {Bayesian Networks,Decision making,Model integration,Participatory modelling,Water resources planning},
 pages = {1075-1088},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001435},
 month = {8},
 id = {b80f9f8d-5320-37b3-a179-4ff6db8b8547},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.},
 bibtype = {article},
 author = {Castelletti, A. and Soncini-Sessa, R.},
 doi = {10.1016/j.envsoft.2006.06.003},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {A software system for assessing the spatially distributed ecological risk posed by oil shipping},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Ecology,Geospatial,Maritime accident,Oil spill,Risk assessment},
 pages = {1-11},
 volume = {61},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214001960},
 month = {11},
 id = {d406037b-5ccb-3e43-a5f1-b36a6c7c77d5},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.},
 bibtype = {article},
 author = {Jolma, A. and Lehikoinen, A. and Helle, I. and Venesjärvi, R.},
 doi = {10.1016/j.envsoft.2014.06.023},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Selecting among five common modelling approaches for integrated environmental assessment and management},
 type = {article},
 year = {2013},
 keywords = {Agent-based model,Bayesian network,Coupled component model,Integrated assessment,Knowledge-based model,System dynamics},
 pages = {159-181},
 volume = {47},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001151},
 month = {9},
 id = {383ca63b-e6ee-3feb-b63d-fdb7f82b957b},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2014-07-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.},
 bibtype = {article},
 author = {Kelly (Letcher), Rebecca A. and Jakeman, Anthony J. and Barreteau, Olivier and Borsuk, Mark E. and ElSawah, Sondoss and Hamilton, Serena H. and Henriksen, Hans Jørgen and Kuikka, Sakari and Maier, Holger R. and Rizzoli, Andrea Emilio and van Delden, Hedwig and Voinov, Alexey A.},
 doi = {10.1016/j.envsoft.2013.05.005},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks},
 type = {article},
 year = {2010},
 keywords = {Aquifer overexploitation,Decision support systems,Integrated water management,Object-Oriented Bayesian Networks,Stakeholders' engagement},
 pages = {383-397},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002679},
 month = {4},
 id = {3b9044a5-6c1e-392d-8748-0ccc0a0747f5},
 created = {2015-04-11T19:52:26.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Object-Oriented Bayesian Networks (OOBNs) have been used increasingly over the past few decades in fields as diverse as medicine, transport and aeronautics. In this paper, OOBNs are applied to the domain of integrated water management and used as a Decision Support System (DSS). This pioneering study, set in the Altiplano region of Murcia in Southern Spain, describes a method for the integrated analysis of a complex water system supplied by groundwater from four aquifers. This method is based on the development of a multivariable integrated technique based on Bayes' theorem. After identifying all relevant factors related to water management in the area these were then translated to variables within a Bayesian Network (BN) and the relationships between them investigated. Each network represented one of the four aquifer units. These individual BNs were then linked to form an OOBN which was used to represent the complex real-world situation. In this way a DSS to simulate the entire water system was constructed using a group of conventional Bns, linked to produce an OOBN. The main stakeholders of the region contributed to network design and construction throughout the entire process. The paper shows how this type of DSS can be used to evaluate the impacts of a range of management strategies that are available to local planners.},
 bibtype = {article},
 author = {Molina, J.L. and Bromley, J. and García-Aróstegui, J.L. and Sullivan, C. and Benavente, J.},
 doi = {10.1016/j.envsoft.2009.10.007},
 journal = {Environmental Modelling & Software},
 number = {4}
}

@article{
 title = {Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting},
 type = {article},
 year = {2013},
 keywords = {Bayesian networks,Discretization,Environmental modelling,Feature subset selection,Missing imputation,Multi-dimensional classification,Recruitment forecasting,Supervised classification},
 pages = {245-254},
 volume = {40},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002472},
 month = {2},
 id = {26edd41d-4cf1-369a-876f-85ee33da467a},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs.},
 bibtype = {article},
 author = {Fernandes, Jose A. and Lozano, Jose A. and Inza, Iñaki and Irigoien, Xabier and Pérez, Aritz and Rodríguez, Juan D.},
 doi = {10.1016/j.envsoft.2012.10.001},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Public participation modelling using Bayesian networks in management of groundwater contamination},
 type = {article},
 year = {2007},
 keywords = {Active involvement,Bayesian networks,EDSS,Groundwater management,MERIT,Negotiation,Pesticides,Planning,Public participatory modelling,Stakeholders},
 pages = {1101-1113},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000491},
 month = {8},
 id = {934f4a5c-91a2-3116-8f90-19f6396acf0b},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Negotiation and active involvement with participation of water managers, experts, stakeholders and representatives of the general public requires decision support tools (Environmental Decision Support Systems; EDSS) that build on transparency and flexibility in order to reach sound action plans and management instruments. One possible EDSS for active involvement of stakeholders is application of Bayesian networks (Bns). The paper gives an example of a case study (The Danish case) where farmers and hydrologists disputed the degree to which pesticide application affected the quality of deep groundwater. Instead of selecting one opinion or another, the decision was made to include both in the Bns. By adopting this approach, it was possible to view the results from either point of view, accepting the reality of the situation, not becoming mired in an insoluble conflict, and in this way laying the foundation for future compromises. The paper explores Bns as a tool for acting on and dealing with management of groundwater protection. Bns allow stakeholders' divergent values, interests and beliefs to be surfaced and negotiated in participatory processes for areas where conventional physically based groundwater models are insufficient due to lack of data, physical understanding, flexibility or lack of integration capability. In this way, the agency will be able to address the institutional arrangement influencing groundwater protection in all its complexity.},
 bibtype = {article},
 author = {Henriksen, Hans Jørgen and Rasmussen, Per and Brandt, Gyrite and von Bülow, Dorthe and Jensen, Finn V.},
 doi = {10.1016/j.envsoft.2006.01.008},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks},
 type = {article},
 year = {2009},
 keywords = {Bayesian Networks (BNs),Extended Trading Ratio System (ETRS),Monte Carlo simulation,Real time operating rules,The Zarjub River,Trading discharge permits (TDP)},
 pages = {238-246},
 volume = {24},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001126},
 month = {2},
 id = {2807af2e-21af-3c39-9611-97201287e493},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.},
 bibtype = {article},
 author = {Mesbah, Seyyed Morteza and Kerachian, Reza and Nikoo, Mohammad Reza},
 doi = {10.1016/j.envsoft.2008.06.007},
 journal = {Environmental Modelling & Software},
 number = {2}
}

@article{
 title = {A cross-validation package driving Netica with python},
 type = {article},
 year = {2015},
 keywords = {Bayesian networks,Cross-validation,Netica,Prediction,Probability,Python,Uncertainty},
 pages = {14-23},
 volume = {63},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002606},
 month = {1},
 id = {265f368a-fbca-3d7a-a9d5-ec0f95618aaa},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).},
 bibtype = {article},
 author = {Fienen, Michael N. and Plant, Nathaniel G.},
 doi = {10.1016/j.envsoft.2014.09.007},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Coupling real-time control and socio-economic issues in participatory river basin planning},
 type = {article},
 year = {2007},
 keywords = {Bayesian Networks,Integrated Water Resource Management,Model integration,Participation,Reservoir operation},
 pages = {1114-1128},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001344},
 month = {8},
 id = {580f894f-d644-37c5-ad08-eae4a743a324},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.},
 bibtype = {article},
 author = {Castelletti, A. and Soncini-Sessa, R.},
 doi = {10.1016/j.envsoft.2006.05.018},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia},
 type = {article},
 year = {2007},
 keywords = {Bayesian network,Coastal lakes,Decision support,Environmental management,Integrated assessment,Pathogens,Sustainability},
 pages = {1129-1139},
 volume = {22},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000764},
 month = {8},
 id = {b32c69b2-ca0d-3ddb-93b2-8e9e7fbe8cfe},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.},
 bibtype = {article},
 author = {Ticehurst, Jenifer L. and Newham, Lachlan T.H. and Rissik, David and Letcher, Rebecca A. and Jakeman, Anthony J.},
 doi = {10.1016/j.envsoft.2006.03.003},
 journal = {Environmental Modelling & Software},
 number = {8}
}

@article{
 title = {Assessing the likelihood of realizing idealized goals: The case of urban water strategies},
 type = {article},
 year = {2012},
 keywords = {Bayesian Networks (BNs),Integrated Urban Water Management,Subjective logic,Water aid},
 pages = {50-60},
 volume = {35},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000539},
 month = {7},
 id = {db6775b2-898c-33e5-a3c2-14926129a6c5},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space.},
 bibtype = {article},
 author = {Moglia, M. and Perez, P. and Burn, S.},
 doi = {10.1016/j.envsoft.2012.02.005},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks},
 type = {article},
 year = {2009},
 keywords = {Bayesian Networks (BNs),Long-term and short-term operation optimization,Reservoir operating rules,Varying chromosome Length Genetic Algorithm (VLGA)},
 pages = {1420-1432},
 volume = {24},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001431},
 month = {12},
 id = {5985fd58-d279-3ed0-8700-3328fc628910},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, a Bayesian Network (BN) is utilized for developing monthly operating rules for a cascade system of reservoirs which is mainly aimed to control floods and supply irrigation needs. BN is trained and verified using the results of a reservoir operation optimization model, which optimizes monthly releases from cascade reservoirs. The inputs of the BN are monthly inflows, reservoir storages at the beginning of the month, and downstream water demands. The trained BN provides the probability distribution functions of reservoirs' releases for each set of input data. The long-term optimization model in monthly scale is formulated to minimize the expected flood and agricultural water deficit damages. The optimization model is developed using an extended version of the Varying chromosome Length Genetic Algorithm (VLGA-II). To incorporate reservoir preparedness for controlling the probable floods in each month, damages associated with floods with different return periods have been considered in the optimization model. For this purpose, a short-term optimization model which provides the optimal hourly releases during floods is utilized and linked to a flood damage estimation model. Damages due to deficit in supplying agricultural water demands are also calculated based on the functions of crop yield responses to deficit irrigation. The developed models are applied to the cascade system of the Dez and Bakhtiari Reservoirs in Southwest of Iran. The result of the trained BN is compared with the rules developed using classical and fuzzy linear regressions and it is shown that the total damage obtained by the BN-based operating rules is about 60 percent less than the total damage obtained using the fuzzy and classical regression analyses. The average relative error in estimating optimal releases is also reduced about 30 percent by using the BN-based rules.},
 bibtype = {article},
 author = {Malekmohammadi, Bahram and Kerachian, Reza and Zahraie, Banafsheh},
 doi = {10.1016/j.envsoft.2009.06.008},
 journal = {Environmental Modelling & Software},
 number = {12}
}

@article{
 title = {A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models},
 type = {article},
 year = {2013},
 keywords = {Agent based modeling,Bayesian network,China,Human–environment interaction,IAMO-LUC,Land use change,Payments for environmental services,Social influence},
 pages = {15-28},
 volume = {45},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001892},
 month = {7},
 id = {34614a54-fa08-3246-a72b-42712c6676c3},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem services. The model combines agent-based modeling (ABM) with Bayesian belief networks (BBNs) and opinion dynamics models (ODM). The model endows agents with the ability to make land-use decisions at the household and plot levels. The decision-making process is captured with the BBNs that were constructed and calibrated with both qualitative and quantitative information, i.e., knowledge gained from group discussions with stakeholders and empirical survey data. To represent interpersonal interactions within social networks, the decision process is further modulated by the opinion dynamics model. The goals of the model are to improve the ability of ABM to emulate land-use decision making and thus provide a better understanding of the potential impacts of payments for ecosystem services on land use and household livelihoods. Our approach provides three important innovations. First, decision making is represented in a causal directed graph. Second, the model provides a natural framework for combining knowledge from experts and stakeholders with quantitative data. Third, the modular architecture and the software implementation can be customized with modest efforts. The model is therefore a flexible, general platform that can be tailored to other studies by mounting the appropriate case-specific “brain” into the agents. The model was calibrated for the Sloping Land Conversion Program (SLCP) in Yunnan, China using data from participatory mapping, focus group interviews, and a survey of 509 farm households in 17 villages.},
 bibtype = {article},
 author = {Sun, Zhanli and Müller, Daniel},
 doi = {10.1016/j.envsoft.2012.06.007},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Hybrid Bayesian network classifiers: Application to species distribution models},
 type = {article},
 year = {2010},
 keywords = {Classification,Conservation planning,Hybrid Bayesian networks,Mixtures of truncated exponentials},
 pages = {1630-1639},
 volume = {25},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815210001222},
 month = {12},
 id = {d0abd407-543b-3e72-a742-dc64d2f0e3ec},
 created = {2015-04-11T19:52:27.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks are one of the most powerful tools in the design of expert systems located in an uncertainty framework. However, normally their application is determined by the discretization of the continuous variables. In this paper the naïve Bayes (NB) and tree augmented naïve Bayes (TAN) models are developed. They are based on Mixtures of Truncated Exponentials (MTE) designed to deal with discrete and continuous variables in the same network simultaneously without any restriction. The aim is to characterize the habitat of the spur-thighed tortoise (Testudo graeca graeca), using several continuous environmental variables, and one discrete (binary) variable representing the presence or absence of the tortoise. These models are compared with the full discrete models and the results show a better classification rate for the continuous one. Therefore, the application of continuous models instead of discrete ones avoids loss of statistical information due to the discretization. Moreover, the results of the TAN continuous model show a more spatially accurate distribution of the tortoise. The species is located in the Doñana Natural Park, and in semiarid habitats. The proposed continuous models based on MTEs are valid for the study of species predictive distribution modelling.},
 bibtype = {article},
 author = {Aguilera, P.A. and Fernández, A. and Reche, F. and Rumí, R.},
 doi = {10.1016/j.envsoft.2010.04.016},
 journal = {Environmental Modelling & Software},
 number = {12}
}

@article{
 title = {An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics},
 type = {article},
 year = {2011},
 pages = {163-172},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815210002355},
 month = {2},
 id = {b34304ce-36ef-3bbc-9b08-97f45089a527},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We develop a Bayesian network (BN) model that describes estuarine chlorophyll dynamics in the upper section of the Neuse River Estuary in North Carolina, using automated constraint based structure learning algorithms. We examine the functionality and usefulness of the structure learning algorithms in building model topology with real-time data under different scenarios. Generated BN models are evaluated and a final model is selected. Model results indicate that although the effect of water temperature and river flow on chlorophyll dynamics has remained unchanged following the implementation of the nitrogen Total Maximum Daily Load (TMDL) program; the response of chlorophyll levels to nutrient concentrations has been altered. The results stress the importance of incorporating expert defined constraints and links in conjunction with the automated structure learning algorithms to generate more plausible structures and minimize the sensitivity of the learning algorithms. This hybrid approach towards structure learning allows for the incorporation of existing knowledge while limiting the scope of the learning algorithms to defining the links between environmental variables for which the expert has little or no information.},
 bibtype = {article},
 author = {},
 journal = {Environmental Modelling & Software},
 number = {2}
}

@article{
 title = {Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.},
 type = {article},
 year = {2015},
 keywords = {BN,Bayesian network,CFU,DAG,Directed Acyclic Graph,FIB,Health risk assessment,MC,MCMC,MPN,MPRM,Markov chain Monte Carlo,Microbial risk,Modelling,Monte Carlo,QMRA,Uncertainty,colony-forming unit,faecal indicator bacteria,modular process risk model,most probable number,quantitative microbial risk assessment},
 pages = {8-18},
 volume = {80},
 websites = {http://www.sciencedirect.com/science/article/pii/S0160412015000719},
 month = {3},
 day = {28},
 id = {f22a6dfb-58ab-3357-8b28-4075c62627b0},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {BACKGROUND: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.

OBJECTIVES: This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.

METHODS: A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.

DISCUSSION: The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.

CONCLUSION: The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.},
 bibtype = {article},
 author = {Beaudequin, Denise and Harden, Fiona and Roiko, Anne and Stratton, Helen and Lemckert, Charles and Mengersen, Kerrie},
 doi = {10.1016/j.envint.2015.03.013},
 journal = {Environment international}
}

@article{
 title = {Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin},
 type = {article},
 year = {2013},
 keywords = {Bayesian networks,Crop model,Economic model,Integrated assessment modelling,Participatory modelling,Water management},
 pages = {144-157},
 volume = {50},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001989},
 month = {12},
 id = {1a722ac0-453f-34ff-8a7c-98fa9198e16f},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.},
 bibtype = {article},
 author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},
 doi = {10.1016/j.envsoft.2013.09.007},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector},
 type = {article},
 year = {2012},
 keywords = {Bayesian Networks,Environmental factors,GHG emissions},
 pages = {132-148},
 volume = {35},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000643},
 month = {7},
 id = {822361c4-6f80-3309-bbdc-c61ee09777aa},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm's capital income.},
 bibtype = {article},
 author = {Pérez-Miñana, E. and Krause, P.J. and Thornton, J.},
 doi = {10.1016/j.envsoft.2012.02.016},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia},
 type = {article},
 year = {2014},
 keywords = {BN,BUIZ,Bayesian Network,Bushland Urban Interface Zone,Fire management,Interface,PB,Prescribed Burning,Prescribed fire},
 pages = {166-175},
 volume = {52},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002326},
 month = {2},
 id = {5c2294fe-7c00-3d21-b487-245ae333d282},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wildfires can result in significant economic and social losses. Prescribed fire is commonly applied to reduce fuel loads and thereby decrease future fire risk to life and property. Fuel treatments can occur in the landscape or adjacent to houses. Location of the prescribed burns can significantly alter the risk of house loss. Furthermore the cost of treating fuels in the landscape is far cheaper than treating fuels adjacent to the houses. Here we develop a Bayesian Network to examine the relative reduction in risk that can be achieved by prescribed burning in the landscape compared with a 500 m interface zone adjacent to houses. We then compare costs of management treatments to determine the most cost-effective method of reducing risk to houses. Burning in the interface zone resulted in the greatest reduction in risk of fires reaching the houses and the intensity of these fires. Fuel treatment in the interface zone allows for a direct transfer of benefits from the fuel treatment. Costs of treating fuels in the interface were significantly higher on a per hectare basis, but the extent of area requiring treatment was considerably lower. Results of this study demonstrate that treatment of fuels at the interface is not only the best means of reducing risk, it is also the most cost-effective.},
 bibtype = {article},
 author = {Penman, T.D. and Bradstock, R.A. and Price, O.F.},
 doi = {10.1016/j.envsoft.2013.09.030},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {A Bayesian network approach to model farmers' crop choice using socio-psychological measurements of expected benefits of ecosystem services},
 type = {article},
 year = {2014},
 keywords = {Analytical Hierarchy Process,Bayesian network,Decision-making support,Ecosystem services,Theory of planned behavior},
 pages = {227-234},
 volume = {57},
 websites = {http://www.sciencedirect.com/science/article/pii/S136481521400084X},
 month = {7},
 id = {e61d892b-2877-39a3-90d9-1b0a6970eb6c},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Models of ecosystem management typically measure the benefits of ecosystem services in terms of ecological or biophysical variables, which are influenced by management decisions and biophysical/ecological conditions. This study uses farmers' expected benefits of ecosystem services as input variables to model their decision between planting rice, annual crops or perennial crops. Based on the theory of planned behavior, a Bayesian network is constructed to model crop choice depending on attitudes toward the ecosystem services of biomass production, reduction of soil erosion, and water quality improvement. The relative importance of these decision-making criteria is quantified using the Analytical Hierarchy Process. Results indicate that Bayesian networks can use socio-psychological measurements to model decision-making. Especially as an extension to biophysical or economic models, they can serve as a powerful tool for grasping the more abstract socio-psychological dimensions of benefits of ecosystem services, and how they translate into the decisions of ecosystem managers.},
 bibtype = {article},
 author = {Poppenborg, Patrick and Koellner, Thomas},
 doi = {10.1016/j.envsoft.2014.03.006},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices},
 type = {article},
 year = {2011},
 keywords = {BMP,Bayesian Network,Best Management Practice,Best management practice,Fertiliser,Grazing,Monte-Carlo,P,Phosphorus,TP,Total Phosphorus},
 pages = {1079-1088},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815211000843},
 month = {9},
 id = {39b2c2ec-c120-3402-9509-c0efa9004de8},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. <10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results.},
 bibtype = {article},
 author = {Nash, David and Hannah, Murray},
 doi = {10.1016/j.envsoft.2011.03.009},
 journal = {Environmental Modelling & Software},
 number = {9}
}

@article{
 title = {Bayesian networks in environmental modelling},
 type = {article},
 year = {2011},
 keywords = {Bayesian networks,Environment,Model implementation,Review,Software},
 pages = {1376-1388},
 volume = {26},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001472},
 month = {12},
 id = {5fc3a716-77d9-3535-a52b-c3f36d379eee},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-03-12},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems. The goal of this review is to show how BNs are being used in environmental modelling. We are interested in the application of BNs, from January 1990 to December 2010, in the areas of the ISI Web of Knowledge related to Environmental Sciences. It is noted that only the 4.2% of the papers have been published under this item. The different steps that configure modelling via BNs have been revised: aim of the model, data pre-processing, model learning, validation and software. Our literature review indicates that BNs have barely been used for Environmental Science and their potential is, as yet, largely unexploited.},
 bibtype = {article},
 author = {Aguilera, P.A. and Fernández, A. and Fernández, R. and Rumí, R. and Salmerón, A.},
 doi = {10.1016/j.envsoft.2011.06.004},
 journal = {Environmental Modelling & Software},
 number = {12}
}

@article{
 title = {Commentary: IUCN classifications under uncertainty},
 type = {article},
 year = {2012},
 keywords = {Bayesian networks,Fuzzy logic,IUCN,Red list,Threatened species,Uncertainty},
 pages = {119-121},
 volume = {38},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001648},
 month = {12},
 id = {5190ac37-462d-3614-8391-0495edf5bb3c},
 created = {2015-04-11T19:52:28.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15–23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data.},
 bibtype = {article},
 author = {Akçakaya, H. Reşit and Ferson, Scott and Burgman, Mark A. and Keith, David A. and Mace, Georgina M. and Todd, Charles R.},
 doi = {10.1016/j.envsoft.2012.05.009},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests},
 type = {article},
 year = {2012},
 keywords = {Bayesian networks,Cascade correlation,Kalman learning rule,Multi-layer perceptron,Sustainable forest management},
 pages = {190-197},
 volume = {2},
 websites = {http://www.sciencedirect.com/science/article/pii/S2210537912000492},
 month = {12},
 id = {26050b06-9c88-35aa-95c6-34e2f10db391},
 created = {2015-04-11T20:33:12.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Financial exploitation of forests comprises an important part of man activity. There are efforts being made to conserve the sustainable exploitation while simultaneously avoiding degradation of the environment. One tool used in these efforts is the modeling of tree features, such as total tree height, sawn-timber tree height, merchantable tree height, and total or sawn-timber tree volume, which yields an estimate of the forest in finance recoverable goods. Sustainable forest management design must be supported by the adjustment of computational techniques. The purpose of this paper is to assess a reliable modeling approach for estimating individual tree heights for the maturity of trees for logging through determining the applicability of different types of neural network models and identifying a neural network procedure for accurate estimation of these variables. These models serve as an alternative to the traditional regression approach. All types of model estimations are evaluated and compared in this paper. Back Propagation Artificial Neural Network (BPANN), Cascade Correlation Artificial Neural Network (CCANN), and Generalized Regression Neural Network (GRNN) models are developed to estimate individual tree heights for the logging of mature trees, such as sawn-timber height and merchantable height. The results reported in this research suggest that the selected BPANN and CCANN models are reliable and demonstrate their adequacy and potential for estimating sawn-timber and merchantable tree height. The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy. Moreover, the NN models were found to be superior to the tested nonlinear regression models.},
 bibtype = {article},
 author = {Diamantopoulou, Maria J.},
 doi = {10.1016/j.suscom.2012.10.002},
 journal = {Sustainable Computing: Informatics and Systems},
 number = {4}
}

@book{
 title = {Integrated Assessment of Scale Impacts of Watershed Intervention},
 type = {book},
 year = {2015},
 source = {Integrated Assessment of Scale Impacts of Watershed Intervention},
 keywords = {Bayesian network,capital strength,integrated modeling,livelihood capitals,resilience},
 pages = {287-316},
 websites = {http://www.sciencedirect.com/science/article/pii/B9780128000670000098},
 publisher = {Elsevier},
 id = {d58a843e-6613-33cb-9a3f-60fa7c81d68e},
 created = {2015-04-11T20:33:13.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.},
 bibtype = {book},
 author = {Merritt, Wendy and Patch, Brendan and Kumar Rout, Sanjit},
 doi = {10.1016/B978-0-12-800067-0.00009-8}
}

@article{
 title = {A mobility constraint model to infer sensor behaviour in forest fire risk monitoring},
 type = {article},
 year = {2012},
 keywords = {Bayesian networks,Forest fire risk monitoring,Mobile wireless sensor network,Mobility constraints,Sensor behaviour,Spatial coverage},
 pages = {81-95},
 volume = {36},
 websites = {http://www.sciencedirect.com/science/article/pii/S0198971511000676},
 month = {1},
 id = {d61193c0-c196-318b-ba47-9e2d44e37b7d},
 created = {2015-04-11T22:23:05.000Z},
 accessed = {2015-03-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.},
 bibtype = {article},
 author = {Ballari, Daniela and Wachowicz, Monica and Bregt, Arnold K. and Manso-Callejo, Miguel},
 doi = {10.1016/j.compenvurbsys.2011.06.004},
 journal = {Computers, Environment and Urban Systems},
 number = {1}
}

@article{
 title = {Modelling uncertainty in agricultural image analysis},
 type = {article},
 year = {1997},
 keywords = {Algorithm fusion,Bayesian networks,Image analysis,Uncertainty},
 pages = {295-305},
 volume = {17},
 websites = {http://www.sciencedirect.com/science/article/pii/S0168169997013227},
 month = {6},
 id = {112c3213-8659-3cee-b728-b0bb21b9bb65},
 created = {2015-04-12T17:48:22.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {No absolute certainty can be given for information derived for images. In most cases image analysis uses single algorithms, or multiple single algorithms' results which are combined in an ad hoc manner, to derive certain information (e.g. edges and textures) to segment images into various regions of interest. However, more robust methods of data fusion can be developed which are based on mathematical foundations of probability theory. One such method combines results from single algorithms using a Bayesian network. This should improve the confidence in the derived image segmentation and gives a direct measure of the probability of each region to be classified correctly. Specific agricultural examples using a Bayesian data fusion approach are given.},
 bibtype = {article},
 author = {Onyango, Christine M. and Marchant, John A. and Zwiggelaar, Reyer},
 doi = {10.1016/S0168-1699(97)01322-7},
 journal = {Computers and Electronics in Agriculture},
 number = {3}
}

@article{
 title = {Modelling the benefits of habitat restoration in socio-ecological systems},
 type = {article},
 year = {2014},
 keywords = {Bayesian Networks,Decision making,Expert opinion,Restoration,Revegetation,Socio-ecological systems,Species richness,Uncertainty},
 pages = {60-67},
 volume = {169},
 websites = {http://www.sciencedirect.com/science/article/pii/S0006320713003789},
 month = {1},
 id = {93e42a20-3418-36bf-b03f-8161bb374b3f},
 created = {2015-04-12T18:51:30.000Z},
 accessed = {2015-01-22},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions compared to those that do not take these factors into account. We demonstrate how Bayesian Networks can be used to integrate ecological and social data and expert opinion to model the cost-effectiveness of revegetation activities for restoring biodiversity in agricultural landscapes. We demonstrate our approach with a case-study in grassy woodlands of south-eastern Australia. In our case-study, cost-effectiveness is defined as the improvement in native reptile and beetle species richness achieved per dollar spent on a restoration action. Socio-ecological models predict that weed control, the planting of trees and shrubs, the addition of litter and timber, and the addition of rocks are likely to be the most cost-effective actions for improving reptile and beetle species richness. The cost-effectiveness of restoration actions is lower in remnant and revegetated areas than in cleared areas because of the higher marginal benefits arising from acting in degraded habitats. This result is contingent on having favourable landowner attitudes. Under the best-case landowner demographic scenarios the greatest biodiversity benefits are seen when cleared areas are restored. We find that current restoration investment practices may not be increasing faunal species richness in agricultural landscapes in the most cost-effective way, and that new restoration actions may be necessary. Integrated socio-ecological models support transparent and cost-effective conservation investment decisions. Application of these models highlights the importance of collecting both social and ecological data when attempting to understand and manage socio-ecological systems.},
 bibtype = {article},
 author = {Jellinek, Sacha and Rumpff, Libby and Driscoll, Don A. and Parris, Kirsten M. and Wintle, Brendan A.},
 doi = {10.1016/j.biocon.2013.10.023},
 journal = {Biological Conservation}
}

@article{
 title = {Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour},
 type = {article},
 year = {2010},
 keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},
 pages = {2565-2575},
 volume = {221},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},
 month = {10},
 id = {4337bf37-9106-3918-a95f-74583cbba3ad},
 created = {2015-04-12T19:14:40.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},
 bibtype = {article},
 author = {Liedloff, Adam C. and Smith, Carl S.},
 doi = {10.1016/j.ecolmodel.2010.07.022},
 journal = {Ecological Modelling},
 number = {21}
}

@article{
 title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},
 type = {article},
 year = {2001},
 keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},
 pages = {29-42},
 volume = {153},
 websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},
 month = {10},
 id = {2b9e25b4-1810-3167-ae7a-a2d6c0ba496a},
 created = {2015-04-12T19:47:10.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},
 bibtype = {article},
 author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},
 doi = {10.1016/S0378-1127(01)00452-2},
 journal = {Forest Ecology and Management},
 number = {1-3}
}

@article{
 title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},
 type = {article},
 year = {2007},
 keywords = {Bayesian networks,Endangered species,Hypotheses},
 pages = {37-59},
 volume = {201},
 websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},
 month = {2},
 id = {c6a17f4b-1f28-3b4b-9550-5d882a385c0c},
 created = {2015-04-12T20:17:32.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},
 bibtype = {article},
 author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},
 doi = {10.1016/j.ecolmodel.2006.07.032},
 journal = {Ecological Modelling},
 number = {1}
}

@article{
 title = {State-and-transition modelling for Adaptive Management of native woodlands},
 type = {article},
 year = {2011},
 keywords = {Adaptive Management,Bayesian network,Native vegetation,Process model,Restoration,State-and-transition},
 pages = {1224-1236},
 volume = {144},
 websites = {http://www.sciencedirect.com/science/article/pii/S0006320710004763},
 month = {4},
 id = {eb2a4f53-5347-397e-90c4-cb09a8a9d2f0},
 created = {2015-04-12T20:17:32.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Adaptive Management (AM) is widely advocated as an approach to dealing with uncertainty in natural resource management as it provides an explicit framework for motivating, designing and interpreting the results of monitoring. One of the major factors impeding implementation is the failure to use appropriate process models; a core element of AM. Process models represent beliefs about the properties and dynamics of an ecological system and ecosystem responses to management. Quantitative models of ecosystem response help resolve ambiguity about the efficacy of management and facilitate iterative updating of knowledge using monitoring data. We report on the use of a state-and-transition model (STM) in the Adaptive Management of native woodland vegetation in south-eastern Australia. The STM is implemented as a Bayesian network, making it simple to communicate and update with new data as they arise. Application of the model is demonstrated using case-study and simulation data. We show how the model may be used to predict the probability of achieving desirable state transitions at restoration sites and how monitoring of those sites can be used to update the model (learn) and adapt (review restoration strategies). After just one monitoring/learning cycle, 7years after the first investments, we found that updated models predict markedly different transition probabilities compared with initial models based on expert opinion. This has strong implications for the apparent cost-efficiency of restoration strategies. The STM approach provides a sound theoretical basis for restoration decisions, while the Bayesian network implementation provides a workable framework for using the STM adaptively.},
 bibtype = {article},
 author = {Rumpff, L. and Duncan, D.H. and Vesk, P.A. and Keith, D.A. and Wintle, B.A.},
 doi = {10.1016/j.biocon.2010.10.026},
 journal = {Biological Conservation},
 number = {4}
}

@article{
 title = {A systems approach to unravel complex water management institutions},
 type = {article},
 year = {2008},
 keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},
 pages = {202-215},
 volume = {5},
 websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},
 month = {9},
 id = {7ae5fbce-67db-300e-8963-c3bf52f746a5},
 created = {2015-04-12T20:17:32.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},
 bibtype = {article},
 author = {Saravanan, V.S.},
 doi = {10.1016/j.ecocom.2008.04.003},
 journal = {Ecological Complexity},
 number = {3}
}

@article{
 title = {Bayesian networks and the quest for reserve adequacy},
 type = {article},
 year = {2012},
 keywords = {Bayesian network,Interior least tern,Persistence,Piping plover,Reserve adequacy,Reserve selection,Stochastic dynamic programming,Whooping crane},
 pages = {178-186},
 volume = {152},
 websites = {http://www.sciencedirect.com/science/article/pii/S0006320712001577},
 month = {8},
 id = {62641700-0260-3c6e-ac80-3a1604b60fdd},
 created = {2015-04-12T20:17:32.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. We describe a method that integrates correlates of persistence for multiple species into a single currency – site quality. Site quality is, in turn, an explicit measure of performance used in optimization. We develop a Bayesian network to assess site quality, which assigns an expected value to a property based on criteria arrayed into a causal diagram. We then use stochastic dynamic programming to determine whether an organization should acquire or reject a site placed on the public market. Our framework for assessing sites and making land acquisition decisions represents a compromise between the use of generic spatial design criteria and more intensive computational tools, like spatially-explicit population models. There is certainly a loss of precision by using site quality as a surrogate for more direct measures of persistence. However, we believe this simplification is defensible when sufficient data, expertise, or other resources are lacking.},
 bibtype = {article},
 author = {Schapaugh, Adam W. and Tyre, Andrew J.},
 doi = {10.1016/j.biocon.2012.03.014},
 journal = {Biological Conservation}
}

@article{
 title = {Analysis of topographic and vegetative factors with data mining for landslide verification},
 type = {article},
 year = {2013},
 keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},
 pages = {669-677},
 volume = {61},
 websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},
 month = {12},
 id = {a79bd6e1-4460-3443-86c7-1e0dc4e4cd8c},
 created = {2015-04-12T20:17:33.000Z},
 accessed = {2015-03-03},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},
 bibtype = {article},
 author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},
 doi = {10.1016/j.ecoleng.2013.07.070},
 journal = {Ecological Engineering}
}

@article{
 title = {EBI: An index for delivery of ecosystem service bundles},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},
 pages = {252-265},
 volume = {37},
 websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},
 month = {2},
 id = {bd5cb454-3186-32c5-8404-381786b4598b},
 created = {2015-04-12T20:17:33.000Z},
 accessed = {2015-02-04},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},
 bibtype = {article},
 author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},
 doi = {10.1016/j.ecolind.2013.04.006},
 journal = {Ecological Indicators}
}

@article{
 title = {Combining state and transition models with dynamic Bayesian networks},
 type = {article},
 year = {2011},
 keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},
 pages = {555-566},
 volume = {222},
 websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},
 month = {2},
 id = {2168ced9-6983-35c2-99f2-f939103c2901},
 created = {2015-04-12T20:17:35.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},
 bibtype = {article},
 author = {Nicholson, Ann E. and Flores, M. Julia},
 doi = {10.1016/j.ecolmodel.2010.10.010},
 journal = {Ecological Modelling},
 number = {3}
}

@article{
 title = {Prediction analysis of a wastewater treatment system using a Bayesian network},
 type = {article},
 year = {2013},
 keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},
 pages = {140-150},
 volume = {40},
 websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},
 id = {70c3be7f-ee3a-352b-9820-4656d9bbc625},
 created = {2015-04-22T21:19:07.000Z},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},
 bibtype = {article},
 author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},
 doi = {10.1016/j.envsoft.2012.08.011},
 journal = {Environmental Modelling & Software}
}

@article{
 title = {Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia.},
 type = {article},
 year = {2015},
 keywords = {Climate change,Decision support system,Habitat condition,Ramsar wetland},
 pages = {127-138},
 volume = {157},
 websites = {http://www.sciencedirect.com/science/article/pii/S0301479715300244},
 month = {4},
 day = {17},
 id = {6ac1efdc-afed-397c-96c2-d95ddc982173},
 created = {2015-04-29T18:49:46.000Z},
 accessed = {2015-04-29},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.},
 bibtype = {article},
 author = {Fu, Baihua and Pollino, Carmel A and Cuddy, Susan M and Andrews, Felix},
 doi = {10.1016/j.jenvman.2015.04.021},
 journal = {Journal of environmental management}
}

@article{
 title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},
 type = {article},
 year = {2014},
 keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},
 pages = {38-50},
 volume = {276},
 websites = {https://darchive.mblwhoilibrary.org/handle/1912/7233},
 month = {3},
 publisher = {Elsevier},
 day = {31},
 id = {801a4e65-dfa4-3867-b5eb-f3b6cd49d872},
 created = {2015-05-07T19:12:09.000Z},
 accessed = {2015-04-11},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 language = {en_US},
 private_publication = {false},
 abstract = {© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 276 (2014): 38–50, doi:10.1016/j.ecolmodel.2014.01.005.},
 bibtype = {article},
 author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},
 doi = {10.1016/j.ecolmodel.2014.01.005},
 journal = {Ecological Modelling}
}

@article{
 title = {Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species},
 type = {article},
 year = {2016},
 pages = {1-11},
 websites = {http://link.springer.com/10.1007/s10666-016-9524-4},
 month = {7},
 publisher = {Springer International Publishing},
 day = {31},
 id = {bb10d0e8-6dd8-39b4-af81-7a48d1a145c7},
 created = {2016-08-06T13:36:25.000Z},
 accessed = {2016-08-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-03-14T14:27:45.955Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Sujak, Agnieszka and Kusz, Andrzej and Rymarz, Marcin and Kitowski, Ignacy},
 doi = {10.1007/s10666-016-9524-4},
 journal = {Environmental Modeling & Assessment}
}

@article{
 title = {Developing a new Bayesian Risk Index for risk evaluation of soil contamination},
 type = {article},
 year = {2017},
 pages = {167-177},
 volume = {603},
 websites = {http://www.sciencedirect.com/science/article/pii/S0048969717314729},
 id = {baf70cd6-06b3-3c79-a490-4a4ffdb101b2},
 created = {2017-06-21T13:23:38.837Z},
 accessed = {2017-06-21},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-06-21T13:23:38.837Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs.},
 bibtype = {article},
 author = {Albuquerque, M.T.D. and Gerassis, S. and Sierra, C. and Taboada, J. and Martín, J.E. and Antunes, I.M.H.R. and Gallego, J.R.},
 doi = {10.1016/j.scitotenv.2017.06.068},
 journal = {Science of The Total Environment}
}

@article{
 title = {Applications of Bayesian belief networks in water resource management: A systematic review},
 type = {article},
 year = {2016},
 volume = {85},
 id = {a2a41975-a65d-35f4-9b19-8d9fbb2f94b1},
 created = {2017-08-23T21:31:39.274Z},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-08-23T21:31:39.274Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.},
 bibtype = {article},
 author = {Phan, Thuc D. and Smart, James C R and Capon, Samantha J. and Hadwen, Wade L. and Sahin, Oz},
 doi = {10.1016/j.envsoft.2016.08.006},
 journal = {Environmental Modelling and Software}
}

@article{
 title = {Bayesian belief network models to analyse and predict ecological water quality in rivers},
 type = {article},
 year = {2015},
 volume = {312},
 id = {30b72578-1e45-327e-9a12-23a0d68e9ace},
 created = {2017-08-23T21:38:25.174Z},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-08-23T21:38:25.174Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Economic growth is often based on the intensification of crop production, energy consumption and urbanization. In many cases, this leads to the degradation of aquatic ecosystems. Modelling water resources and the related identification of key drivers of change are essential to improve and protect water quality in river basins. This study evaluates the potential of Bayesian belief network models to predict the ecological water quality in a typical multifunctional and tropical river basin. Field data, expert knowledge and literature data were used to develop a set of Bayesian belief network models. The developed models were evaluated based on weighted Cohen's Kappa (??<inf>w</inf>), percentage of correctly classified instances (CCI) and spherical payoff. On top, a sensitivity analysis and practical simulation tests of the two most reliable models were performed. Cross-validation based on ??<inf>w</inf> (Model 1: 0.44??0.08; Model 2: 0.44??0.11) and CCI (Model 1: 36.3??2.3; Model 2: 41.6??2.3) indicated that the performance was reliable and stable. Model 1 comprised of input variables main land use, elevation, sediment type, chlorophyll, flow velocity, dissolved oxygen, and chemical oxygen demand; whereas Model 2 did not include dissolved oxygen and chemical oxygen demand. Although the predictive performance of Model 2 was slightly higher than that of Model 1, simulation outcomes of Model 1 were more coherent. Additionally, more management options could be evaluated with Model 1. As the model's ability to simulate management outcomes is of utmost importance in model selection, Model 1 is recommended as a tool to support decision-making in river management. Model predictions and sensitivity analysis indicated that flow velocity is the major variable determining ecological water quality and suggested that construction of additional dams and water abstraction within the basin would have an adverse effect on water quality. Although a case study in a single river basin is presented, the modelling approach can be of general use on any other river basin.},
 bibtype = {article},
 author = {Forio, Marie Anne Eurie and Landuyt, Dries and Bennetsen, Elina and Lock, Koen and Nguyen, Thi Hanh Tien and Ambarita, Minar Naomi Damanik and Musonge, Peace Liz Sasha and Boets, Pieter and Everaert, Gert and Dominguez-Granda, Luis and Goethals, Peter L M},
 doi = {10.1016/j.ecolmodel.2015.05.025},
 journal = {Ecological Modelling}
}

@article{
 title = {A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study},
 type = {article},
 year = {2016},
 volume = {60},
 id = {b2cdd9ec-2d60-358e-92fb-57b1191a95eb},
 created = {2017-08-23T21:40:59.207Z},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2017-08-23T21:40:59.207Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.},
 bibtype = {article},
 author = {Yet, Barbaros and Constantinou, Anthony and Fenton, Norman and Neil, Martin and Luedeling, Eike and Shepherd, Keith},
 doi = {10.1016/j.eswa.2016.05.005},
 journal = {Expert Systems with Applications}
}

@article{
 title = {Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications},
 type = {article},
 year = {2018},
 keywords = {Causality,Coastal resiliency,Evidence‐based policy,Influence diagrams,Watershed conservation practices},
 websites = {http://doi.wiley.com/10.1002/ieam.2027},
 month = {2},
 publisher = {Wiley-Blackwell},
 day = {22},
 id = {6d333bfb-f52e-3125-abac-a92559804d95},
 created = {2018-03-31T21:58:07.222Z},
 accessed = {2018-03-31},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2018-03-31T21:58:07.222Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Carriger, John F and Dyson, Brian E and Benson, William H},
 doi = {10.1002/ieam.2027},
 journal = {Integrated Environmental Assessment and Management}
}

@article{
 title = {Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran},
 type = {article},
 year = {2018},
 pages = {279},
 volume = {190},
 websites = {http://link.springer.com/10.1007/s10661-018-6609-3},
 month = {5},
 publisher = {Springer International Publishing},
 day = {13},
 id = {db0cf666-f3d4-32da-b854-8fb0c99ccea3},
 created = {2018-04-25T01:18:01.632Z},
 accessed = {2018-04-24},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2018-04-25T01:18:01.632Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Malekmohammadi, Bahram and Tayebzadeh Moghadam, Negar},
 doi = {10.1007/s10661-018-6609-3},
 journal = {Environmental Monitoring and Assessment},
 number = {5}
}

@article{
 title = {A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve},
 type = {article},
 year = {2019},
 pages = {767-777},
 volume = {218},
 websites = {https://www.sciencedirect.com/science/article/pii/S0045653518322677#!},
 month = {3},
 publisher = {Pergamon},
 day = {1},
 id = {7a8f52b9-c000-37ca-ba69-ae2b997ebac5},
 created = {2018-12-07T01:00:37.818Z},
 accessed = {2018-12-06},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2018-12-07T01:00:37.818Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The impact of mining activities on the environment is vast. In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.},
 bibtype = {article},
 author = {Boente, C. and Albuquerque, M.T.D. and Gerassis, S. and Rodríguez-Valdés, E. and Gallego, J.R.},
 doi = {10.1016/J.CHEMOSPHERE.2018.11.172},
 journal = {Chemosphere}
}

@article{
 title = {Dynamic Bayesian network for crop growth prediction in greenhouses},
 type = {article},
 year = {2020},
 pages = {105167},
 volume = {169},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131},
 month = {2},
 id = {8ae93dcc-1177-388a-a326-5589a48fedea},
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 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
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 confirmed = {false},
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 bibtype = {article},
 author = {Kocian, A. and Massa, D. and Cannazzaro, S. and Incrocci, L. and Di Lonardo, S. and Milazzo, P. and Chessa, S.},
 doi = {10.1016/j.compag.2019.105167},
 journal = {Computers and Electronics in Agriculture}
}

@article{
 title = {A Bayesian network approach to refining ecological risk assessments: Mercury and the Florida panther (Puma concolor coryi)},
 type = {article},
 year = {2020},
 pages = {108911},
 volume = {418},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193},
 month = {2},
 id = {348ea094-0f44-384b-a378-c1ae48b0c907},
 created = {2020-01-28T14:13:04.708Z},
 accessed = {2020-01-28},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
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 last_modified = {2020-01-28T14:13:04.708Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Carriger, John F. and Barron, Mace G.},
 doi = {10.1016/j.ecolmodel.2019.108911},
 journal = {Ecological Modelling}
}

@techreport{
 title = {Bayesian networks: A guide for their application in natural resource management and policy What is the objective of the model? Testing model scenarios Evaluation of models (sensitivity and accuracy) Parameterise model (quantitative and qualitative) Describe the model variables (assign states) Transform conceptual model into influence diagram Conceptual model of how the system works},
 type = {techreport},
 year = {2010},
 websites = {www.landscapelogic.org.au},
 id = {591a715b-2aec-3587-82db-2aebb3b8dd72},
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 authored = {false},
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 hidden = {false},
 private_publication = {false},
 bibtype = {techreport},
 author = {}
}

@article{
 title = {Probabilistic computational model for correlated wind speed, solar irradiation, and load using Bayesian network},
 type = {article},
 year = {2020},
 pages = {1-1},
 websites = {https://ieeexplore.ieee.org/document/9020145/},
 id = {c63ee328-e3b5-37bb-8010-13bf1f03e0d7},
 created = {2020-03-10T13:48:26.328Z},
 accessed = {2020-03-10},
 file_attached = {true},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2020-03-10T13:48:38.251Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Hongtao and Zou, Bin},
 doi = {10.1109/ACCESS.2020.2977727},
 journal = {IEEE Access}
}

@inbook{
 type = {inbook},
 year = {2020},
 pages = {347-370},
 websites = {http://link.springer.com/10.1007/978-3-030-42553-1_14},
 publisher = {Springer, Cham},
 id = {89e06c64-23e8-3016-9631-1377b0a71ff4},
 created = {2020-06-02T21:00:54.976Z},
 accessed = {2020-06-02},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2020-06-02T21:00:54.976Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {inbook},
 author = {Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.},
 doi = {10.1007/978-3-030-42553-1_14},
 chapter = {Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation}
}

@article{
 title = {Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support},
 type = {article},
 year = {2021},
 keywords = {Bayesian networks,Causal modeling,Conceptual site models,Ecological risk assessment,Ecological risk management,Environmental solutions,Qualitative influence diagrams},
 pages = {111478},
 volume = {278},
 month = {1},
 publisher = {Academic Press},
 day = {15},
 id = {6099340e-e5ff-3c41-88fd-2153eec18491},
 created = {2020-11-02T19:20:01.320Z},
 accessed = {2020-11-02},
 file_attached = {false},
 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
 group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},
 last_modified = {2020-11-02T19:20:01.423Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.},
 bibtype = {article},
 author = {Carriger, John F. and Parker, Randy A.},
 doi = {10.1016/j.jenvman.2020.111478},
 journal = {Journal of Environmental Management}
}\">\n            <i class=\"fa fa-download fa-fw\"></i> Download BibTeX\n          </a>\n        </li>\n        <li>\n          <a href=\"//bibbase.org/rss?bib=\">\n            <i class=\"fa fa-rss fa-fw\"></i> RSS Feed\n          </a>\n          </li>\n      </ul>\n      </li>\n\n      \n\n\n      \n    </ul>\n\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_embed\"\n         style=\"display: none;\">\n\n      Excellent! 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In order to keep using Mendeley with BibBase past April\n        14th, you need to:\n        <ol>\n          <li>renew the authorization for BibBase on Mendeley, and</li>\n          <li>update the BibBase URL\n            in your page the same way you did when you initially set up\n            this page.\n          </li>\n        </ol>\n      </p>\n\n      <p>\n        <a href=\"http://bibbase.org/cgi-bin/mendeley2/get.py\">\n          <i class=\"fa fa-angle-double-right\"></i>\n          Fix it now</a>\n      </p>\n    </div>\n\n  </div>\n\n\n  <div id=\"bibbase_body\">\n    \n  \n  <div class=\"bibbase_group_whole\" id=\"group_2021\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2021')\"\n      onkeypress=\"toggleGroup('group_2021')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2021</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"carriger-parker-conceptualbayesiannetworksforcontaminatedsiteecologicalriskassessmentandremediationsupport-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Carriger,  J., F.;  and Parker,  R., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Environmental Management</i>, 278: 111478. 1 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2020.111478\"\n     onclick=\"log_download('carriger-parker-conceptualbayesiannetworksforcontaminatedsiteecologicalriskassessmentandremediationsupport-2021', 'http://doi.org/10.1016/j.jenvman.2020.111478', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/carriger-parker-conceptualbayesiannetworksforcontaminatedsiteecologicalriskassessmentandremediationsupport-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('carriger-parker-conceptualbayesiannetworksforcontaminatedsiteecologicalriskassessmentandremediationsupport-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Conceptual Bayesian networks for contaminated site ecological risk assessment and remediation support},\n type = {article},\n year = {2021},\n keywords = {Bayesian networks,Causal modeling,Conceptual site models,Ecological risk assessment,Ecological risk management,Environmental solutions,Qualitative influence diagrams},\n pages = {111478},\n volume = {278},\n month = {1},\n publisher = {Academic Press},\n day = {15},\n id = {6099340e-e5ff-3c41-88fd-2153eec18491},\n created = {2020-11-02T19:20:01.320Z},\n accessed = {2020-11-02},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-11-02T19:20:01.423Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.},\n bibtype = {article},\n author = {Carriger, John F. and Parker, Randy A.},\n doi = {10.1016/j.jenvman.2020.111478},\n journal = {Journal of Environmental Management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The causal pathways of stressors that lead to impacts on individuals, populations, and communities of organisms are useful to know for designing alternatives that manage or remediate ecological risks. The ecological risk assessment (ERA) framework (USEPA, 1998b) can help to identify and prioritize management of risks. One key product of the problem formulation step in an ERA, that captures and represents causal knowledge, is the conceptual site model (CSM). The CSM is a graphical depiction of the risk environment that traces the fate and transport pathways of contaminants from sources of contamination (e.g., a leaking storage tank) to receptors (i.e., the ecological endpoints of concern in the risk assessment). The CSM guides the development of methods for assessing ecological risk scenarios and for remediation design alternatives. The qualitative and quantitative aspects of Bayesian networks may support CSM development and risk characterization. Bayesian networks provide a graphical platform geared toward probabilistic modeling making them important candidates for calculating risks in environmental assessments. The diagrammatic representation of causal Bayesian networks (i.e., the directed acyclic graphs) also adds explanatory depth for developing the evidence-base for risk characterization and remediation interventions. We call these qualitative graphs conceptual Bayesian networks (CBNs). The components of CBNs can be used to represent the variables and relationships between sources of contamination, media transfer, bioaccumulation, and risk. The connections help to compose, piece together, and explore hypothesized relationships that bring about high-risk scenarios. Causal pathway analysis of the CBNs provides visualizations of exposure pathways from initial and intermediate sources to receptors. Remediation options that would interrupt or stop the transport of contaminants to ecological receptors can then be identified. Even if the CBN is not quantified, the structures can support mechanistic and statistical designs for exposure and effects analysis and risk characterization and evaluate information needs for resolving uncertainties. This paper will examine these and other unexplored benefits of CBNs to assessment and management of contaminated sites.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2020\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2020')\"\n      onkeypress=\"toggleGroup('group_2020')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2020</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131', event);\">\n    Dynamic Bayesian network for crop growth prediction in greenhouses.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kocian,  A.; Massa,  D.; Cannazzaro,  S.; Incrocci,  L.; Di Lonardo,  S.; Milazzo,  P.;  and Chessa,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Electronics in Agriculture</i>, 169: 105167. 2 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131\"\n     onclick=\"log_download('kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dynamic Bayesian network for crop growth prediction in greenhouses [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compag.2019.105167\"\n     onclick=\"log_download('kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020', 'http://doi.org/10.1016/j.compag.2019.105167', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kocian-massa-cannazzaro-incrocci-dilonardo-milazzo-chessa-dynamicbayesiannetworkforcropgrowthpredictioningreenhouses-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dynamic Bayesian network for crop growth prediction in greenhouses},\n type = {article},\n year = {2020},\n pages = {105167},\n volume = {169},\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0168169919321131},\n month = {2},\n id = {8ae93dcc-1177-388a-a326-5589a48fedea},\n created = {2020-01-11T19:54:57.755Z},\n accessed = {2020-01-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-01-11T19:54:57.839Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Kocian, A. and Massa, D. and Cannazzaro, S. and Incrocci, L. and Di Lonardo, S. and Milazzo, P. and Chessa, S.},\n doi = {10.1016/j.compag.2019.105167},\n journal = {Computers and Electronics in Agriculture}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193', event);\">\n    A Bayesian network approach to refining ecological risk assessments: Mercury and the Florida panther (Puma concolor coryi).\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Carriger,  J., F.;  and Barron,  M., G.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 418: 108911. 2 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193\"\n     onclick=\"log_download('carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network approach to refining ecological risk assessments: Mercury and the Florida panther (Puma concolor coryi) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2019.108911\"\n     onclick=\"log_download('carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020', 'http://doi.org/10.1016/j.ecolmodel.2019.108911', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('carriger-barron-abayesiannetworkapproachtorefiningecologicalriskassessmentsmercuryandthefloridapantherpumaconcolorcoryi-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network approach to refining ecological risk assessments: Mercury and the Florida panther (Puma concolor coryi)},\n type = {article},\n year = {2020},\n pages = {108911},\n volume = {418},\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0304380019304193},\n month = {2},\n id = {348ea094-0f44-384b-a378-c1ae48b0c907},\n created = {2020-01-28T14:13:04.708Z},\n accessed = {2020-01-28},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-01-28T14:13:04.708Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Carriger, John F. and Barron, Mace G.},\n doi = {10.1016/j.ecolmodel.2019.108911},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/14a26397-d240-ea77-7647-7b3b0ab26a2e/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020', 'https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/14a26397-d240-ea77-7647-7b3b0ab26a2e/full_text.pdf.pdf', event);\">\n    Probabilistic computational model for correlated wind speed, solar irradiation, and load using Bayesian network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  H.;  and Zou,  B.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Access</i>,1-1.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/14a26397-d240-ea77-7647-7b3b0ab26a2e/full_text.pdf.pdf\"\n     onclick=\"log_download('wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020', 'https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/14a26397-d240-ea77-7647-7b3b0ab26a2e/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Probabilistic computational model for correlated wind speed, solar irradiation, and load using Bayesian network [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9020145/\"\n     onclick=\"log_download('wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020', 'https://ieeexplore.ieee.org/document/9020145/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Probabilistic computational model for correlated wind speed, solar irradiation, and load using Bayesian network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/ACCESS.2020.2977727\"\n     onclick=\"log_download('wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020', 'http://doi.org/10.1109/ACCESS.2020.2977727', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>4 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-zou-probabilisticcomputationalmodelforcorrelatedwindspeedsolarirradiationandloadusingbayesiannetwork-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Probabilistic computational model for correlated wind speed, solar irradiation, and load using Bayesian network},\n type = {article},\n year = {2020},\n pages = {1-1},\n websites = {https://ieeexplore.ieee.org/document/9020145/},\n id = {c63ee328-e3b5-37bb-8010-13bf1f03e0d7},\n created = {2020-03-10T13:48:26.328Z},\n accessed = {2020-03-10},\n file_attached = {true},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-03-10T13:48:38.251Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Hongtao and Zou, Bin},\n doi = {10.1109/ACCESS.2020.2977727},\n journal = {IEEE Access}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"davis-good-hunter-johnson-mengersen--2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'davis-good-hunter-johnson-mengersen--2020', 'http://link.springer.com/10.1007/978-3-030-42553-1_14', event);\">\n    Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Davis,  J.; Good,  K.; Hunter,  V.; Johnson,  S.;  and Mengersen,  K., L.\n</span>\n\n  \n\n</span>\n\n  pages 347-370. Springer, Cham,  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-42553-1_14\"\n     onclick=\"log_download('davis-good-hunter-johnson-mengersen--2020', 'http://link.springer.com/10.1007/978-3-030-42553-1_14', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\" [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-42553-1_14\"\n     onclick=\"log_download('davis-good-hunter-johnson-mengersen--2020', 'http://doi.org/10.1007/978-3-030-42553-1_14', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/davis-good-hunter-johnson-mengersen--2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('davis-good-hunter-johnson-mengersen--2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inbook{\n type = {inbook},\n year = {2020},\n pages = {347-370},\n websites = {http://link.springer.com/10.1007/978-3-030-42553-1_14},\n publisher = {Springer, Cham},\n id = {89e06c64-23e8-3016-9631-1377b0a71ff4},\n created = {2020-06-02T21:00:54.976Z},\n accessed = {2020-06-02},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-06-02T21:00:54.976Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {inbook},\n author = {Davis, Jac and Good, Kyle and Hunter, Vanessa and Johnson, Sandra and Mengersen, Kerrie L.},\n doi = {10.1007/978-3-030-42553-1_14},\n chapter = {Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2019\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2019')\"\n      onkeypress=\"toggleGroup('group_2019')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2019</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0045653518322677#!\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019', 'https://www.sciencedirect.com/science/article/pii/S0045653518322677#!', event);\">\n    A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Boente,  C.; Albuquerque,  M.; Gerassis,  S.; Rodríguez-Valdés,  E.;  and Gallego,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Chemosphere</i>, 218: 767-777. 3 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0045653518322677#!\"\n     onclick=\"log_download('boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019', 'https://www.sciencedirect.com/science/article/pii/S0045653518322677#!', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/J.CHEMOSPHERE.2018.11.172\"\n     onclick=\"log_download('boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019', 'http://doi.org/10.1016/J.CHEMOSPHERE.2018.11.172', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('boente-albuquerque-gerassis-rodrguezvalds-gallego-acoupledmultivariatestatisticsgeostatisticalandmachinelearningapproachtoaddresssoilpollutioninaprototypicalhgminingsiteinanaturalreserve-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve},\n type = {article},\n year = {2019},\n pages = {767-777},\n volume = {218},\n websites = {https://www.sciencedirect.com/science/article/pii/S0045653518322677#!},\n month = {3},\n publisher = {Pergamon},\n day = {1},\n id = {7a8f52b9-c000-37ca-ba69-ae2b997ebac5},\n created = {2018-12-07T01:00:37.818Z},\n accessed = {2018-12-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2018-12-07T01:00:37.818Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The impact of mining activities on the environment is vast. In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.},\n bibtype = {article},\n author = {Boente, C. and Albuquerque, M.T.D. and Gerassis, S. and Rodríguez-Valdés, E. and Gallego, J.R.},\n doi = {10.1016/J.CHEMOSPHERE.2018.11.172},\n journal = {Chemosphere}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The impact of mining activities on the environment is vast. In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2018\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2018')\"\n      onkeypress=\"toggleGroup('group_2018')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2018</span>\n      <span class=\"bibbase_group_count\">\n        \n        (2)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://doi.wiley.com/10.1002/ieam.2027\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018', 'http://doi.wiley.com/10.1002/ieam.2027', event);\">\n    Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Carriger,  J., F.; Dyson,  B., E.;  and Benson,  W., H.\n</span>\n\n  \n\n</span>\n\n  <i>Integrated Environmental Assessment and Management</i>. 2 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://doi.wiley.com/10.1002/ieam.2027\"\n     onclick=\"log_download('carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018', 'http://doi.wiley.com/10.1002/ieam.2027', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/ieam.2027\"\n     onclick=\"log_download('carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018', 'http://doi.org/10.1002/ieam.2027', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('carriger-dyson-benson-representingcausalknowledgeinenvironmentalpolicyinterventionsadvantagesandopportunitiesforqualitativeinfluencediagramapplications-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Representing causal knowledge in environmental policy interventions: Advantages and opportunities for qualitative influence diagram applications},\n type = {article},\n year = {2018},\n keywords = {Causality,Coastal resiliency,Evidence‐based policy,Influence diagrams,Watershed conservation practices},\n websites = {http://doi.wiley.com/10.1002/ieam.2027},\n month = {2},\n publisher = {Wiley-Blackwell},\n day = {22},\n id = {6d333bfb-f52e-3125-abac-a92559804d95},\n created = {2018-03-31T21:58:07.222Z},\n accessed = {2018-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2018-03-31T21:58:07.222Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Carriger, John F and Dyson, Brian E and Benson, William H},\n doi = {10.1002/ieam.2027},\n journal = {Integrated Environmental Assessment and Management}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10661-018-6609-3\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018', 'http://link.springer.com/10.1007/s10661-018-6609-3', event);\">\n    Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Malekmohammadi,  B.;  and Tayebzadeh Moghadam,  N.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Monitoring and Assessment</i>, 190(5): 279. 5 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10661-018-6609-3\"\n     onclick=\"log_download('malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018', 'http://link.springer.com/10.1007/s10661-018-6609-3', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10661-018-6609-3\"\n     onclick=\"log_download('malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018', 'http://doi.org/10.1007/s10661-018-6609-3', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('malekmohammadi-tayebzadehmoghadam-applicationofbayesiannetworksinahierarchicalstructureforenvironmentalriskassessmentacasestudyofthegabricdamiran-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran},\n type = {article},\n year = {2018},\n pages = {279},\n volume = {190},\n websites = {http://link.springer.com/10.1007/s10661-018-6609-3},\n month = {5},\n publisher = {Springer International Publishing},\n day = {13},\n id = {db0cf666-f3d4-32da-b854-8fb0c99ccea3},\n created = {2018-04-25T01:18:01.632Z},\n accessed = {2018-04-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2018-04-25T01:18:01.632Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Malekmohammadi, Bahram and Tayebzadeh Moghadam, Negar},\n doi = {10.1007/s10661-018-6609-3},\n journal = {Environmental Monitoring and Assessment},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2017\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2017')\"\n      onkeypress=\"toggleGroup('group_2017')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2017</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0048969717314729\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017', 'http://www.sciencedirect.com/science/article/pii/S0048969717314729', event);\">\n    Developing a new Bayesian Risk Index for risk evaluation of soil contamination.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Albuquerque,  M.; Gerassis,  S.; Sierra,  C.; Taboada,  J.; Martín,  J.; Antunes,  I.;  and Gallego,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Science of The Total Environment</i>, 603: 167-177.  2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0048969717314729\"\n     onclick=\"log_download('albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017', 'http://www.sciencedirect.com/science/article/pii/S0048969717314729', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing a new Bayesian Risk Index for risk evaluation of soil contamination [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.scitotenv.2017.06.068\"\n     onclick=\"log_download('albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017', 'http://doi.org/10.1016/j.scitotenv.2017.06.068', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('albuquerque-gerassis-sierra-taboada-martn-antunes-gallego-developinganewbayesianriskindexforriskevaluationofsoilcontamination-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing a new Bayesian Risk Index for risk evaluation of soil contamination},\n type = {article},\n year = {2017},\n pages = {167-177},\n volume = {603},\n websites = {http://www.sciencedirect.com/science/article/pii/S0048969717314729},\n id = {baf70cd6-06b3-3c79-a490-4a4ffdb101b2},\n created = {2017-06-21T13:23:38.837Z},\n accessed = {2017-06-21},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-06-21T13:23:38.837Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs.},\n bibtype = {article},\n author = {Albuquerque, M.T.D. and Gerassis, S. and Sierra, C. and Taboada, J. and Martín, J.E. and Antunes, I.M.H.R. and Gallego, J.R.},\n doi = {10.1016/j.scitotenv.2017.06.068},\n journal = {Science of The Total Environment}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2016\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2016')\"\n      onkeypress=\"toggleGroup('group_2016')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2016</span>\n      <span class=\"bibbase_group_count\">\n        \n        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10666-016-9524-4\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016', 'http://link.springer.com/10.1007/s10666-016-9524-4', event);\">\n    Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sujak,  A.; Kusz,  A.; Rymarz,  M.;  and Kitowski,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modeling & Assessment</i>,1-11. 7 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10666-016-9524-4\"\n     onclick=\"log_download('sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016', 'http://link.springer.com/10.1007/s10666-016-9524-4', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10666-016-9524-4\"\n     onclick=\"log_download('sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016', 'http://doi.org/10.1007/s10666-016-9524-4', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sujak-kusz-rymarz-kitowski-environmentalbioindicationstudiesbybayesiannetworkwithuseofgreyheronasmodelspecies-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Environmental Bioindication Studies by Bayesian Network with Use of Grey Heron as Model Species},\n type = {article},\n year = {2016},\n pages = {1-11},\n websites = {http://link.springer.com/10.1007/s10666-016-9524-4},\n month = {7},\n publisher = {Springer International Publishing},\n day = {31},\n id = {bb10d0e8-6dd8-39b4-af81-7a48d1a145c7},\n created = {2016-08-06T13:36:25.000Z},\n accessed = {2016-08-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Sujak, Agnieszka and Kusz, Andrzej and Rymarz, Marcin and Kitowski, Ignacy},\n doi = {10.1007/s10666-016-9524-4},\n journal = {Environmental Modeling &amp; Assessment}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"phan-smart-capon-hadwen-sahin-applicationsofbayesianbeliefnetworksinwaterresourcemanagementasystematicreview-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Applications of Bayesian belief networks in water resource management: A systematic review.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Phan,  T., D.; Smart,  J., C., R.; Capon,  S., J.; Hadwen,  W., L.;  and Sahin,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling and Software</i>, 85.  2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2016.08.006\"\n     onclick=\"log_download('phan-smart-capon-hadwen-sahin-applicationsofbayesianbeliefnetworksinwaterresourcemanagementasystematicreview-2016', 'http://doi.org/10.1016/j.envsoft.2016.08.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/phan-smart-capon-hadwen-sahin-applicationsofbayesianbeliefnetworksinwaterresourcemanagementasystematicreview-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('phan-smart-capon-hadwen-sahin-applicationsofbayesianbeliefnetworksinwaterresourcemanagementasystematicreview-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Applications of Bayesian belief networks in water resource management: A systematic review},\n type = {article},\n year = {2016},\n volume = {85},\n id = {a2a41975-a65d-35f4-9b19-8d9fbb2f94b1},\n created = {2017-08-23T21:31:39.274Z},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-08-23T21:31:39.274Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.},\n bibtype = {article},\n author = {Phan, Thuc D. and Smart, James C R and Capon, Samantha J. and Hadwen, Wade L. and Sahin, Oz},\n doi = {10.1016/j.envsoft.2016.08.006},\n journal = {Environmental Modelling and Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yet-constantinou-fenton-neil-luedeling-shepherd-abayesiannetworkframeworkforprojectcostbenefitandriskanalysiswithanagriculturaldevelopmentcasestudy-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yet,  B.; Constantinou,  A.; Fenton,  N.; Neil,  M.; Luedeling,  E.;  and Shepherd,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Expert Systems with Applications</i>, 60.  2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.eswa.2016.05.005\"\n     onclick=\"log_download('yet-constantinou-fenton-neil-luedeling-shepherd-abayesiannetworkframeworkforprojectcostbenefitandriskanalysiswithanagriculturaldevelopmentcasestudy-2016', 'http://doi.org/10.1016/j.eswa.2016.05.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yet-constantinou-fenton-neil-luedeling-shepherd-abayesiannetworkframeworkforprojectcostbenefitandriskanalysiswithanagriculturaldevelopmentcasestudy-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yet-constantinou-fenton-neil-luedeling-shepherd-abayesiannetworkframeworkforprojectcostbenefitandriskanalysiswithanagriculturaldevelopmentcasestudy-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study},\n type = {article},\n year = {2016},\n volume = {60},\n id = {b2cdd9ec-2d60-358e-92fb-57b1191a95eb},\n created = {2017-08-23T21:40:59.207Z},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-08-23T21:40:59.207Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.},\n bibtype = {article},\n author = {Yet, Barbaros and Constantinou, Anthony and Fenton, Norman and Neil, Martin and Luedeling, Eike and Shepherd, Keith},\n doi = {10.1016/j.eswa.2016.05.005},\n journal = {Expert Systems with Applications}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2015\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2015')\"\n      onkeypress=\"toggleGroup('group_2015')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2015</span>\n      <span class=\"bibbase_group_count\">\n        \n        (17)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event);\">\n    Evaluating acceptability of groundwater protection measures under different agricultural policies.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Giordano,  R.; D’Agostino,  D.; Apollonio,  C.; Scardigno,  A.; Pagano,  A.; Portoghese,  I.; Lamaddalena,  N.; Piccinni,  A., F.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Water Management</i>, 147: 54-66. 1 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluating acceptability of groundwater protection measures under different agricultural policies [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agwat.2014.07.023\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://doi.org/10.1016/j.agwat.2014.07.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\n pages = {54-66},\n volume = {147},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\n month = {1},\n id = {305c6eb9-3c9b-3b2d-a33e-c97dffec1133},\n created = {2015-04-11T15:16:23.000Z},\n accessed = {2015-01-27},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy&#x27;s effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\n bibtype = {article},\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\n doi = {10.1016/j.agwat.2014.07.023},\n journal = {Agricultural Water Management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event);\">\n    Evaluating acceptability of groundwater protection measures under different agricultural policies.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Giordano,  R.; D’Agostino,  D.; Apollonio,  C.; Scardigno,  A.; Pagano,  A.; Portoghese,  I.; Lamaddalena,  N.; Piccinni,  A., F.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Water Management</i>, 147: 54-66. 1 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluating acceptability of groundwater protection measures under different agricultural policies [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agwat.2014.07.023\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://doi.org/10.1016/j.agwat.2014.07.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\n pages = {54-66},\n volume = {147},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\n month = {1},\n id = {99b5d3a4-66ef-3453-83db-36352710606f},\n created = {2015-04-11T15:16:24.000Z},\n accessed = {2015-01-27},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy&#x27;s effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\n bibtype = {article},\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\n doi = {10.1016/j.agwat.2014.07.023},\n journal = {Agricultural Water Management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event);\">\n    Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hamilton,  S., H.; Pollino,  C., A.;  and Jakeman,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 299: 64-78. 3 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.12.004\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://doi.org/10.1016/j.ecolmodel.2014.12.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\n pages = {64-78},\n volume = {299},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\n month = {3},\n id = {c5616b49-da10-3235-865a-d74393655fca},\n created = {2015-04-11T15:30:36.000Z},\n accessed = {2015-01-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\n bibtype = {article},\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\n doi = {10.1016/j.ecolmodel.2014.12.004},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event);\">\n    Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hamilton,  S., H.; Pollino,  C., A.;  and Jakeman,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 299: 64-78. 3 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.12.004\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://doi.org/10.1016/j.ecolmodel.2014.12.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\n pages = {64-78},\n volume = {299},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\n month = {3},\n id = {b02b5d31-9b7f-3d35-a559-3c76e87b962e},\n created = {2015-04-11T15:45:45.000Z},\n accessed = {2015-01-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\n bibtype = {article},\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\n doi = {10.1016/j.ecolmodel.2014.12.004},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event);\">\n    Evaluating acceptability of groundwater protection measures under different agricultural policies.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Giordano,  R.; D’Agostino,  D.; Apollonio,  C.; Scardigno,  A.; Pagano,  A.; Portoghese,  I.; Lamaddalena,  N.; Piccinni,  A., F.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Water Management</i>, 147: 54-66. 1 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377414002224\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://www.sciencedirect.com/science/article/pii/S0378377414002224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluating acceptability of groundwater protection measures under different agricultural policies [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agwat.2014.07.023\"\n     onclick=\"log_download('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015', 'http://doi.org/10.1016/j.agwat.2014.07.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('giordano-dagostino-apollonio-scardigno-pagano-portoghese-lamaddalena-piccinni-etal-evaluatingacceptabilityofgroundwaterprotectionmeasuresunderdifferentagriculturalpolicies-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluating acceptability of groundwater protection measures under different agricultural policies},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief network,CAP reform,Conflict assessment,Groundwater protection policy,Policies interaction},\n pages = {54-66},\n volume = {147},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377414002224},\n month = {1},\n id = {811f579b-70c3-3d8f-99a4-0247f35ac0f5},\n created = {2015-04-11T17:37:59.000Z},\n accessed = {2015-01-27},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy&#x27;s effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.},\n bibtype = {article},\n author = {Giordano, Raffaele and D’Agostino, Daniela and Apollonio, Ciro and Scardigno, Alessandra and Pagano, Alessandro and Portoghese, Ivan and Lamaddalena, Nicola and Piccinni, Alberto F. and Vurro, Michele},\n doi = {10.1016/j.agwat.2014.07.023},\n journal = {Agricultural Water Management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Water resources management is often characterized by conflicts in many arid and semi-arid regions, where agriculture is the main user of groundwater (GW). Conflicts could arise among different decision-makers and stakeholders. Moreover, different policies can interact each other hampering or facilitating their implementation and effectiveness. This contribution describes a new implementation of GeSAP, an integrated modelling tool for enabling local GW management by combining the need for GW protection with socio-economic and behavioural determinants of GW use. GeSAP is based on the involvement of multiple stakeholders and the use of Bayesian Belief Networks (BBN) to simulate and explore their attitude relative to GW exploitation and their responses to the introduction of new protection and agricultural policies. In this work, GeSAP was implemented in the area of the Capitanata Irrigation Users Organization, located in the Apulia region (southern Italy). It was used to simulate the reactions of the main stakeholders involved in GW protection policy implementation and to assess the policy's effectiveness in terms of actual reduction of GW exploitation. Furthermore, the interactions between the GW protection policy and the coming reform of the Common Agricultural Policy (CAP) was investigated. The results of the application proved the capability of the GeSAP tool to assess the actual effectiveness of GW protection policy by investigating how far this policy could be considered acceptable by farmers. In addition, this study demonstrates how the effectiveness of the GW protection policy could be affected by the interaction with the CAP reform. The latter could strongly impact the balance between water demand and availability with the effect of nullifying the positive synergy between CAP and GW protection policy. Although water management issues are not explicitly mentioned among the main scopes of the CAP, this work clearly demonstrates the impact that such policy could have on farmers’ decisions on water use.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event);\">\n    Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hamilton,  S., H.; Pollino,  C., A.;  and Jakeman,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 299: 64-78. 3 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014006103\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://www.sciencedirect.com/science/article/pii/S0304380014006103', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.12.004\"\n     onclick=\"log_download('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015', 'http://doi.org/10.1016/j.ecolmodel.2014.12.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hamilton-pollino-jakeman-habitatsuitabilitymodellingofrarespeciesusingbayesiannetworksmodelevaluationunderlimiteddata-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data},\n type = {article},\n year = {2015},\n keywords = {Bayesian belief networks,Ecological modeling,Endangered species,Model validation,Uncertainty},\n pages = {64-78},\n volume = {299},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014006103},\n month = {3},\n id = {5ff020c8-12b9-33e0-b574-0d4c42063017},\n created = {2015-04-11T17:43:54.000Z},\n accessed = {2015-01-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.},\n bibtype = {article},\n author = {Hamilton, Serena H. and Pollino, Carmel A. and Jakeman, Anthony J.},\n doi = {10.1016/j.ecolmodel.2014.12.004},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Paucity of data on rare species is a common problem, preventing the use of most approaches to model development and evaluation. This study demonstrates how models can be developed and different forms of evaluation can be performed despite a lack of sufficient data, by presenting a habitat suitability model for the rare Astacopsis gouldi, the giant freshwater crayfish. We use a Bayesian network approach that readily incorporates incomplete data and allows for the evaluation of uncertainties. To supplement the limited field data on A. gouldi, expert knowledge was elicited through surveys designed to provide probability values that described the strength of relationships between the habitat suitability of the species and three variables – elevation, upstream riparian condition and geomorphic condition – and credible intervals around those values. A series of 18 alternative models were developed based on the same model structure but parameterised using different sources – expert judgement, field data or a combination of the two. The models were evaluated by estimating and comparing their performance accuracy and sensitivity analysis results, and in assessing the assumptions underpinning each of the models. Using performance accuracy as a measure, the data-based and combined expert- and data-based models performed better than the expert-based models. The sensitivity analysis results show that geomorphic condition was the most influential variable in the majority of models and that elevation had minimal influence on the occurrence of A. gouldi. Overall the models were found to have large predictive uncertainties, although the modelling process itself revealed insights into the habitat suitability of the species and identified key knowledge and data gaps for future monitoring, management and research.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214003776\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214003776', event);\">\n    Reducing the risk of house loss due to wildfires.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Penman,  T.; Nicholson,  A.; Bradstock,  R.; Collins,  L.; Penman,  S.;  and Price,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 67: 12-25. 5 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214003776\"\n     onclick=\"log_download('penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214003776', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Reducing the risk of house loss due to wildfires [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.12.020\"\n     onclick=\"log_download('penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015', 'http://doi.org/10.1016/j.envsoft.2014.12.020', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('penman-nicholson-bradstock-collins-penman-price-reducingtheriskofhouselossduetowildfires-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reducing the risk of house loss due to wildfires},\n type = {article},\n year = {2015},\n keywords = {Bayesian Network,Community engagement,Fire management,Planning,Suppression,Wildfire},\n pages = {12-25},\n volume = {67},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003776},\n month = {5},\n id = {dd85fb82-33ed-3112-9eaa-a0b2c1b5186e},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors.},\n bibtype = {article},\n author = {Penman, T.D. and Nicholson, A.E. and Bradstock, R.A. and Collins, L. and Penman, S.H. and Price, O.F.},\n doi = {10.1016/j.envsoft.2014.12.020},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214003764\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214003764', event);\">\n    Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lucena-Moya,  P.; Brawata,  R.; Kath,  J.; Harrison,  E.; ElSawah,  S.;  and Dyer,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 66: 36-45. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214003764\"\n     onclick=\"log_download('lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214003764', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.12.019\"\n     onclick=\"log_download('lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015', 'http://doi.org/10.1016/j.envsoft.2014.12.019', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lucenamoya-brawata-kath-harrison-elsawah-dyer-discretizationofcontinuouspredictorvariablesinbayesiannetworksanecologicalthresholdapproach-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Discretization of continuous predictor variables in Bayesian networks: An ecological threshold approach},\n type = {article},\n year = {2015},\n keywords = {Aquatic ecology,Bayesian networks,Discretization,Ecological community,Macroinvertebrates,TITAN,Thresholds},\n pages = {36-45},\n volume = {66},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214003764},\n month = {4},\n id = {e08492c9-2d60-3b06-bd97-9fccb755eef8},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-01-22},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The TITAN-based method may be used together with expert opinion.},\n bibtype = {article},\n author = {Lucena-Moya, Paloma and Brawata, Renee and Kath, Jarrod and Harrison, Evan and ElSawah, Sondoss and Dyer, Fiona},\n doi = {10.1016/j.envsoft.2014.12.019},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different approaches to the discretization of continuous predictor variables for the BN were compared. One approach used Threshold Indicator Taxa Analysis (TITAN) which estimates the thresholds based on the biological community. The other approach used was the expert opinion. The TITAN-based discretizations provided comparable predictions to expert opinion-based discretizations but in combining statistical rigor and ecological relevance, offer a novel and objective approach to the discretization. The TITAN-based method may be used together with expert opinion.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0921800914003711\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015', 'http://www.sciencedirect.com/science/article/pii/S0921800914003711', event);\">\n    Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  McVittie,  A.; Norton,  L.; Martin-Ortega,  J.; Siameti,  I.; Glenk,  K.;  and Aalders,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Economics</i>, 110: 15-27. 2 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0921800914003711\"\n     onclick=\"log_download('mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015', 'http://www.sciencedirect.com/science/article/pii/S0921800914003711', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolecon.2014.12.004\"\n     onclick=\"log_download('mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015', 'http://doi.org/10.1016/j.ecolecon.2014.12.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mcvittie-norton-martinortega-siameti-glenk-aalders-operationalizinganecosystemservicesbasedapproachusingbayesianbeliefnetworksanapplicationtoriparianbufferstrips-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips},\n type = {article},\n year = {2015},\n keywords = {Bayesian networks,Ecosystem services,Interdisciplinary research,Valuation},\n pages = {15-27},\n volume = {110},\n websites = {http://www.sciencedirect.com/science/article/pii/S0921800914003711},\n month = {2},\n id = {8062ddd5-b97f-32bd-9a5d-7de30cdc0186},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-01-21},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services from riparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context.},\n bibtype = {article},\n author = {McVittie, Alistair and Norton, Lisa and Martin-Ortega, Julia and Siameti, Ioanna and Glenk, Klaus and Aalders, Inge},\n doi = {10.1016/j.ecolecon.2014.12.004},\n journal = {Ecological Economics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services from riparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1574954114001563\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015', 'http://www.sciencedirect.com/science/article/pii/S1574954114001563', event);\">\n    Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fernandes,  J., A.; Irigoien,  X.; Lozano,  J., A.; Inza,  I.; Goikoetxea,  N.;  and Pérez,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Informatics</i>, 25: 35-42. 1 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1574954114001563\"\n     onclick=\"log_download('fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015', 'http://www.sciencedirect.com/science/article/pii/S1574954114001563', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoinf.2014.11.004\"\n     onclick=\"log_download('fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015', 'http://doi.org/10.1016/j.ecoinf.2014.11.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fernandes-irigoien-lozano-inza-goikoetxea-prez-evaluatingmachinelearningtechniquesforrecruitmentforecastingofsevennortheastatlanticfishspecies-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species},\n type = {article},\n year = {2015},\n keywords = {Bayesian networks,Fisheries management,Kernel density estimation,Pelagic fish,Recruitment forecasting,Supervised classification},\n pages = {35-42},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S1574954114001563},\n month = {1},\n id = {7a2bc8b9-dad4-3812-bab1-52f4f01aaf66},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.},\n bibtype = {article},\n author = {Fernandes, Jose A. and Irigoien, Xabier and Lozano, Jose A. and Inza, Iñaki and Goikoetxea, Nerea and Pérez, Aritz},\n doi = {10.1016/j.ecoinf.2014.11.004},\n journal = {Ecological Informatics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0264837715000824\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015', 'http://www.sciencedirect.com/science/article/pii/S0264837715000824', event);\">\n    A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gregorio,  N.; Herbohn,  J.; Harrison,  S.;  and Smith,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Land Use Policy</i>, 47: 29-41. 9 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0264837715000824\"\n     onclick=\"log_download('gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015', 'http://www.sciencedirect.com/science/article/pii/S0264837715000824', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.landusepol.2015.03.009\"\n     onclick=\"log_download('gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015', 'http://doi.org/10.1016/j.landusepol.2015.03.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gregorio-herbohn-harrison-smith-asystemsapproachtoimprovingthequalityoftreeseedlingsforagroforestrytreefarmingandreforestationinthephilippines-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A systems approach to improving the quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines},\n type = {article},\n year = {2015},\n keywords = {Bayesian network,Germplasm supply,Nursery accreditation,Nursery organisation},\n pages = {29-41},\n volume = {47},\n websites = {http://www.sciencedirect.com/science/article/pii/S0264837715000824},\n month = {9},\n id = {595f7fe3-90b0-35a3-98f2-c555ac0599e7},\n created = {2015-04-11T19:52:02.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The limited supply of high quality planting materials for a wide species base is a major reason for the limited success of reforestation programmes or projects in many developing countries. This paper reports the research that was undertaken to improve the supply of high quality planting materials for agroforestry, tree farming and reforestation in the Philippines. A systems approach was used to identify mechanisms to improve the operational effectiveness of the forest nursery sector. A Bayesian Belief Network of the forest nursery sector was developed to examine the interactions between the key components of the forest nursery sector, identify key leverage points for intervention and explore potential impacts of possible policy interventions. Although improving the operational effectiveness of individual, communal and government nurseries will result in high operational effectiveness of the forest nursery sector, the operational effectiveness of government nurseries is likely to have a negative impact on the market for seedlings from smallholder nurseries i.e. individual and communal nurseries, thus impeding the sustainability of smallholder nurseries. Increasing the supply of high quality germplasm for a wide variety of species, improving the technical capabilities of smallholder nursery operators in seedling production and increasing the market demand of high quality seedlings from smallholder nurseries are the most important requirements for improving the operational effectiveness of the forest nursery sector. However, government nurseries can play a crucial role in improving the effectiveness of the forest nursery sector by diversifying their production to focus on species that are in demand by smallholder farmers and which cannot be supplied by individual or communal nurseries. Failing to do this will result in the current situation continuing in which government nursery sector competes with private and communal nurseries.},\n bibtype = {article},\n author = {Gregorio, Nestor and Herbohn, John and Harrison, Steve and Smith, Carl},\n doi = {10.1016/j.landusepol.2015.03.009},\n journal = {Land Use Policy}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The limited supply of high quality planting materials for a wide species base is a major reason for the limited success of reforestation programmes or projects in many developing countries. This paper reports the research that was undertaken to improve the supply of high quality planting materials for agroforestry, tree farming and reforestation in the Philippines. A systems approach was used to identify mechanisms to improve the operational effectiveness of the forest nursery sector. A Bayesian Belief Network of the forest nursery sector was developed to examine the interactions between the key components of the forest nursery sector, identify key leverage points for intervention and explore potential impacts of possible policy interventions. Although improving the operational effectiveness of individual, communal and government nurseries will result in high operational effectiveness of the forest nursery sector, the operational effectiveness of government nurseries is likely to have a negative impact on the market for seedlings from smallholder nurseries i.e. individual and communal nurseries, thus impeding the sustainability of smallholder nurseries. Increasing the supply of high quality germplasm for a wide variety of species, improving the technical capabilities of smallholder nursery operators in seedling production and increasing the market demand of high quality seedlings from smallholder nurseries are the most important requirements for improving the operational effectiveness of the forest nursery sector. However, government nurseries can play a crucial role in improving the effectiveness of the forest nursery sector by diversifying their production to focus on species that are in demand by smallholder farmers and which cannot be supplied by individual or communal nurseries. Failing to do this will result in the current situation continuing in which government nursery sector competes with private and communal nurseries.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1750583615000262\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015', 'http://www.sciencedirect.com/science/article/pii/S1750583615000262', event);\">\n    Bi-directional risk assessment in carbon capture and storage with Bayesian Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gerstenberger,  M.; Christophersen,  A.; Buxton,  R.;  and Nicol,  A.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Greenhouse Gas Control</i>, 35: 150-159. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1750583615000262\"\n     onclick=\"log_download('gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015', 'http://www.sciencedirect.com/science/article/pii/S1750583615000262', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bi-directional risk assessment in carbon capture and storage with Bayesian Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ijggc.2015.01.010\"\n     onclick=\"log_download('gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015', 'http://doi.org/10.1016/j.ijggc.2015.01.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gerstenberger-christophersen-buxton-nicol-bidirectionalriskassessmentincarboncaptureandstoragewithbayesiannetworks-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bi-directional risk assessment in carbon capture and storage with Bayesian Networks},\n type = {article},\n year = {2015},\n keywords = {Bayesian Networks,CCS,Risk assessment},\n pages = {150-159},\n volume = {35},\n websites = {http://www.sciencedirect.com/science/article/pii/S1750583615000262},\n month = {4},\n id = {4e33b138-ca45-3429-8b20-cd35252bbabf},\n created = {2015-04-11T19:52:03.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The complex system required for carbon capture and storage (CCS) encompasses numerous sub-systems with inter-dependencies and large parameter uncertainties that propagate throughout the system. Exploring and understanding these inter-dependencies and uncertainties is invaluable for developing robust risk information. Bayesian Networks (BN), a decision support tool, are being increasingly used in the broader risk assessment community and show promise for use in CCS. BNs explore the dependencies and uncertainties within a system and have the potential to provide a better understanding of risk than more traditional tools such as logic trees or other less integrated approaches. Working with experts from within the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), we have developed a generic BN structure for the storage sub-system of CCS which can be used to guide the development of BNs for other CCS applications and for use in both diagnostic and predictive analysis. This bi-directionality provides one of the more important benefits of BNs; it allows for (1) traditional bottom-up risk assessment where the likely consequences based on the expected state of the system can be calculated and also (2) top-down, or outcome oriented risk, where the state of the system leading to a particular outcome, such as the likelihood of 2% leakage in 1000 years, is determined. This allows for a comprehensive sensitivity analysis which highlights important contributors to the risk and also where additional knowledge may benefit the project and reduce uncertainty. A robust expert elicitation procedure, for both the development of the network structure and the determination of event probabilities, is an integral part of the use of any such BN tool in CCS. Finally, we show the direct application of a smaller CCS BN by the CO2CRC.},\n bibtype = {article},\n author = {Gerstenberger, M.C. and Christophersen, A. and Buxton, R. and Nicol, A.},\n doi = {10.1016/j.ijggc.2015.01.010},\n journal = {International Journal of Greenhouse Gas Control}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The complex system required for carbon capture and storage (CCS) encompasses numerous sub-systems with inter-dependencies and large parameter uncertainties that propagate throughout the system. Exploring and understanding these inter-dependencies and uncertainties is invaluable for developing robust risk information. Bayesian Networks (BN), a decision support tool, are being increasingly used in the broader risk assessment community and show promise for use in CCS. BNs explore the dependencies and uncertainties within a system and have the potential to provide a better understanding of risk than more traditional tools such as logic trees or other less integrated approaches. Working with experts from within the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), we have developed a generic BN structure for the storage sub-system of CCS which can be used to guide the development of BNs for other CCS applications and for use in both diagnostic and predictive analysis. This bi-directionality provides one of the more important benefits of BNs; it allows for (1) traditional bottom-up risk assessment where the likely consequences based on the expected state of the system can be calculated and also (2) top-down, or outcome oriented risk, where the state of the system leading to a particular outcome, such as the likelihood of 2% leakage in 1000 years, is determined. This allows for a comprehensive sensitivity analysis which highlights important contributors to the risk and also where additional knowledge may benefit the project and reduce uncertainty. A robust expert elicitation procedure, for both the development of the network structure and the determination of event probabilities, is an integral part of the use of any such BN tool in CCS. Finally, we show the direct application of a smaller CCS BN by the CO2CRC.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214002606\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214002606', event);\">\n    A cross-validation package driving Netica with python.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fienen,  M., N.;  and Plant,  N., G.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 63: 14-23. 1 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214002606\"\n     onclick=\"log_download('fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015', 'http://www.sciencedirect.com/science/article/pii/S1364815214002606', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A cross-validation package driving Netica with python [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.09.007\"\n     onclick=\"log_download('fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015', 'http://doi.org/10.1016/j.envsoft.2014.09.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fienen-plant-acrossvalidationpackagedrivingneticawithpython-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A cross-validation package driving Netica with python},\n type = {article},\n year = {2015},\n keywords = {Bayesian networks,Cross-validation,Netica,Prediction,Probability,Python,Uncertainty},\n pages = {14-23},\n volume = {63},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002606},\n month = {1},\n id = {265f368a-fbca-3d7a-a9d5-ec0f95618aaa},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).},\n bibtype = {article},\n author = {Fienen, Michael N. and Plant, Nathaniel G.},\n doi = {10.1016/j.envsoft.2014.09.007},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0160412015000719\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015', 'http://www.sciencedirect.com/science/article/pii/S0160412015000719', event);\">\n    Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Beaudequin,  D.; Harden,  F.; Roiko,  A.; Stratton,  H.; Lemckert,  C.;  and Mengersen,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Environment international</i>, 80: 8-18. 3 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0160412015000719\"\n     onclick=\"log_download('beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015', 'http://www.sciencedirect.com/science/article/pii/S0160412015000719', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envint.2015.03.013\"\n     onclick=\"log_download('beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015', 'http://doi.org/10.1016/j.envint.2015.03.013', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('beaudequin-harden-roiko-stratton-lemckert-mengersen-beyondqmramodellingmicrobialhealthriskasacomplexsystemusingbayesiannetworks-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.},\n type = {article},\n year = {2015},\n keywords = {BN,Bayesian network,CFU,DAG,Directed Acyclic Graph,FIB,Health risk assessment,MC,MCMC,MPN,MPRM,Markov chain Monte Carlo,Microbial risk,Modelling,Monte Carlo,QMRA,Uncertainty,colony-forming unit,faecal indicator bacteria,modular process risk model,most probable number,quantitative microbial risk assessment},\n pages = {8-18},\n volume = {80},\n websites = {http://www.sciencedirect.com/science/article/pii/S0160412015000719},\n month = {3},\n day = {28},\n id = {f22a6dfb-58ab-3357-8b28-4075c62627b0},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {BACKGROUND: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.\n\nOBJECTIVES: This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.\n\nMETHODS: A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.\n\nDISCUSSION: The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.\n\nCONCLUSION: The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.},\n bibtype = {article},\n author = {Beaudequin, Denise and Harden, Fiona and Roiko, Anne and Stratton, Helen and Lemckert, Charles and Mengersen, Kerrie},\n doi = {10.1016/j.envint.2015.03.013},\n journal = {Environment international}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  BACKGROUND: Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.\n\nOBJECTIVES: This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.\n\nMETHODS: A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.\n\nDISCUSSION: The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.\n\nCONCLUSION: The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/B9780128000670000098\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015', 'http://www.sciencedirect.com/science/article/pii/B9780128000670000098', event);\">\n    Integrated Assessment of Scale Impacts of Watershed Intervention.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Merritt,  W.; Patch,  B.;  and Kumar Rout,  S.\n</span>\n\n  \n\n</span>\n\n  Elsevier,  2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/B9780128000670000098\"\n     onclick=\"log_download('merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015', 'http://www.sciencedirect.com/science/article/pii/B9780128000670000098', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Integrated Assessment of Scale Impacts of Watershed Intervention [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/B978-0-12-800067-0.00009-8\"\n     onclick=\"log_download('merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015', 'http://doi.org/10.1016/B978-0-12-800067-0.00009-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('merritt-patch-kumarrout-integratedassessmentofscaleimpactsofwatershedintervention-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@book{\n title = {Integrated Assessment of Scale Impacts of Watershed Intervention},\n type = {book},\n year = {2015},\n source = {Integrated Assessment of Scale Impacts of Watershed Intervention},\n keywords = {Bayesian network,capital strength,integrated modeling,livelihood capitals,resilience},\n pages = {287-316},\n websites = {http://www.sciencedirect.com/science/article/pii/B9780128000670000098},\n publisher = {Elsevier},\n id = {d58a843e-6613-33cb-9a3f-60fa7c81d68e},\n created = {2015-04-11T20:33:13.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.},\n bibtype = {book},\n author = {Merritt, Wendy and Patch, Brendan and Kumar Rout, Sanjit},\n doi = {10.1016/B978-0-12-800067-0.00009-8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479715300244\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015', 'http://www.sciencedirect.com/science/article/pii/S0301479715300244', event);\">\n    Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fu,  B.; Pollino,  C., A.; Cuddy,  S., M.;  and Andrews,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 157: 127-138. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479715300244\"\n     onclick=\"log_download('fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015', 'http://www.sciencedirect.com/science/article/pii/S0301479715300244', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2015.04.021\"\n     onclick=\"log_download('fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015', 'http://doi.org/10.1016/j.jenvman.2015.04.021', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fu-pollino-cuddy-andrews-assessingclimatechangeimpactsonwetlandsinaflowregulatedcatchmentacasestudyinthemacquariemarshesaustralia-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessing climate change impacts on wetlands in a flow regulated catchment: A case study in the Macquarie Marshes, Australia.},\n type = {article},\n year = {2015},\n keywords = {Climate change,Decision support system,Habitat condition,Ramsar wetland},\n pages = {127-138},\n volume = {157},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479715300244},\n month = {4},\n day = {17},\n id = {6ac1efdc-afed-397c-96c2-d95ddc982173},\n created = {2015-04-29T18:49:46.000Z},\n accessed = {2015-04-29},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for &#x27;natural&#x27; flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.},\n bibtype = {article},\n author = {Fu, Baihua and Pollino, Carmel A and Cuddy, Susan M and Andrews, Felix},\n doi = {10.1016/j.jenvman.2015.04.021},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"forio-landuyt-bennetsen-lock-nguyen-ambarita-musonge-boets-etal-bayesianbeliefnetworkmodelstoanalyseandpredictecologicalwaterqualityinrivers-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Bayesian belief network models to analyse and predict ecological water quality in rivers.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Forio,  M., A., E.; Landuyt,  D.; Bennetsen,  E.; Lock,  K.; Nguyen,  T., H., T.; Ambarita,  M., N., D.; Musonge,  P., L., S.; Boets,  P.; Everaert,  G.; Dominguez-Granda,  L.;  and Goethals,  P., L., M.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 312.  2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2015.05.025\"\n     onclick=\"log_download('forio-landuyt-bennetsen-lock-nguyen-ambarita-musonge-boets-etal-bayesianbeliefnetworkmodelstoanalyseandpredictecologicalwaterqualityinrivers-2015', 'http://doi.org/10.1016/j.ecolmodel.2015.05.025', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/forio-landuyt-bennetsen-lock-nguyen-ambarita-musonge-boets-etal-bayesianbeliefnetworkmodelstoanalyseandpredictecologicalwaterqualityinrivers-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('forio-landuyt-bennetsen-lock-nguyen-ambarita-musonge-boets-etal-bayesianbeliefnetworkmodelstoanalyseandpredictecologicalwaterqualityinrivers-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian belief network models to analyse and predict ecological water quality in rivers},\n type = {article},\n year = {2015},\n volume = {312},\n id = {30b72578-1e45-327e-9a12-23a0d68e9ace},\n created = {2017-08-23T21:38:25.174Z},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-08-23T21:38:25.174Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Economic growth is often based on the intensification of crop production, energy consumption and urbanization. In many cases, this leads to the degradation of aquatic ecosystems. Modelling water resources and the related identification of key drivers of change are essential to improve and protect water quality in river basins. This study evaluates the potential of Bayesian belief network models to predict the ecological water quality in a typical multifunctional and tropical river basin. Field data, expert knowledge and literature data were used to develop a set of Bayesian belief network models. The developed models were evaluated based on weighted Cohen&#x27;s Kappa (??&lt;inf&gt;w&lt;/inf&gt;), percentage of correctly classified instances (CCI) and spherical payoff. On top, a sensitivity analysis and practical simulation tests of the two most reliable models were performed. Cross-validation based on ??&lt;inf&gt;w&lt;/inf&gt; (Model 1: 0.44??0.08; Model 2: 0.44??0.11) and CCI (Model 1: 36.3??2.3; Model 2: 41.6??2.3) indicated that the performance was reliable and stable. Model 1 comprised of input variables main land use, elevation, sediment type, chlorophyll, flow velocity, dissolved oxygen, and chemical oxygen demand; whereas Model 2 did not include dissolved oxygen and chemical oxygen demand. Although the predictive performance of Model 2 was slightly higher than that of Model 1, simulation outcomes of Model 1 were more coherent. Additionally, more management options could be evaluated with Model 1. As the model&#x27;s ability to simulate management outcomes is of utmost importance in model selection, Model 1 is recommended as a tool to support decision-making in river management. Model predictions and sensitivity analysis indicated that flow velocity is the major variable determining ecological water quality and suggested that construction of additional dams and water abstraction within the basin would have an adverse effect on water quality. Although a case study in a single river basin is presented, the modelling approach can be of general use on any other river basin.},\n bibtype = {article},\n author = {Forio, Marie Anne Eurie and Landuyt, Dries and Bennetsen, Elina and Lock, Koen and Nguyen, Thi Hanh Tien and Ambarita, Minar Naomi Damanik and Musonge, Peace Liz Sasha and Boets, Pieter and Everaert, Gert and Dominguez-Granda, Luis and Goethals, Peter L M},\n doi = {10.1016/j.ecolmodel.2015.05.025},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Economic growth is often based on the intensification of crop production, energy consumption and urbanization. In many cases, this leads to the degradation of aquatic ecosystems. Modelling water resources and the related identification of key drivers of change are essential to improve and protect water quality in river basins. This study evaluates the potential of Bayesian belief network models to predict the ecological water quality in a typical multifunctional and tropical river basin. Field data, expert knowledge and literature data were used to develop a set of Bayesian belief network models. The developed models were evaluated based on weighted Cohen's Kappa (??<inf>w</inf>), percentage of correctly classified instances (CCI) and spherical payoff. On top, a sensitivity analysis and practical simulation tests of the two most reliable models were performed. Cross-validation based on ??<inf>w</inf> (Model 1: 0.44??0.08; Model 2: 0.44??0.11) and CCI (Model 1: 36.3??2.3; Model 2: 41.6??2.3) indicated that the performance was reliable and stable. Model 1 comprised of input variables main land use, elevation, sediment type, chlorophyll, flow velocity, dissolved oxygen, and chemical oxygen demand; whereas Model 2 did not include dissolved oxygen and chemical oxygen demand. Although the predictive performance of Model 2 was slightly higher than that of Model 1, simulation outcomes of Model 1 were more coherent. Additionally, more management options could be evaluated with Model 1. As the model's ability to simulate management outcomes is of utmost importance in model selection, Model 1 is recommended as a tool to support decision-making in river management. Model predictions and sensitivity analysis indicated that flow velocity is the major variable determining ecological water quality and suggested that construction of additional dams and water abstraction within the basin would have an adverse effect on water quality. Although a case study in a single river basin is presented, the modelling approach can be of general use on any other river basin.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2014\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2014')\"\n      onkeypress=\"toggleGroup('group_2014')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2014</span>\n      <span class=\"bibbase_group_count\">\n        \n        (23)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X14001265\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X14001265', event);\">\n    Using the integrated ecosystem assessment framework to build consensus and transfer information to managers.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fletcher,  P., J.; Kelble,  C., R.; Nuttle,  W., K.;  and Kiker,  G., A.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Indicators</i>, 44: 11-25. 9 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X14001265\"\n     onclick=\"log_download('fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X14001265', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using the integrated ecosystem assessment framework to build consensus and transfer information to managers [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolind.2014.03.024\"\n     onclick=\"log_download('fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014', 'http://doi.org/10.1016/j.ecolind.2014.03.024', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fletcher-kelble-nuttle-kiker-usingtheintegratedecosystemassessmentframeworktobuildconsensusandtransferinformationtomanagers-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using the integrated ecosystem assessment framework to build consensus and transfer information to managers},\n type = {article},\n year = {2014},\n keywords = {Bayesian Belief Networks,Conceptual ecological models,EBM-DPSER,Ecosystem-based management,Integrated ecosystem assessments,South Florida},\n pages = {11-25},\n volume = {44},\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X14001265},\n month = {9},\n id = {91133e08-bba3-37b8-abb3-99a57aca3fa1},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-03-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Ecosystem-based management is widely regarded as a method to improve the way we manage our coastal marine resources and ecosystems. Effective ecosystem-based management relies upon synthesizing our scientific knowledge and transferring this knowledge into management actions. Integrated ecosystem assessment is a framework to conduct this scientific synthesis and transfer information to resource managers. Portions of the framework were applied to build consensus on the focal ecosystem components and processes that are characteristic of a sustainable South Florida coastal ecosystem that is producing ecosystem services at the level society desires. Consensus was developed through facilitated meetings that aimed to conceptualize the ecosystem, develop ecosystem indicators, and conduct risk analysis. Resource managers, researchers, academics, and non-governmental organizations participated in these meetings and contributed to the synthesis of science and a myriad of science communications to transfer information to decision makers and the public. A proof of concept Bayesian Belief Network was developed to explore integrating the results of this assessment into an interactive management scenario evaluation tool. The four year effort resulted in the development of a research and management coordination network in South Florida that should provide the foundation for implementing ecosystem-based resource management across multiple agencies.},\n bibtype = {article},\n author = {Fletcher, Pamela J. and Kelble, Christopher R. and Nuttle, William K. and Kiker, Gregory A.},\n doi = {10.1016/j.ecolind.2014.03.024},\n journal = {Ecological Indicators}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Ecosystem-based management is widely regarded as a method to improve the way we manage our coastal marine resources and ecosystems. Effective ecosystem-based management relies upon synthesizing our scientific knowledge and transferring this knowledge into management actions. Integrated ecosystem assessment is a framework to conduct this scientific synthesis and transfer information to resource managers. Portions of the framework were applied to build consensus on the focal ecosystem components and processes that are characteristic of a sustainable South Florida coastal ecosystem that is producing ecosystem services at the level society desires. Consensus was developed through facilitated meetings that aimed to conceptualize the ecosystem, develop ecosystem indicators, and conduct risk analysis. Resource managers, researchers, academics, and non-governmental organizations participated in these meetings and contributed to the synthesis of science and a myriad of science communications to transfer information to decision makers and the public. A proof of concept Bayesian Belief Network was developed to explore integrating the results of this assessment into an interactive management scenario evaluation tool. The four year effort resulted in the development of a research and management coordination network in South Florida that should provide the foundation for implementing ecosystem-based resource management across multiple agencies.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308597X13002893\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014', 'http://www.sciencedirect.com/science/article/pii/S0308597X13002893', event);\">\n    Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gjelsvik Tiller,  R.; Mork,  J.; Richards,  R.; Eisenhauer,  L.; Liu,  Y.; Nakken,  J.;  and Borgersen,  Å.\n</span>\n\n  \n\n</span>\n\n  <i>Marine Policy</i>, 46: 72-83. 5 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308597X13002893\"\n     onclick=\"log_download('gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014', 'http://www.sciencedirect.com/science/article/pii/S0308597X13002893', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpol.2013.12.006\"\n     onclick=\"log_download('gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014', 'http://doi.org/10.1016/j.marpol.2013.12.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gjelsviktiller-mork-richards-eisenhauer-liu-nakken-borgersen-somethingfishyassessingstakeholderresiliencetoincreasingjellyfishperiphyllaperiphyllaintrondheimsfjordnorway-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Something fishy: Assessing stakeholder resilience to increasing jellyfish (Periphylla periphylla) in Trondheimsfjord, Norway},\n type = {article},\n year = {2014},\n keywords = {Bayesian Belief Networks,Coastal management,Hydrography,Jellyfish,Periphylla,Stakeholders},\n pages = {72-83},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S0308597X13002893},\n month = {5},\n id = {a11badc8-0e7a-3e78-8a55-673f7d1c98b4},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-04-01},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The following article outlines of an assessment of the adaptive capacity of stakeholder groups in the Trondheimsfjord region to the impacts related to local changes in Periphylla periphylla (jellyfish) concentrations. This paper addresses the interaction between the socio-ecological system and the marine ecosystem and the management challenges inherent therein by focusing on a serious management problem that is occurring in several Norwegian fjords. This is the recent superabundance of the lower trophic level jellyfish species P. periphylla, which competes with commercial Norwegian fish species for a wide variety of pelagic organisms including redfeed (Calanus finmarchicus), a key species in the coastal ecosystem and a particularly important food item for all codfishes in coastal waters. P. periphylla has, however, also some properties that might make it a valuable new resource in Norwegian waters, namely its potential for being a new and abundant source of collagen. The question addressed here is how to manage this jellyfish species in a manner that is rational from both socio-political and ecological perspectives, exploring stakeholder perceptions concerning their adaptation options and capacity to implement these options to this new resource and management mitigation options based on a set of stakeholder driven future scenarios.},\n bibtype = {article},\n author = {Gjelsvik Tiller, Rachel and Mork, Jarle and Richards, Russell and Eisenhauer, Lionel and Liu, Yajie and Nakken, Jens-Fredrik and Borgersen, Åshild.L},\n doi = {10.1016/j.marpol.2013.12.006},\n journal = {Marine Policy}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The following article outlines of an assessment of the adaptive capacity of stakeholder groups in the Trondheimsfjord region to the impacts related to local changes in Periphylla periphylla (jellyfish) concentrations. This paper addresses the interaction between the socio-ecological system and the marine ecosystem and the management challenges inherent therein by focusing on a serious management problem that is occurring in several Norwegian fjords. This is the recent superabundance of the lower trophic level jellyfish species P. periphylla, which competes with commercial Norwegian fish species for a wide variety of pelagic organisms including redfeed (Calanus finmarchicus), a key species in the coastal ecosystem and a particularly important food item for all codfishes in coastal waters. P. periphylla has, however, also some properties that might make it a valuable new resource in Norwegian waters, namely its potential for being a new and abundant source of collagen. The question addressed here is how to manage this jellyfish species in a manner that is rational from both socio-political and ecological perspectives, exploring stakeholder perceptions concerning their adaptation options and capacity to implement these options to this new resource and management mitigation options based on a set of stakeholder driven future scenarios.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S016920461400125X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014', 'http://www.sciencedirect.com/science/article/pii/S016920461400125X', event);\">\n    Green spaces in the direct living environment and social contacts of the aging population.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kemperman,  A.;  and Timmermans,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Landscape and Urban Planning</i>, 129: 44-54. 9 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S016920461400125X\"\n     onclick=\"log_download('kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014', 'http://www.sciencedirect.com/science/article/pii/S016920461400125X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Green spaces in the direct living environment and social contacts of the aging population [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.landurbplan.2014.05.003\"\n     onclick=\"log_download('kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014', 'http://doi.org/10.1016/j.landurbplan.2014.05.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kemperman-timmermans-greenspacesinthedirectlivingenvironmentandsocialcontactsoftheagingpopulation-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Green spaces in the direct living environment and social contacts of the aging population},\n type = {article},\n year = {2014},\n keywords = {Aging,Bayesian belief network,Green spaces,Living environment,Social contacts},\n pages = {44-54},\n volume = {129},\n websites = {http://www.sciencedirect.com/science/article/pii/S016920461400125X},\n month = {9},\n id = {f4ed9030-bc5b-34a8-bf10-1e2619ae784d},\n created = {2015-04-11T18:46:34.000Z},\n accessed = {2014-11-28},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Green spaces in the living environment may provide a meeting place and support social contacts. When people get older they, in general, are less mobile and have more limited activity spaces. At the same time they are faced with smaller social networks due to social and health related changes. Green spaces in their direct living environment are therefore important to support their needs. The aim of this study was to better understand the nature of the relationship between various types of green spaces in the direct living environment and the extent and nature of social contacts of the aging generation, taking into account socio-demographics and other physical and social environmental characteristics. Data for this study were obtained from a survey about living surroundings from a national representative sample of 1501 persons in the age category of 60 years and over in the Netherlands conducted in 2009. The survey included both subjective and objective measurements of the direct living environment of the respondents. Specifically, a Bayesian belief network was used to formulate and estimate the direct and indirect relationships between the selected variables. Results show that social contacts among neighbors are mainly influenced by the availability of trees and grass and the perceived level of green. Green spaces support social contacts in the neighborhood. However, the safety and maintenance of the green spaces are also important; high quality green spaces support social contacts between neighbors and strengthen communities for the aging population.},\n bibtype = {article},\n author = {Kemperman, Astrid and Timmermans, Harry},\n doi = {10.1016/j.landurbplan.2014.05.003},\n journal = {Landscape and Urban Planning}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Green spaces in the living environment may provide a meeting place and support social contacts. When people get older they, in general, are less mobile and have more limited activity spaces. At the same time they are faced with smaller social networks due to social and health related changes. Green spaces in their direct living environment are therefore important to support their needs. The aim of this study was to better understand the nature of the relationship between various types of green spaces in the direct living environment and the extent and nature of social contacts of the aging generation, taking into account socio-demographics and other physical and social environmental characteristics. Data for this study were obtained from a survey about living surroundings from a national representative sample of 1501 persons in the age category of 60 years and over in the Netherlands conducted in 2009. The survey included both subjective and objective measurements of the direct living environment of the respondents. Specifically, a Bayesian belief network was used to formulate and estimate the direct and indirect relationships between the selected variables. Results show that social contacts among neighbors are mainly influenced by the availability of trees and grass and the perceived level of green. Green spaces support social contacts in the neighborhood. However, the safety and maintenance of the green spaces are also important; high quality green spaces support social contacts between neighbors and strengthen communities for the aging population.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X14002148\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014', 'http://www.sciencedirect.com/science/article/pii/S0025326X14002148', event);\">\n    A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nojavan A,  F.; Qian,  S., S.; Paerl,  H., W.; Reckhow,  K., H.;  and Albright,  E., A.\n</span>\n\n  \n\n</span>\n\n  <i>Marine pollution bulletin</i>, 83(1): 107-15. 6 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X14002148\"\n     onclick=\"log_download('nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014', 'http://www.sciencedirect.com/science/article/pii/S0025326X14002148', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpolbul.2014.04.011\"\n     onclick=\"log_download('nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014', 'http://doi.org/10.1016/j.marpolbul.2014.04.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nojavana-qian-paerl-reckhow-albright-astudyofanthropogenicandclimaticdisturbanceofthenewriverestuaryusingabayesianbeliefnetwork-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.},\n type = {article},\n year = {2014},\n keywords = {Bayes Theorem,Climate,Climate Change,Ecosystem,Estuaries,Eutrophication,Models, Theoretical,North Carolina,Water Quality},\n pages = {107-15},\n volume = {83},\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X14002148},\n month = {6},\n day = {15},\n id = {6210ae43-abaf-357b-9e72-dc054e812bcb},\n created = {2015-04-11T18:56:31.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions.},\n bibtype = {article},\n author = {Nojavan A, Farnaz and Qian, Song S and Paerl, Hans W and Reckhow, Kenneth H and Albright, Elizabeth A},\n doi = {10.1016/j.marpolbul.2014.04.011},\n journal = {Marine pollution bulletin},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0959378014000843\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014', 'http://www.sciencedirect.com/science/article/pii/S0959378014000843', event);\">\n    Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ban,  S., S.; Pressey,  R., L.;  and Graham,  N., A.\n</span>\n\n  \n\n</span>\n\n  <i>Global Environmental Change</i>, 27: 64-72. 7 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0959378014000843\"\n     onclick=\"log_download('ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014', 'http://www.sciencedirect.com/science/article/pii/S0959378014000843', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.gloenvcha.2014.04.018\"\n     onclick=\"log_download('ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014', 'http://doi.org/10.1016/j.gloenvcha.2014.04.018', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ban-pressey-graham-assessinginteractionsofmultiplestressorswhendataarelimitedabayesianbeliefnetworkappliedtocoralreefs-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessing interactions of multiple stressors when data are limited: A Bayesian belief network applied to coral reefs},\n type = {article},\n year = {2014},\n keywords = {Bayesian belief network,Climate change,Conservation planning,Coral reef,Expert elicitation,Risk assessment},\n pages = {64-72},\n volume = {27},\n websites = {http://www.sciencedirect.com/science/article/pii/S0959378014000843},\n month = {7},\n id = {e6a03683-84ae-3be6-807c-9dfc0103c216},\n created = {2015-04-11T19:07:35.000Z},\n accessed = {2015-01-15},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian belief networks are finding increasing application in adaptive ecosystem management where data are limited and uncertainty is high. The combined effect of multiple stressors is one area where considerable uncertainty exists. Our study area, the Great Barrier Reef is simultaneously data-rich – concerning the physical and biological environment – and data-poor – concerning the effects of interacting stressors. We used a formal expert-elicitation process to obtain estimates of outcomes associated with a variety of scenarios that combined stressors both within and outside the control of local managers. There was much stronger consensus about certain stressor effects – such as between temperature anomalies and bleaching – than others, such as the relationship between water quality and coral cover. In general, the expert outlook for the Great Barrier Reef is pessimistic, with the potential for climate change effects potentially to overshadow the effects of local management actions.},\n bibtype = {article},\n author = {Ban, Stephen S. and Pressey, Robert L. and Graham, Nicholas A.J.},\n doi = {10.1016/j.gloenvcha.2014.04.018},\n journal = {Global Environmental Change}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian belief networks are finding increasing application in adaptive ecosystem management where data are limited and uncertainty is high. The combined effect of multiple stressors is one area where considerable uncertainty exists. Our study area, the Great Barrier Reef is simultaneously data-rich – concerning the physical and biological environment – and data-poor – concerning the effects of interacting stressors. We used a formal expert-elicitation process to obtain estimates of outcomes associated with a variety of scenarios that combined stressors both within and outside the control of local managers. There was much stronger consensus about certain stressor effects – such as between temperature anomalies and bleaching – than others, such as the relationship between water quality and coral cover. In general, the expert outlook for the Great Barrier Reef is pessimistic, with the potential for climate change effects potentially to overshadow the effects of local management actions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0264837713001555\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014', 'http://www.sciencedirect.com/science/article/pii/S0264837713001555', event);\">\n    Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Frayer,  J.; Sun,  Z.; Müller,  D.; Munroe,  D., K.;  and Xu,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Land Use Policy</i>, 36: 248-258. 1 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0264837713001555\"\n     onclick=\"log_download('frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014', 'http://www.sciencedirect.com/science/article/pii/S0264837713001555', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.landusepol.2013.08.005\"\n     onclick=\"log_download('frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014', 'http://doi.org/10.1016/j.landusepol.2013.08.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('frayer-sun-mller-munroe-xu-analyzingthedriversoftreeplantinginyunnanchinawithbayesiannetworks-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks},\n type = {article},\n year = {2014},\n keywords = {Afforestation,Bayesian belief network,China,Forest transition,Land use change,SLCP},\n pages = {248-258},\n volume = {36},\n websites = {http://www.sciencedirect.com/science/article/pii/S0264837713001555},\n month = {1},\n id = {952422ca-1136-3fed-b247-7519a9b7cd81},\n created = {2015-04-11T19:07:36.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Strict enforcement of forest protection and massive afforestation campaigns have contributed to a significant increase in China&#x27;s forest cover during the last 20 years. At the same time, demographic changes in rural areas due to changes in reproduction patterns and the emigration of younger population segments have affected land-use strategies. We identified proximate causes and underlying drivers that influence the decisions of farm households to plant trees on former cropland with Bayesian networks (BNs). BNs allow the incorporation of causal relationships in data analysis and can combine qualitative stakeholder knowledge with quantitative data. We defined the structure of the network with expert knowledge and in-depth discussions with land users. The network was calibrated and validated with data from a survey of 509 rural households in two upland areas of Yunnan Province in Southwest China. The results substantiate the influence of land endowments, labor availability and forest policies for switching from cropland to tree planting. State forest policies have constituted the main underlying driver to the forest transition in the past, but private afforestation activities increasingly dominate the expansion of tree cover. Farmers plant trees on private incentives mainly to cash in on the improved economic opportunities provided by tree crops, but tree planting also constitutes an important strategy to adjust to growing labor scarcities.},\n bibtype = {article},\n author = {Frayer, Jens and Sun, Zhanli and Müller, Daniel and Munroe, Darla K. and Xu, Jianchu},\n doi = {10.1016/j.landusepol.2013.08.005},\n journal = {Land Use Policy}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Strict enforcement of forest protection and massive afforestation campaigns have contributed to a significant increase in China's forest cover during the last 20 years. At the same time, demographic changes in rural areas due to changes in reproduction patterns and the emigration of younger population segments have affected land-use strategies. We identified proximate causes and underlying drivers that influence the decisions of farm households to plant trees on former cropland with Bayesian networks (BNs). BNs allow the incorporation of causal relationships in data analysis and can combine qualitative stakeholder knowledge with quantitative data. We defined the structure of the network with expert knowledge and in-depth discussions with land users. The network was calibrated and validated with data from a survey of 509 rural households in two upland areas of Yunnan Province in Southwest China. The results substantiate the influence of land endowments, labor availability and forest policies for switching from cropland to tree planting. State forest policies have constituted the main underlying driver to the forest transition in the past, but private afforestation activities increasingly dominate the expansion of tree cover. Farmers plant trees on private incentives mainly to cash in on the improved economic opportunities provided by tree crops, but tree planting also constitutes an important strategy to adjust to growing labor scarcities.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214000619\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214000619', event);\">\n    A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Cha,  Y.;  and Stow,  C., A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 57: 90-100. 7 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214000619\"\n     onclick=\"log_download('cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214000619', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.02.010\"\n     onclick=\"log_download('cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014', 'http://doi.org/10.1016/j.envsoft.2014.02.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('cha-stow-abayesiannetworkincorporatingobservationerrortopredictphosphorusandchlorophyllainsaginawbay-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay},\n type = {article},\n year = {2014},\n keywords = {Bayesian hierarchical modeling,Bayesian network,Dreissenid invasion,Observation error,Phosphorus targets,Saginaw Bay,Water quality criteria},\n pages = {90-100},\n volume = {57},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214000619},\n month = {7},\n id = {ec29901c-feb6-3c2b-acdb-e93991455248},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-02-18},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.},\n bibtype = {article},\n author = {Cha, YoonKyung and Stow, Craig A.},\n doi = {10.1016/j.envsoft.2014.02.010},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213002570\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815213002570', event);\">\n    Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Celio,  E.; Koellner,  T.;  and Grêt-Regamey,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 52: 222-233. 2 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213002570\"\n     onclick=\"log_download('celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815213002570', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.10.014\"\n     onclick=\"log_download('celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014', 'http://doi.org/10.1016/j.envsoft.2013.10.014', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('celio-koellner-grtregamey-modelinglandusedecisionswithbayesiannetworksspatiallyexplicitanalysisofdrivingforcesonlandusechange-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change},\n type = {article},\n year = {2014},\n keywords = {Bayesian networks,Land use decisions,Land use modeling,Participatory modeling},\n pages = {222-233},\n volume = {52},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002570},\n month = {2},\n id = {49e939ec-75cf-3c6b-a23e-c8bfb76b0ac8},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-02-23},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors&#x27; knowledge into a spatially explicit BN. A structured experts&#x27; process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors&#x27; characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.},\n bibtype = {article},\n author = {Celio, Enrico and Koellner, Thomas and Grêt-Regamey, Adrienne},\n doi = {10.1016/j.envsoft.2013.10.014},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors' knowledge into a spatially explicit BN. A structured experts' process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors' characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014003056\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014', 'http://www.sciencedirect.com/science/article/pii/S0304380014003056', event);\">\n    Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  \n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 291: 42-57. 11 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014003056\"\n     onclick=\"log_download('developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014', 'http://www.sciencedirect.com/science/article/pii/S0304380014003056', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.06.023\"\n     onclick=\"log_download('developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014', 'http://doi.org/10.1016/j.ecolmodel.2014.06.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('developmentofastakeholderdrivenspatialmodelingframeworkforstrategiclandscapeplanningusingbayesiannetworksacrosstwourbanruralgradientsinmaineusa-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA},\n type = {article},\n year = {2014},\n keywords = {Bayesian networks,Conservation,Land use planning,Land use suitability,Natural resource management,Stakeholder engagement},\n pages = {42-57},\n volume = {291},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014003056},\n month = {11},\n id = {8adb7754-2183-324d-8933-8e5102931288},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-01-27},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, USA, we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socio-economic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30m×30m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.},\n bibtype = {article},\n author = {},\n doi = {10.1016/j.ecolmodel.2014.06.023},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, USA, we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socio-economic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30m×30m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014000398\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'http://www.sciencedirect.com/science/article/pii/S0304380014000398', event);\">\n    A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gieder,  K., D.; Karpanty,  S., M.; Fraser,  J., D.; Catlin,  D., H.; Gutierrez,  B., T.; Plant,  N., G.; Turecek,  A., M.;  and Robert Thieler,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 276: 38-50. 3 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380014000398\"\n     onclick=\"log_download('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'http://www.sciencedirect.com/science/article/pii/S0304380014000398', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.01.005\"\n     onclick=\"log_download('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'http://doi.org/10.1016/j.ecolmodel.2014.01.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},\n pages = {38-50},\n volume = {276},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380014000398},\n month = {3},\n id = {7ae94537-1682-30b1-b604-7af959748642},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modeling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model&#x27;s dataset. We found that model predictions were more successful when the ranges of physical conditions included in model development were varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modeling impacts of sea-level rise or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.},\n bibtype = {article},\n author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},\n doi = {10.1016/j.ecolmodel.2014.01.005},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modeling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model's dataset. We found that model predictions were more successful when the ranges of physical conditions included in model development were varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modeling impacts of sea-level rise or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X13001568', event);\">\n    EBI: An index for delivery of ecosystem service bundles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Van der Biest,  K.; D’Hondt,  R.; Jacobs,  S.; Landuyt,  D.; Staes,  J.; Goethals,  P.;  and Meire,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Indicators</i>, 37: 252-265. 2 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"\n     onclick=\"log_download('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X13001568', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"EBI: An index for delivery of ecosystem service bundles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolind.2013.04.006\"\n     onclick=\"log_download('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://doi.org/10.1016/j.ecolind.2013.04.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {EBI: An index for delivery of ecosystem service bundles},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},\n pages = {252-265},\n volume = {37},\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},\n month = {2},\n id = {4950ea88-8fbd-3696-874a-efb0cce29b0c},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-02-04},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},\n bibtype = {article},\n author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},\n doi = {10.1016/j.ecolind.2013.04.006},\n journal = {Ecological Indicators}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X13007595\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014', 'http://www.sciencedirect.com/science/article/pii/S0025326X13007595', event);\">\n    A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Goerlandt,  F.;  and Montewka,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Marine pollution bulletin</i>, 79(1-2): 130-44. 2 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X13007595\"\n     onclick=\"log_download('goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014', 'http://www.sciencedirect.com/science/article/pii/S0025326X13007595', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpolbul.2013.12.026\"\n     onclick=\"log_download('goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014', 'http://doi.org/10.1016/j.marpolbul.2013.12.026', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('goerlandt-montewka-aprobabilisticmodelforaccidentalcargooiloutflowfromproducttankersinashipshipcollision-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision.},\n type = {article},\n year = {2014},\n keywords = {Accidents,Accidents: statistics &amp; numerical data,Environment,Models, Chemical,Models, Statistical,Petroleum,Petroleum Pollution,Petroleum Pollution: statistics &amp; numerical data,Risk Assessment,Ships,Ships: statistics &amp; numerical data,Water Pollution, Chemical,Water Pollution, Chemical: statistics &amp; numerical},\n pages = {130-44},\n volume = {79},\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13007595},\n month = {2},\n day = {15},\n id = {44afabf0-e88c-34f0-9569-aaf076fb3d2c},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.},\n bibtype = {article},\n author = {Goerlandt, Floris and Montewka, Jakub},\n doi = {10.1016/j.marpolbul.2013.12.026},\n journal = {Marine pollution bulletin},\n number = {1-2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0303243414001251\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014', 'http://www.sciencedirect.com/science/article/pii/S0303243414001251', event);\">\n    Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mukashema,  A.; Veldkamp,  A.;  and Vrieling,  A.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Applied Earth Observation and Geoinformation</i>, 33: 331-340. 12 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0303243414001251\"\n     onclick=\"log_download('mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014', 'http://www.sciencedirect.com/science/article/pii/S0303243414001251', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jag.2014.05.005\"\n     onclick=\"log_download('mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014', 'http://doi.org/10.1016/j.jag.2014.05.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mukashema-veldkamp-vrieling-automatedhighresolutionmappingofcoffeeinrwandausinganexpertbayesiannetwork-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Coffee,Expert knowledge,Remote sensing,Rwanda,Very high resolution imagery},\n pages = {331-340},\n volume = {33},\n websites = {http://www.sciencedirect.com/science/article/pii/S0303243414001251},\n month = {12},\n id = {792bc970-bcee-3e78-bee7-7361ff38848e},\n created = {2015-04-11T19:52:03.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2=0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.},\n bibtype = {article},\n author = {Mukashema, A. and Veldkamp, A. and Vrieling, A.},\n doi = {10.1016/j.jag.2014.05.005},\n journal = {International Journal of Applied Earth Observation and Geoinformation}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  African highland agro-ecosystems are dominated by small-scale agricultural fields that often contain a mix of annual and perennial crops. This makes such systems difficult to map by remote sensing. We developed an expert Bayesian network model to extract the small-scale coffee fields of Rwanda from very high resolution data. The model was subsequently applied to aerial orthophotos covering more than 99% of Rwanda and on one QuickBird image for the remaining part. The method consists of a stepwise adjustment of pixel probabilities, which incorporates expert knowledge on size of coffee trees and fields, and on their location. The initial naive Bayesian network, which is a spectral-based classification, yielded a coffee map with an overall accuracy of around 50%. This confirms that standard spectral variables alone cannot accurately identify coffee fields from high resolution images. The combination of spectral and ancillary data (DEM and a forest map) allowed mapping of coffee fields and associated uncertainties with an overall accuracy of 87%. Aggregated to district units, the mapped coffee areas demonstrated a high correlation with the coffee areas reported in the detailed national coffee census of 2009 (R2=0.92). Unlike the census data our map provides high spatial resolution of coffee area patterns of Rwanda. The proposed method has potential for mapping other perennial small scale cropping systems in the East African Highlands and elsewhere.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S2212096314000023\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014', 'http://www.sciencedirect.com/science/article/pii/S2212096314000023', event);\">\n    Assessing pricing assumptions for weather index insurance in a changing climate.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Daron,  J.;  and Stainforth,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Climate Risk Management</i>, 1: 76-91.  2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S2212096314000023\"\n     onclick=\"log_download('daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014', 'http://www.sciencedirect.com/science/article/pii/S2212096314000023', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing pricing assumptions for weather index insurance in a changing climate [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.crm.2014.01.001\"\n     onclick=\"log_download('daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014', 'http://doi.org/10.1016/j.crm.2014.01.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('daron-stainforth-assessingpricingassumptionsforweatherindexinsuranceinachangingclimate-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessing pricing assumptions for weather index insurance in a changing climate},\n type = {article},\n year = {2014},\n keywords = {Adaptation,Bayesian Networks,Climate modeling,India,Uncertainty},\n pages = {76-91},\n volume = {1},\n websites = {http://www.sciencedirect.com/science/article/pii/S2212096314000023},\n id = {10344d5f-c88c-3aaf-869a-863ec53e1c06},\n created = {2015-04-11T19:52:11.000Z},\n accessed = {2015-03-17},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not these products are themselves resilient to climate change has not been well studied. Given climate variability and climate change, an over-reliance on historical climate observations to guide the design of such products can result in premiums which mislead policyholders and insurers alike, about the magnitude of underlying risks. Here, a method to incorporate different sources of climate data into the product design phase is presented. Bayesian Networks are constructed to demonstrate how insurers can assess the product viability from a climate perspective, using past observations and simulations of future climate. Sensitivity analyses illustrate the dependence of pricing decisions on both the choice of information, and the method for incorporating such data. The methods and their sensitivities are illustrated using a case study analysing the provision of index-based crop insurance in Kolhapur, India. We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data.},\n bibtype = {article},\n author = {Daron, J.D. and Stainforth, D.A.},\n doi = {10.1016/j.crm.2014.01.001},\n journal = {Climate Risk Management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not these products are themselves resilient to climate change has not been well studied. Given climate variability and climate change, an over-reliance on historical climate observations to guide the design of such products can result in premiums which mislead policyholders and insurers alike, about the magnitude of underlying risks. Here, a method to incorporate different sources of climate data into the product design phase is presented. Bayesian Networks are constructed to demonstrate how insurers can assess the product viability from a climate perspective, using past observations and simulations of future climate. Sensitivity analyses illustrate the dependence of pricing decisions on both the choice of information, and the method for incorporating such data. The methods and their sensitivities are illustrated using a case study analysing the provision of index-based crop insurance in Kolhapur, India. We expose the benefits and limitations of the Bayesian Network approach, weather index insurance as an adaptation measure and climate simulations as a source of quantitative predictive information. Current climate model output is shown to be of limited value and difficult to use by index insurance practitioners. The method presented, however, is shown to be an effective tool for testing pricing assumptions and could feasibly be employed in the future to incorporate multiple sources of climate data.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713007548\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014', 'http://www.sciencedirect.com/science/article/pii/S0301479713007548', event);\">\n    Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Buys,  L.; Mengersen,  K.; Johnson,  S.; van Buuren,  N.;  and Chauvin,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 133: 184-92. 1 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713007548\"\n     onclick=\"log_download('buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014', 'http://www.sciencedirect.com/science/article/pii/S0301479713007548', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2013.12.013\"\n     onclick=\"log_download('buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014', 'http://doi.org/10.1016/j.jenvman.2013.12.013', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('buys-mengersen-johnson-vanbuuren-chauvin-creatingasustainabilityscorecardasapredictivetoolformeasuringthecomplexsocialeconomicandenvironmentalimpactsofindustriesacasestudyassessingtheviabilityandsustainabilityofthedairyindustry-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.},\n type = {article},\n year = {2014},\n keywords = {Bayes Theorem,Dairying,Environment,Industry},\n pages = {184-92},\n volume = {133},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713007548},\n month = {1},\n day = {15},\n id = {e81c4063-dfc3-35dc-b60b-a148baecaf10},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-02-28},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.},\n bibtype = {article},\n author = {Buys, L and Mengersen, K and Johnson, S and van Buuren, N and Chauvin, A},\n doi = {10.1016/j.jenvman.2013.12.013},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521400067X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014', 'http://www.sciencedirect.com/science/article/pii/S136481521400067X', event);\">\n    Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ropero,  R.; Aguilera,  P.; Fernández,  A.;  and Rumí,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 57: 127-137. 7 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521400067X\"\n     onclick=\"log_download('ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014', 'http://www.sciencedirect.com/science/article/pii/S136481521400067X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.02.016\"\n     onclick=\"log_download('ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014', 'http://doi.org/10.1016/j.envsoft.2014.02.016', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ropero-aguilera-fernndez-rum-regressionusinghybridbayesiannetworksmodellinglandscapesocioeconomyrelationships-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Regression using hybrid Bayesian networks: Modelling landscape–socioeconomy relationships},\n type = {article},\n year = {2014},\n keywords = {Continuous Bayesian networks,Landscape,Mixtures of truncated exponentials,Regression,Socioeconomic structure},\n pages = {127-137},\n volume = {57},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521400067X},\n month = {7},\n id = {b8a790cb-d7e6-3755-a346-7ee7d5969aed},\n created = {2015-04-11T19:52:26.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape–socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling.},\n bibtype = {article},\n author = {Ropero, R.F. and Aguilera, P.A. and Fernández, A. and Rumí, R.},\n doi = {10.1016/j.envsoft.2014.02.016},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape–socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214002096\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214002096', event);\">\n    Modelling uncertainty in social–natural interactions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ropero,  R.; Rumí,  R.;  and Aguilera,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>. 8 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214002096\"\n     onclick=\"log_download('ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214002096', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling uncertainty in social–natural interactions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.07.008\"\n     onclick=\"log_download('ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014', 'http://doi.org/10.1016/j.envsoft.2014.07.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ropero-rum-aguilera-modellinguncertaintyinsocialnaturalinteractions-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling uncertainty in social–natural interactions},\n type = {article},\n year = {2014},\n keywords = {Hybrid Bayesian networks,Mixtures of truncated exponentials,Socio-ecological system,Systemic change,Water flows},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214002096},\n month = {8},\n id = {a3a3542a-81ec-34e9-8a4a-84bd654a598e},\n created = {2015-04-11T19:52:26.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Socio-ecological systems can be represented as a complex network of causal interactions. Modelling such systems requires methodologies that are able to take uncertainty into account. Due to their probabilistic nature, Bayesian networks are a powerful tool for representing complex systems where interactions between variables are subject to uncertainty. In this paper, we study the interactions between social and natural subsystems (land use and water flow components) using hybrid Bayesian networks based on the Mixture of Truncated Exponentials model. This study aims to provide a new methodology to model systemic change in a socio-ecological context. Two endogenous changes – agricultural intensification and the maintenance of traditional cropland – are proposed. Intensification of the agricultural practices leads to a rise in the rate of immigration to the area, as well as to greater water losses through evaporation. By contrast, maintenance of traditional cropland hardly changes the social structure, while increasing evapotranspiration rates and improving the control over runoff water. These results indicate that hybrid Bayesian networks are an excellent tool for modelling social–natural interactions.},\n bibtype = {article},\n author = {Ropero, R.F. and Rumí, R. and Aguilera, P.A.},\n doi = {10.1016/j.envsoft.2014.07.008},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Socio-ecological systems can be represented as a complex network of causal interactions. Modelling such systems requires methodologies that are able to take uncertainty into account. Due to their probabilistic nature, Bayesian networks are a powerful tool for representing complex systems where interactions between variables are subject to uncertainty. In this paper, we study the interactions between social and natural subsystems (land use and water flow components) using hybrid Bayesian networks based on the Mixture of Truncated Exponentials model. This study aims to provide a new methodology to model systemic change in a socio-ecological context. Two endogenous changes – agricultural intensification and the maintenance of traditional cropland – are proposed. Intensification of the agricultural practices leads to a rise in the rate of immigration to the area, as well as to greater water losses through evaporation. By contrast, maintenance of traditional cropland hardly changes the social structure, while increasing evapotranspiration rates and improving the control over runoff water. These results indicate that hybrid Bayesian networks are an excellent tool for modelling social–natural interactions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214001960\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214001960', event);\">\n    A software system for assessing the spatially distributed ecological risk posed by oil shipping.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jolma,  A.; Lehikoinen,  A.; Helle,  I.;  and Venesjärvi,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 61: 1-11. 11 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815214001960\"\n     onclick=\"log_download('jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815214001960', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A software system for assessing the spatially distributed ecological risk posed by oil shipping [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.06.023\"\n     onclick=\"log_download('jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014', 'http://doi.org/10.1016/j.envsoft.2014.06.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jolma-lehikoinen-helle-venesjrvi-asoftwaresystemforassessingthespatiallydistributedecologicalriskposedbyoilshipping-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A software system for assessing the spatially distributed ecological risk posed by oil shipping},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Ecology,Geospatial,Maritime accident,Oil spill,Risk assessment},\n pages = {1-11},\n volume = {61},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815214001960},\n month = {11},\n id = {d406037b-5ccb-3e43-a5f1-b36a6c7c77d5},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.},\n bibtype = {article},\n author = {Jolma, A. and Lehikoinen, A. and Helle, I. and Venesjärvi, R.},\n doi = {10.1016/j.envsoft.2014.06.023},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213002326\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815213002326', event);\">\n    Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Penman,  T.; Bradstock,  R.;  and Price,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 52: 166-175. 2 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213002326\"\n     onclick=\"log_download('penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014', 'http://www.sciencedirect.com/science/article/pii/S1364815213002326', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.09.030\"\n     onclick=\"log_download('penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014', 'http://doi.org/10.1016/j.envsoft.2013.09.030', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('penman-bradstock-price-reducingwildfirerisktourbandevelopmentssimulationofcosteffectivefueltreatmentsolutionsinsoutheasternaustralia-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reducing wildfire risk to urban developments: Simulation of cost-effective fuel treatment solutions in south eastern Australia},\n type = {article},\n year = {2014},\n keywords = {BN,BUIZ,Bayesian Network,Bushland Urban Interface Zone,Fire management,Interface,PB,Prescribed Burning,Prescribed fire},\n pages = {166-175},\n volume = {52},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213002326},\n month = {2},\n id = {5c2294fe-7c00-3d21-b487-245ae333d282},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Wildfires can result in significant economic and social losses. Prescribed fire is commonly applied to reduce fuel loads and thereby decrease future fire risk to life and property. Fuel treatments can occur in the landscape or adjacent to houses. Location of the prescribed burns can significantly alter the risk of house loss. Furthermore the cost of treating fuels in the landscape is far cheaper than treating fuels adjacent to the houses. Here we develop a Bayesian Network to examine the relative reduction in risk that can be achieved by prescribed burning in the landscape compared with a 500 m interface zone adjacent to houses. We then compare costs of management treatments to determine the most cost-effective method of reducing risk to houses. Burning in the interface zone resulted in the greatest reduction in risk of fires reaching the houses and the intensity of these fires. Fuel treatment in the interface zone allows for a direct transfer of benefits from the fuel treatment. Costs of treating fuels in the interface were significantly higher on a per hectare basis, but the extent of area requiring treatment was considerably lower. Results of this study demonstrate that treatment of fuels at the interface is not only the best means of reducing risk, it is also the most cost-effective.},\n bibtype = {article},\n author = {Penman, T.D. and Bradstock, R.A. and Price, O.F.},\n doi = {10.1016/j.envsoft.2013.09.030},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wildfires can result in significant economic and social losses. Prescribed fire is commonly applied to reduce fuel loads and thereby decrease future fire risk to life and property. Fuel treatments can occur in the landscape or adjacent to houses. Location of the prescribed burns can significantly alter the risk of house loss. Furthermore the cost of treating fuels in the landscape is far cheaper than treating fuels adjacent to the houses. Here we develop a Bayesian Network to examine the relative reduction in risk that can be achieved by prescribed burning in the landscape compared with a 500 m interface zone adjacent to houses. We then compare costs of management treatments to determine the most cost-effective method of reducing risk to houses. Burning in the interface zone resulted in the greatest reduction in risk of fires reaching the houses and the intensity of these fires. Fuel treatment in the interface zone allows for a direct transfer of benefits from the fuel treatment. Costs of treating fuels in the interface were significantly higher on a per hectare basis, but the extent of area requiring treatment was considerably lower. Results of this study demonstrate that treatment of fuels at the interface is not only the best means of reducing risk, it is also the most cost-effective.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521400084X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014', 'http://www.sciencedirect.com/science/article/pii/S136481521400084X', event);\">\n    A Bayesian network approach to model farmers' crop choice using socio-psychological measurements of expected benefits of ecosystem services.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Poppenborg,  P.;  and Koellner,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 57: 227-234. 7 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521400084X\"\n     onclick=\"log_download('poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014', 'http://www.sciencedirect.com/science/article/pii/S136481521400084X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network approach to model farmers&#x27; crop choice using socio-psychological measurements of expected benefits of ecosystem services [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2014.03.006\"\n     onclick=\"log_download('poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014', 'http://doi.org/10.1016/j.envsoft.2014.03.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('poppenborg-koellner-abayesiannetworkapproachtomodelfarmerscropchoiceusingsociopsychologicalmeasurementsofexpectedbenefitsofecosystemservices-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network approach to model farmers&#x27; crop choice using socio-psychological measurements of expected benefits of ecosystem services},\n type = {article},\n year = {2014},\n keywords = {Analytical Hierarchy Process,Bayesian network,Decision-making support,Ecosystem services,Theory of planned behavior},\n pages = {227-234},\n volume = {57},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521400084X},\n month = {7},\n id = {e61d892b-2877-39a3-90d9-1b0a6970eb6c},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Models of ecosystem management typically measure the benefits of ecosystem services in terms of ecological or biophysical variables, which are influenced by management decisions and biophysical/ecological conditions. This study uses farmers&#x27; expected benefits of ecosystem services as input variables to model their decision between planting rice, annual crops or perennial crops. Based on the theory of planned behavior, a Bayesian network is constructed to model crop choice depending on attitudes toward the ecosystem services of biomass production, reduction of soil erosion, and water quality improvement. The relative importance of these decision-making criteria is quantified using the Analytical Hierarchy Process. Results indicate that Bayesian networks can use socio-psychological measurements to model decision-making. Especially as an extension to biophysical or economic models, they can serve as a powerful tool for grasping the more abstract socio-psychological dimensions of benefits of ecosystem services, and how they translate into the decisions of ecosystem managers.},\n bibtype = {article},\n author = {Poppenborg, Patrick and Koellner, Thomas},\n doi = {10.1016/j.envsoft.2014.03.006},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Models of ecosystem management typically measure the benefits of ecosystem services in terms of ecological or biophysical variables, which are influenced by management decisions and biophysical/ecological conditions. This study uses farmers' expected benefits of ecosystem services as input variables to model their decision between planting rice, annual crops or perennial crops. Based on the theory of planned behavior, a Bayesian network is constructed to model crop choice depending on attitudes toward the ecosystem services of biomass production, reduction of soil erosion, and water quality improvement. The relative importance of these decision-making criteria is quantified using the Analytical Hierarchy Process. Results indicate that Bayesian networks can use socio-psychological measurements to model decision-making. Especially as an extension to biophysical or economic models, they can serve as a powerful tool for grasping the more abstract socio-psychological dimensions of benefits of ecosystem services, and how they translate into the decisions of ecosystem managers.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320713003789\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014', 'http://www.sciencedirect.com/science/article/pii/S0006320713003789', event);\">\n    Modelling the benefits of habitat restoration in socio-ecological systems.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jellinek,  S.; Rumpff,  L.; Driscoll,  D., A.; Parris,  K., M.;  and Wintle,  B., A.\n</span>\n\n  \n\n</span>\n\n  <i>Biological Conservation</i>, 169: 60-67. 1 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320713003789\"\n     onclick=\"log_download('jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014', 'http://www.sciencedirect.com/science/article/pii/S0006320713003789', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling the benefits of habitat restoration in socio-ecological systems [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.biocon.2013.10.023\"\n     onclick=\"log_download('jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014', 'http://doi.org/10.1016/j.biocon.2013.10.023', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jellinek-rumpff-driscoll-parris-wintle-modellingthebenefitsofhabitatrestorationinsocioecologicalsystems-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling the benefits of habitat restoration in socio-ecological systems},\n type = {article},\n year = {2014},\n keywords = {Bayesian Networks,Decision making,Expert opinion,Restoration,Revegetation,Socio-ecological systems,Species richness,Uncertainty},\n pages = {60-67},\n volume = {169},\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320713003789},\n month = {1},\n id = {93e42a20-3418-36bf-b03f-8161bb374b3f},\n created = {2015-04-12T18:51:30.000Z},\n accessed = {2015-01-22},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions compared to those that do not take these factors into account. We demonstrate how Bayesian Networks can be used to integrate ecological and social data and expert opinion to model the cost-effectiveness of revegetation activities for restoring biodiversity in agricultural landscapes. We demonstrate our approach with a case-study in grassy woodlands of south-eastern Australia. In our case-study, cost-effectiveness is defined as the improvement in native reptile and beetle species richness achieved per dollar spent on a restoration action. Socio-ecological models predict that weed control, the planting of trees and shrubs, the addition of litter and timber, and the addition of rocks are likely to be the most cost-effective actions for improving reptile and beetle species richness. The cost-effectiveness of restoration actions is lower in remnant and revegetated areas than in cleared areas because of the higher marginal benefits arising from acting in degraded habitats. This result is contingent on having favourable landowner attitudes. Under the best-case landowner demographic scenarios the greatest biodiversity benefits are seen when cleared areas are restored. We find that current restoration investment practices may not be increasing faunal species richness in agricultural landscapes in the most cost-effective way, and that new restoration actions may be necessary. Integrated socio-ecological models support transparent and cost-effective conservation investment decisions. Application of these models highlights the importance of collecting both social and ecological data when attempting to understand and manage socio-ecological systems.},\n bibtype = {article},\n author = {Jellinek, Sacha and Rumpff, Libby and Driscoll, Don A. and Parris, Kirsten M. and Wintle, Brendan A.},\n doi = {10.1016/j.biocon.2013.10.023},\n journal = {Biological Conservation}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Decisions affecting the management of natural resources in agricultural landscapes are influenced by both social and ecological factors. Models that integrate these factors are likely to better predict the outcomes of natural resource management decisions compared to those that do not take these factors into account. We demonstrate how Bayesian Networks can be used to integrate ecological and social data and expert opinion to model the cost-effectiveness of revegetation activities for restoring biodiversity in agricultural landscapes. We demonstrate our approach with a case-study in grassy woodlands of south-eastern Australia. In our case-study, cost-effectiveness is defined as the improvement in native reptile and beetle species richness achieved per dollar spent on a restoration action. Socio-ecological models predict that weed control, the planting of trees and shrubs, the addition of litter and timber, and the addition of rocks are likely to be the most cost-effective actions for improving reptile and beetle species richness. The cost-effectiveness of restoration actions is lower in remnant and revegetated areas than in cleared areas because of the higher marginal benefits arising from acting in degraded habitats. This result is contingent on having favourable landowner attitudes. Under the best-case landowner demographic scenarios the greatest biodiversity benefits are seen when cleared areas are restored. We find that current restoration investment practices may not be increasing faunal species richness in agricultural landscapes in the most cost-effective way, and that new restoration actions may be necessary. Integrated socio-ecological models support transparent and cost-effective conservation investment decisions. Application of these models highlights the importance of collecting both social and ecological data when attempting to understand and manage socio-ecological systems.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X13001568', event);\">\n    EBI: An index for delivery of ecosystem service bundles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Van der Biest,  K.; D’Hondt,  R.; Jacobs,  S.; Landuyt,  D.; Staes,  J.; Goethals,  P.;  and Meire,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Indicators</i>, 37: 252-265. 2 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X13001568\"\n     onclick=\"log_download('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://www.sciencedirect.com/science/article/pii/S1470160X13001568', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"EBI: An index for delivery of ecosystem service bundles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolind.2013.04.006\"\n     onclick=\"log_download('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014', 'http://doi.org/10.1016/j.ecolind.2013.04.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vanderbiest-dhondt-jacobs-landuyt-staes-goethals-meire-ebianindexfordeliveryofecosystemservicebundles-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {EBI: An index for delivery of ecosystem service bundles},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Biophysical potential,Climate regulation,Ecosystem services,Land use planning,Provisioning services,Trade-offs},\n pages = {252-265},\n volume = {37},\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X13001568},\n month = {2},\n id = {bd5cb454-3186-32c5-8404-381786b4598b},\n created = {2015-04-12T20:17:33.000Z},\n accessed = {2015-02-04},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.},\n bibtype = {article},\n author = {Van der Biest, K. and D’Hondt, R. and Jacobs, S. and Landuyt, D. and Staes, J. and Goethals, P. and Meire, P.},\n doi = {10.1016/j.ecolind.2013.04.006},\n journal = {Ecological Indicators}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Integrating the ecosystem service concept into land use planning requires tools that allow rapid and transparent assessment of ecosystem services. The demand for simple indicators has stimulated the emergence of land use based proxy methods. Although these have been very powerful to create policy awareness on different levels, they are insufficient when it comes to land use and policy planning for ecosystem service delivery. Discarding the complex ecological reality or scientific uncertainty poses serious risks for adverse effects of policies. This explorative study constitutes the basis for the further development of a tool to link land use planning for ecosystem service bundle optimization, capturing inherent ecological complexity and uncertainty. Particular emphasis was placed on the biophysical potential of an ecosystem to deliver services and the link with the actual land use. The EBI – Ecosystem Service Bundle Index – builds on a Bayesian network model that allows integration of biophysical and socio-economic processes as well as land use planning policies driving the delivery of bundles of ecosystem services. The EBI prototype was tested in a pilot study area using three interacting ecosystem services. Incorporation of judicial land use claims, more intense involvement of stakeholders and other improvements are being developed.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://darchive.mblwhoilibrary.org/handle/1912/7233\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'https://darchive.mblwhoilibrary.org/handle/1912/7233', event);\">\n    A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gieder,  K., D.; Karpanty,  S., M.; Fraser,  J., D.; Catlin,  D., H.; Gutierrez,  B., T.; Plant,  N., G.; Turecek,  A., M.;  and Robert Thieler,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 276: 38-50. 3 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://darchive.mblwhoilibrary.org/handle/1912/7233\"\n     onclick=\"log_download('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'https://darchive.mblwhoilibrary.org/handle/1912/7233', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2014.01.005\"\n     onclick=\"log_download('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014', 'http://doi.org/10.1016/j.ecolmodel.2014.01.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gieder-karpanty-fraser-catlin-gutierrez-plant-turecek-robertthieler-abayesiannetworkapproachtopredictingnestpresenceofthefederallythreatenedpipingplovercharadriusmelodususingbarrierislandfeatures-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features},\n type = {article},\n year = {2014},\n keywords = {Bayesian network,Development,Habitat,Piping plover,Sea-level rise,Shorebird},\n pages = {38-50},\n volume = {276},\n websites = {https://darchive.mblwhoilibrary.org/handle/1912/7233},\n month = {3},\n publisher = {Elsevier},\n day = {31},\n id = {801a4e65-dfa4-3867-b5eb-f3b6cd49d872},\n created = {2015-05-07T19:12:09.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n language = {en_US},\n private_publication = {false},\n abstract = {© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 276 (2014): 38–50, doi:10.1016/j.ecolmodel.2014.01.005.},\n bibtype = {article},\n author = {Gieder, Katherina D. and Karpanty, Sarah M. and Fraser, James D. and Catlin, Daniel H. and Gutierrez, Benjamin T. and Plant, Nathaniel G. and Turecek, Aaron M. and Robert Thieler, E.},\n doi = {10.1016/j.ecolmodel.2014.01.005},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 276 (2014): 38–50, doi:10.1016/j.ecolmodel.2014.01.005.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2013\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2013')\"\n      onkeypress=\"toggleGroup('group_2013')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2013</span>\n      <span class=\"bibbase_group_count\">\n        \n        (26)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://www.sciencedirect.com/science/article/pii/S136481521200206X', event);\">\n    Bayesian belief modeling of climate change impacts for informing regional adaptation options.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Richards,  R.; Sanó,  M.; Roiko,  A.; Carter,  R.; Bussey,  M.; Matthews,  J.;  and Smith,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 44: 113-121. 6 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"\n     onclick=\"log_download('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://www.sciencedirect.com/science/article/pii/S136481521200206X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian belief modeling of climate change impacts for informing regional adaptation options [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.07.008\"\n     onclick=\"log_download('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://doi.org/10.1016/j.envsoft.2012.07.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},\n type = {article},\n year = {2013},\n keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},\n pages = {113-121},\n volume = {44},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},\n month = {6},\n id = {a54c3232-2de1-345c-9420-c718b2f27607},\n created = {2015-04-11T15:45:45.000Z},\n accessed = {2015-02-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},\n bibtype = {article},\n author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},\n doi = {10.1016/j.envsoft.2012.07.008},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000522', event);\">\n    An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Portoghese,  I.; D'Agostino,  D.; Giordano,  R.; Scardigno,  A.; Apollonio,  C.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 46: 90-103. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"\n     onclick=\"log_download('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000522', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.03.001\"\n     onclick=\"log_download('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://doi.org/10.1016/j.envsoft.2013.03.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},\n type = {article},\n year = {2013},\n keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},\n pages = {90-103},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},\n month = {8},\n id = {ecee1c33-4441-35b5-b2e5-d008f50d97d0},\n created = {2015-04-11T15:45:45.000Z},\n accessed = {2015-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders&#x27; attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers&#x27; behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},\n bibtype = {article},\n author = {Portoghese, Ivan and D&#x27;Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},\n doi = {10.1016/j.envsoft.2013.03.001},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000741', event);\">\n    A review of Bayesian belief networks in ecosystem service modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Landuyt,  D.; Broekx,  S.; D'hondt,  R.; Engelen,  G.; Aertsens,  J.;  and Goethals,  P., L.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 46: 1-11. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"\n     onclick=\"log_download('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000741', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A review of Bayesian belief networks in ecosystem service modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.03.011\"\n     onclick=\"log_download('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://doi.org/10.1016/j.envsoft.2013.03.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A review of Bayesian belief networks in ecosystem service modelling},\n type = {article},\n year = {2013},\n keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},\n pages = {1-11},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},\n month = {8},\n id = {cde4bf8d-fd72-3d55-bba7-f0059de57b6a},\n created = {2015-04-11T15:50:45.000Z},\n accessed = {2015-02-10},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},\n bibtype = {article},\n author = {Landuyt, Dries and Broekx, Steven and D&#x27;hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},\n doi = {10.1016/j.envsoft.2013.03.011},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713002016\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713002016', event);\">\n    Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Spence,  P., L.;  and Jordan,  S., J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 124: 91-9. 7 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713002016\"\n     onclick=\"log_download('spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713002016', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2013.03.029\"\n     onclick=\"log_download('spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013', 'http://doi.org/10.1016/j.jenvman.2013.03.029', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('spence-jordan-effectsofnitrogeninputsonfreshwaterwetlandecosystemservicesabayesiannetworkanalysis-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Effects of nitrogen inputs on freshwater wetland ecosystem services - a Bayesian network analysis.},\n type = {article},\n year = {2013},\n keywords = {Bayes Theorem,Ecosystem,Empirical Research,Fresh Water,Fresh Water: chemistry,Nitrogen,Nitrogen: analysis,Wetlands},\n pages = {91-9},\n volume = {124},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713002016},\n month = {7},\n day = {30},\n id = {c5517933-9eb6-37af-a3d4-a2d37a79f7f2},\n created = {2015-04-11T17:43:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Increased nitrogen (N) inputs to freshwater wetlands potentially affect the interaction between nitrous oxide (N2O) emissions and outflow water quality. The purpose of this study is to evaluate the influence of N inputs on N removal, as well as the interaction between N2O emissions and outflow water quality, using a Bayesian Belief Network (BBN). The BBN was developed by linking wetland classification, biogeochemical processes, and environmental factors. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was implemented using 30 wetlands (88% of the case file) and evaluated using a single test file containing 4 wetlands (12% of the case file). The BBN implies it is not average annual total N load entering the wetland, but the N removal efficiency that influences the interactions between N2O emissions and outflow water quality. Even though the network has a very low error rate indicating a high predictive accuracy, additional testing and larger training and testing datasets would increase confidence in the model&#x27;s ability to provide robust predictions and to reduce the uncertainty resulting from an incomplete dataset and knowledge gaps regarding the interactions between N2O emissions and outflow water quality.},\n bibtype = {article},\n author = {Spence, Porché L and Jordan, Stephen J},\n doi = {10.1016/j.jenvman.2013.03.029},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Increased nitrogen (N) inputs to freshwater wetlands potentially affect the interaction between nitrous oxide (N2O) emissions and outflow water quality. The purpose of this study is to evaluate the influence of N inputs on N removal, as well as the interaction between N2O emissions and outflow water quality, using a Bayesian Belief Network (BBN). The BBN was developed by linking wetland classification, biogeochemical processes, and environmental factors. Empirical data for 34 freshwater wetlands were gathered from a comprehensive review of published peer-reviewed and gray literature. The BBN was implemented using 30 wetlands (88% of the case file) and evaluated using a single test file containing 4 wetlands (12% of the case file). The BBN implies it is not average annual total N load entering the wetland, but the N removal efficiency that influences the interactions between N2O emissions and outflow water quality. Even though the network has a very low error rate indicating a high predictive accuracy, additional testing and larger training and testing datasets would increase confidence in the model's ability to provide robust predictions and to reduce the uncertainty resulting from an incomplete dataset and knowledge gaps regarding the interactions between N2O emissions and outflow water quality.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000121\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000121', event);\">\n    The construction of causal networks to estimate coral bleaching intensity.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Krug,  L., A.; Gherardi,  D., F., M.; Stech,  J., L.; Leão,  Z., M., A., N.; Kikuchi,  R., K., P.; Hruschka,  E., R.;  and Suggett,  D., J.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 42: 157-167. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000121\"\n     onclick=\"log_download('krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000121', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The construction of causal networks to estimate coral bleaching intensity [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.01.003\"\n     onclick=\"log_download('krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013', 'http://doi.org/10.1016/j.envsoft.2013.01.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('krug-gherardi-stech-leo-kikuchi-hruschka-suggett-theconstructionofcausalnetworkstoestimatecoralbleachingintensity-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The construction of causal networks to estimate coral bleaching intensity},\n type = {article},\n year = {2013},\n keywords = {AGRRA,Atlantic and Gulf Rapid Reef Assessment,BN,BNPC,BSST,Bayesian network,Bayesian networks,Belief Network Power Constructor,CI,CPT,Coral bleaching,Coral reef,DAG,EM,Environmental variability,K490,MEI,MaxSST,PCA,PPT,Remote sensing,SST,SSTAc5d,South Atlantic coral reefs,U,V,best sea surface temperature,conditional independence,conditional probabilities table,diffuse light attenuation coefficient at 490 nm,directed acyclic graph,expectation–maximization,maximum sea surface temperature,mean surface wind fields,meridional wind,multivariate El Niño index,principal component analysis,rain precipitation,sea surface temperature,sea surface temperature accumulated in five days,zonal wind,|W|},\n pages = {157-167},\n volume = {42},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000121},\n month = {4},\n id = {4a097128-e62a-3c7b-ad37-6b51838d86f0},\n created = {2015-04-11T17:55:10.000Z},\n accessed = {2015-02-27},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Current metrics for predicting bleaching episodes, e.g. NOAA&#x27;s Coral Reef Watch Program, do not seem to apply well to Brazil&#x27;s marginal reefs located in Bahia state and alternative predictive approaches must be sought for effective long term management. Bleaching occurrences at Abrolhos have been observed since the 1990s but with a much lower frequency/extent than for other reef systems worldwide. We constructed a Bayesian Belief Network (BN) to back-predict the intensity of bleaching events and learn how local and regional scale forcing factors interact to enhance or alleviate coral bleaching specific to Abrolhos. Bleaching intensity data were collected for several reef sites across Bahia state coast (∼12°–20°S; 37°–40°W) during the austral summer 1994–2005 and compared to environmental data: sea surface temperature (SST), diffuse light attenuation coefficient at 490 nm (K490), rain precipitation, wind velocities, and El Niño Southern Oscillation (ENSO) proxies. Conditional independence tests were calculated to produce four specialized BNs, each with specific factors that likely regulate bleaching intensity. All specialized BNs identified that a five-day accumulated SST proxy (SSTAc5d) was the exclusive parent node for coral bleaching producing a total predictive rate of 88% based on SSTAc5d state. When SSTAc5d was simulated as unknown, the Thermal-Eolic Resultant BN kept the total predictive rate of 88%. Our approach has produced initial means to predict beaching intensity at Abrolhos. However, the robustness of the model required for management purposes must be further (and regularly) operationally tested with new in situ and remote sensing data.},\n bibtype = {article},\n author = {Krug, Lilian Anne and Gherardi, Douglas Francisco Marcolino and Stech, José Luís and Leão, Zelinda Margarida Andrade Nery and Kikuchi, Ruy Kenji Papa and Hruschka, Estevam Rafael and Suggett, David John},\n doi = {10.1016/j.envsoft.2013.01.003},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Current metrics for predicting bleaching episodes, e.g. NOAA's Coral Reef Watch Program, do not seem to apply well to Brazil's marginal reefs located in Bahia state and alternative predictive approaches must be sought for effective long term management. Bleaching occurrences at Abrolhos have been observed since the 1990s but with a much lower frequency/extent than for other reef systems worldwide. We constructed a Bayesian Belief Network (BN) to back-predict the intensity of bleaching events and learn how local and regional scale forcing factors interact to enhance or alleviate coral bleaching specific to Abrolhos. Bleaching intensity data were collected for several reef sites across Bahia state coast (∼12°–20°S; 37°–40°W) during the austral summer 1994–2005 and compared to environmental data: sea surface temperature (SST), diffuse light attenuation coefficient at 490 nm (K490), rain precipitation, wind velocities, and El Niño Southern Oscillation (ENSO) proxies. Conditional independence tests were calculated to produce four specialized BNs, each with specific factors that likely regulate bleaching intensity. All specialized BNs identified that a five-day accumulated SST proxy (SSTAc5d) was the exclusive parent node for coral bleaching producing a total predictive rate of 88% based on SSTAc5d state. When SSTAc5d was simulated as unknown, the Thermal-Eolic Resultant BN kept the total predictive rate of 88%. Our approach has produced initial means to predict beaching intensity at Abrolhos. However, the robustness of the model required for management purposes must be further (and regularly) operationally tested with new in situ and remote sensing data.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000522', event);\">\n    An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Portoghese,  I.; D'Agostino,  D.; Giordano,  R.; Scardigno,  A.; Apollonio,  C.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 46: 90-103. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000522\"\n     onclick=\"log_download('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000522', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.03.001\"\n     onclick=\"log_download('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013', 'http://doi.org/10.1016/j.envsoft.2013.03.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('portoghese-dagostino-giordano-scardigno-apollonio-vurro-anintegratedmodellingtooltoevaluatetheacceptabilityofirrigationconstraintmeasuresforgroundwaterprotection-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An integrated modelling tool to evaluate the acceptability of irrigation constraint measures for groundwater protection},\n type = {article},\n year = {2013},\n keywords = {Bayesian Belief Networks,Conflict mitigation,Groundwater protection policy,Stakeholder involvement},\n pages = {90-103},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000522},\n month = {8},\n id = {aad23f85-469d-3656-8244-34b843ea5b87},\n created = {2015-04-11T18:33:34.000Z},\n accessed = {2015-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders&#x27; attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers&#x27; behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.},\n bibtype = {article},\n author = {Portoghese, Ivan and D&#x27;Agostino, Daniela and Giordano, Raffaele and Scardigno, Alessandra and Apollonio, Ciro and Vurro, Michele},\n doi = {10.1016/j.envsoft.2013.03.001},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In many arid and semi-arid regions agriculture is the main user of GW, causing problems with the quantity and quality of water, but there are few institutional policies and regulations governing sustainable GW exploitation. The authors suggest an integrated methodology for enabling local GW management, capable of combining the need for GW protection with socio-economic and behavioural determinants of GW use. In the proposed tool, integration is reinforced by the inclusion of multiple stakeholders, and the use of Bayesian Belief Networks (BBN) to simulate and explore these stakeholders' attitude to GW exploitation and their responses to the introduction of new protection policies. BBNs and hydrological system properties are integrated in a GIS-based decision support system – GeSAP – which can elaborate and analyse scenarios concerning the pressure on GW due to exploitation for irrigation, and the effectiveness of protection policies, taking into account the level of consensus. In addition, the GIS interface makes it possible to spatialize the information and to investigate model results. The paper presents the results of an experimental application of the GeSAP tool to support GW planning and management in the Apulia Region (Southern Italy). To evaluate the actual usability of the GeSAP tool, case study applications were performed involving the main experts in GW protection and the regional decision-makers. Results showed that GeSAP can simulate farmers' behaviour concerning the selection of water sources for irrigation, allowing evaluation of the effectiveness of a wide range of strategies which impact water demand and consumption.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://www.sciencedirect.com/science/article/pii/S136481521200206X', event);\">\n    Bayesian belief modeling of climate change impacts for informing regional adaptation options.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Richards,  R.; Sanó,  M.; Roiko,  A.; Carter,  R.; Bussey,  M.; Matthews,  J.;  and Smith,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 44: 113-121. 6 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481521200206X\"\n     onclick=\"log_download('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://www.sciencedirect.com/science/article/pii/S136481521200206X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian belief modeling of climate change impacts for informing regional adaptation options [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.07.008\"\n     onclick=\"log_download('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013', 'http://doi.org/10.1016/j.envsoft.2012.07.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('richards-san-roiko-carter-bussey-matthews-smith-bayesianbeliefmodelingofclimatechangeimpactsforinformingregionaladaptationoptions-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian belief modeling of climate change impacts for informing regional adaptation options},\n type = {article},\n year = {2013},\n keywords = {Adaptation,Bayesian Belief Networks,Climate change,Group-model building,Stakeholder beliefs},\n pages = {113-121},\n volume = {44},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481521200206X},\n month = {6},\n id = {ae659db2-aa4d-3a21-bab2-5227c2e85480},\n created = {2015-04-11T18:33:35.000Z},\n accessed = {2015-02-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.},\n bibtype = {article},\n author = {Richards, R. and Sanó, M. and Roiko, A. and Carter, R.W. and Bussey, M. and Matthews, J. and Smith, T.F.},\n doi = {10.1016/j.envsoft.2012.07.008},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A sequential approach to combining two established modeling techniques (systems thinking and Bayesian Belief Networks; BBNs) was developed and applied to climate change adaptation research within the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI). Six participatory workshops involving 66 stakeholders based within SEQ produced six system conceptualizations and 22 alpha-level BBNs. The outcomes of the initial systems modeling exercise successfully allowed the selection of critical determinants of key response variables for in depth analysis within more homogeneous, sector-based groups of participants. Using two cases, this article focuses on the processes and methodological issues relating to the use of the BBN modeling technique when the data are based on expert opinion. The study expected to find both generic and specific determinants of adaptive capacity based on the perceptions of the stakeholders involved. While generic determinants were found (e.g. funding and awareness levels), sensitivity analysis identified the importance of pragmatic, context-based determinants, which also had methodological implications. The article raises questions about the most appropriate scale at which the methodology applied can be used to identify useful generic determinants of adaptive capacity when, at the scale used, the most useful determinants were sector-specific. Comparisons between individual BBN conditional probabilities identified diverging and converging beliefs, and that the sensitivity of response variables to direct descendant nodes was not always perceived consistently. It was often the accompanying narrative that provided important contextual information that explained observed differences, highlighting the benefits of using critical narrative with modeling tools.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479712005968\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479712005968', event);\">\n    Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Giordano,  R.; D'Agostino,  D.; Apollonio,  C.; Lamaddalena,  N.;  and Vurro,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 115: 136-46. 1 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479712005968\"\n     onclick=\"log_download('giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479712005968', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2012.11.011\"\n     onclick=\"log_download('giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013', 'http://doi.org/10.1016/j.jenvman.2012.11.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('giordano-dagostino-apollonio-lamaddalena-vurro-bayesianbeliefnetworktosupportconflictanalysisforgroundwaterprotectionthecaseoftheapuliaregion-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.},\n type = {article},\n year = {2013},\n keywords = {Bayes Theorem,Geographic Information Systems,Groundwater,Models, Theoretical},\n pages = {136-46},\n volume = {115},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479712005968},\n month = {1},\n day = {30},\n id = {eb1d6109-7a14-3dea-87f7-7d525816fa8b},\n created = {2015-04-11T18:33:36.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers&#x27; mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers&#x27; objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers&#x27; behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region&#x27;s water management regime, which is still grounded in merely technical approaches.},\n bibtype = {article},\n author = {Giordano, Raffaele and D&#x27;Agostino, Daniela and Apollonio, Ciro and Lamaddalena, Nicola and Vurro, Michele},\n doi = {10.1016/j.jenvman.2012.11.011},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X13005821\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013', 'http://www.sciencedirect.com/science/article/pii/S0025326X13005821', event);\">\n    A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Montewka,  J.; Weckström,  M.;  and Kujala,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Marine Pollution Bulletin</i>, 76(1-2): 61-71. 11 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X13005821\"\n     onclick=\"log_download('montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013', 'http://www.sciencedirect.com/science/article/pii/S0025326X13005821', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpolbul.2013.09.031\"\n     onclick=\"log_download('montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013', 'http://doi.org/10.1016/j.marpolbul.2013.09.031', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('montewka-weckstrm-kujala-aprobabilisticmodelestimatingoilspillcleanupcostsacasestudyforthegulfoffinland-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A probabilistic model estimating oil spill clean-up costs – A case study for the Gulf of Finland},\n type = {article},\n year = {2013},\n keywords = {Bayesian Belief Networks,Clean-up costs,Maritime traffic,Oil spill,Risk analysis,The Gulf of Finland},\n pages = {61-71},\n volume = {76},\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X13005821},\n month = {11},\n id = {f778c0e8-482c-32c1-8276-b92a0d3e2c33},\n created = {2015-04-11T18:33:36.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).},\n bibtype = {article},\n author = {Montewka, Jakub and Weckström, Mia and Kujala, Pentti},\n doi = {10.1016/j.marpolbul.2013.09.031},\n journal = {Marine Pollution Bulletin},\n number = {1-2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000741', event);\">\n    A review of Bayesian belief networks in ecosystem service modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Landuyt,  D.; Broekx,  S.; D'hondt,  R.; Engelen,  G.; Aertsens,  J.;  and Goethals,  P., L.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 46: 1-11. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000741\"\n     onclick=\"log_download('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000741', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A review of Bayesian belief networks in ecosystem service modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.03.011\"\n     onclick=\"log_download('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013', 'http://doi.org/10.1016/j.envsoft.2013.03.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('landuyt-broekx-dhondt-engelen-aertsens-goethals-areviewofbayesianbeliefnetworksinecosystemservicemodelling-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A review of Bayesian belief networks in ecosystem service modelling},\n type = {article},\n year = {2013},\n keywords = {Bayesian belief networks,Ecosystem services,Expert based systems,Graphical models},\n pages = {1-11},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000741},\n month = {8},\n id = {0229274b-5eb8-3c13-82dd-e9f5691ae50a},\n created = {2015-04-11T18:46:32.000Z},\n accessed = {2015-02-10},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.},\n bibtype = {article},\n author = {Landuyt, Dries and Broekx, Steven and D&#x27;hondt, Rob and Engelen, Guy and Aertsens, Joris and Goethals, Peter L.M.},\n doi = {10.1016/j.envsoft.2013.03.011},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A wide range of quantitative and qualitative modelling research on ecosystem services (ESS) has recently been conducted. The available models range between elementary, indicator-based models and complex process-based systems. A semi-quantitative modelling approach that has recently gained importance in ecological modelling is Bayesian belief networks (BBNs). Due to their high transparency, the possibility to combine empirical data with expert knowledge and their explicit treatment of uncertainties, BBNs can make a considerable contribution to the ESS modelling research. However, the number of applications of BBNs in ESS modelling is still limited. This review discusses a number of BBN-based ESS models developed in the last decade. A SWOT analysis highlights the advantages and disadvantages of BBNs in ESS modelling and pinpoints remaining challenges for future research. The existing BBN models are suited to describe, analyse, predict and value ESS. Nevertheless, some weaknesses have to be considered, including poor flexibility of frequently applied software packages, difficulties in eliciting expert knowledge and the inability to model feedback loops.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0167198713000925\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013', 'http://www.sciencedirect.com/science/article/pii/S0167198713000925', event);\">\n    Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Troldborg,  M.; Aalders,  I.; Towers,  W.; Hallett,  P., D.; McKenzie,  B., M.; Bengough,  A., G.; Lilly,  A.; Ball,  B., C.;  and Hough,  R., L.\n</span>\n\n  \n\n</span>\n\n  <i>Soil and Tillage Research</i>, 132: 56-68. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0167198713000925\"\n     onclick=\"log_download('troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013', 'http://www.sciencedirect.com/science/article/pii/S0167198713000925', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.still.2013.05.005\"\n     onclick=\"log_download('troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013', 'http://doi.org/10.1016/j.still.2013.05.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('troldborg-aalders-towers-hallett-mckenzie-bengough-lilly-ball-etal-applicationofbayesianbeliefnetworkstoquantifyandmapareasatrisktosoilthreatsusingsoilcompactionasanexample-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Application of Bayesian Belief Networks to quantify and map areas at risk to soil threats: Using soil compaction as an example},\n type = {article},\n year = {2013},\n keywords = {Bayesian Belief Network,Expert knowledge,Risk assessment,Soil Framework directive,Soil compaction,Uncertainty},\n pages = {56-68},\n volume = {132},\n websites = {http://www.sciencedirect.com/science/article/pii/S0167198713000925},\n month = {8},\n id = {ec8cccf5-6295-358f-8c7f-855694c983ee},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil&#x27;s vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland.},\n bibtype = {article},\n author = {Troldborg, Mads and Aalders, Inge and Towers, Willie and Hallett, Paul D. and McKenzie, Blair M. and Bengough, A. Glyn and Lilly, Allan and Ball, Bruce C. and Hough, Rupert L.},\n doi = {10.1016/j.still.2013.05.005},\n journal = {Soil and Tillage Research}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The assessment of areas at risk from various soil threats is a key task within the proposed EU Soil Framework Directive. Such assessment is, however, hampered by the complex nature of the soil threats, which result from the sometimes poorly understood interaction of various soil physical properties, climatic factors and land management practices. Methodologies for risk assessment of soil threats are needed to protect the soil quality for future generations and to target resources to the areas at greatest risk. We present here a generic risk framework for the development of Bayesian Belief Networks (BBNs) to estimate the risk from soil threats. The generic BBN structure follows a standard risk assessment approach, where the risk is quantified by combining assessments of vulnerability and exposure. The soil's vulnerability to a given threat is determined from inherent soil and site characteristics as well as from climatic factors influencing soil characteristics, while the exposure estimate is based on an evaluation of the stresses inflicted by land management and climate. The generic framework is demonstrated by taking soil compaction as an example. Soil compaction is a major threat to soil function particularly in highly managed agricultural systems and is known to have many adverse effects on farming systems including decreased crop yield and soil productivity, increased management costs, increased emissions of greenhouse gases, and decreased water infiltration into the soil leading to accelerated run-off and risk of soil erosion. Existing modelling approaches to predict soil compaction risk either require data on soil mechanical behaviour that are difficult and expensive to collect, or are expert-based systems that are highly subjective and sometimes cannot accommodate the myriad of processes underlying compaction risk. Using the generic framework, a detailed BBN for assessing the risk of soil compaction is developed. The BBN allows for combining available data from standard soil surveys and land use databases with qualitative expert knowledge and explicitly accounts for uncertainties in the assessment of the risk. The BBN is applied to identify the distribution of the compaction risk across Scotland using data from the National Soils Inventory of Scotland.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002319', event);\">\n    Prediction analysis of a wastewater treatment system using a Bayesian network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  D.; Yang,  H., Z.;  and Liang,  X., F.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 40: 140-150. 2 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"\n     onclick=\"log_download('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002319', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Prediction analysis of a wastewater treatment system using a Bayesian network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.08.011\"\n     onclick=\"log_download('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://doi.org/10.1016/j.envsoft.2012.08.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Prediction analysis of a wastewater treatment system using a Bayesian network},\n type = {article},\n year = {2013},\n keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},\n pages = {140-150},\n volume = {40},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},\n month = {2},\n id = {07511849-6753-38c4-9bdb-aeb95cf6d63c},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},\n bibtype = {article},\n author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},\n doi = {10.1016/j.envsoft.2012.08.011},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://www.sciencedirect.com/science/article/pii/S0925857413003224', event);\">\n    Analysis of topographic and vegetative factors with data mining for landslide verification.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tsai,  F.; Lai,  J.; Chen,  W., W.;  and Lin,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Engineering</i>, 61: 669-677. 12 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"\n     onclick=\"log_download('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://www.sciencedirect.com/science/article/pii/S0925857413003224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Analysis of topographic and vegetative factors with data mining for landslide verification [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoleng.2013.07.070\"\n     onclick=\"log_download('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://doi.org/10.1016/j.ecoleng.2013.07.070', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Analysis of topographic and vegetative factors with data mining for landslide verification},\n type = {article},\n year = {2013},\n keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},\n pages = {669-677},\n volume = {61},\n websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},\n month = {12},\n id = {d9301f8a-f1f0-3dd7-b8fe-36b17a45dd03},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-03-03},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},\n bibtype = {article},\n author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},\n doi = {10.1016/j.ecoleng.2013.07.070},\n journal = {Ecological Engineering}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380013003967\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013', 'http://www.sciencedirect.com/science/article/pii/S0304380013003967', event);\">\n    Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment).\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keshtkar,  A.; Salajegheh,  A.; Sadoddin,  A.;  and Allan,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 268: 48-54. 10 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380013003967\"\n     onclick=\"log_download('keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013', 'http://www.sciencedirect.com/science/article/pii/S0304380013003967', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2013.08.003\"\n     onclick=\"log_download('keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013', 'http://doi.org/10.1016/j.ecolmodel.2013.08.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keshtkar-salajegheh-sadoddin-allan-applicationofbayesiannetworksforsustainabilityassessmentincatchmentmodelingandmanagementcasestudythehablehroodrivercatchment-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Application of Bayesian networks for sustainability assessment in catchment modeling and management (Case study: The Hablehrood river catchment)},\n type = {article},\n year = {2013},\n keywords = {Bayesian network,Decision support,Integrated catchment management,Iran,Sustainability assessment,Vegetation management},\n pages = {48-54},\n volume = {268},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380013003967},\n month = {10},\n id = {1927d58f-21fe-3e7f-9be6-314f51358ff8},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.},\n bibtype = {article},\n author = {Keshtkar, A.R. and Salajegheh, A. and Sadoddin, A. and Allan, M.G.},\n doi = {10.1016/j.ecolmodel.2013.08.003},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Catchment management is a process which increases the sustainable development and management of all catchment resources in order to maximize the balance among socioeconomic welfare and the sustainability of vital ecosystems. The increase of anthropogenic activities within river catchments causes degradation and serious problems for stakeholders and managers, particularly in arid and semi-arid regions. Although there are many techniques for solving these problems, it is not easy for catchment managers to apply them. An integrated Bayesian network model framework was applied to evaluate the sustainability of a semi-arid river catchment located in the Iranian Central Plateau river basin encompassing 32.6km2 area on the Hablehrood river catchment, located in the northern part of the Iranian Central Plateau river basin. The research illustrated the assessment of the relevant management problems, the model framework, and the techniques applied to extract input data. Results for the study area implementation and a suggestion for management are described and discussed.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001200333X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013', 'http://www.sciencedirect.com/science/article/pii/S030438001200333X', event);\">\n    Mining monitored data for decision-making with a Bayesian network model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Williams,  B.;  and Cole,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 249: 26-36. 1 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001200333X\"\n     onclick=\"log_download('williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013', 'http://www.sciencedirect.com/science/article/pii/S030438001200333X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Mining monitored data for decision-making with a Bayesian network model [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2012.07.008\"\n     onclick=\"log_download('williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013', 'http://doi.org/10.1016/j.ecolmodel.2012.07.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('williams-cole-miningmonitoreddatafordecisionmakingwithabayesiannetworkmodel-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Mining monitored data for decision-making with a Bayesian network model},\n type = {article},\n year = {2013},\n keywords = {Bayesian networks,Cyanobacteria,Data mining,Elicitation,Reservoir management,Water quality},\n pages = {26-36},\n volume = {249},\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001200333X},\n month = {1},\n id = {27102ba9-ac77-3ba5-87dd-7283b4291c45},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-08},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers. Monitored data were arranged in a consistently formatted database from which the model could ‘learn’ probabilistic relationships between model elements such as pumped nutrient load, lake water column nutrient concentrations, and Anabaena concentrations. This ‘minimal model’ produced useful insights into ecosystem relationships and provided a basic model for later development. Subsequent modelling and elicitation of conditional probabilities from experts strengthened components of the model for which there is little data available. The approach to incorporating elicited data is described and some simple scenario testing is also presented. Management outcomes resulting from application of the model are presented.},\n bibtype = {article},\n author = {Williams, B.J. and Cole, B.},\n doi = {10.1016/j.ecolmodel.2012.07.008},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers. Monitored data were arranged in a consistently formatted database from which the model could ‘learn’ probabilistic relationships between model elements such as pumped nutrient load, lake water column nutrient concentrations, and Anabaena concentrations. This ‘minimal model’ produced useful insights into ecosystem relationships and provided a basic model for later development. Subsequent modelling and elicitation of conditional probabilities from experts strengthened components of the model for which there is little data available. The approach to incorporating elicited data is described and some simple scenario testing is also presented. Management outcomes resulting from application of the model are presented.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X13000887\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013', 'http://www.sciencedirect.com/science/article/pii/S0308521X13000887', event);\">\n    Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Florin,  M., J.; van Ittersum,  M., K.;  and van de Ven,  G., W.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Systems</i>, 121: 81-95. 10 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X13000887\"\n     onclick=\"log_download('florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013', 'http://www.sciencedirect.com/science/article/pii/S0308521X13000887', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agsy.2013.07.002\"\n     onclick=\"log_download('florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013', 'http://doi.org/10.1016/j.agsy.2013.07.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('florin-vanittersum-vandeven-familyfarmersandbiodieselproductionsystemsthinkingandmultileveldecisionsinnorthernminasgeraisbrazil-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil},\n type = {article},\n year = {2013},\n keywords = {Bayesian network modelling,Biodiesel,Expert opinion,Family farming,Social inclusion,Systems thinking},\n pages = {81-95},\n volume = {121},\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X13000887},\n month = {10},\n id = {484e0845-a9f8-3bb7-a2a4-1fbd4a6c552a},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-03-10},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This study focuses on family farmer engagement in the Brazilian national programme for Production and use of Biodiesel (PNPB). The Brazilian government has been promoting the role of family farmers as producers of biomass for biodiesel since 2004; however, fewer than expected family farmers have decided to produce biomass for biodiesel. The North of Minas Gerais is one region where a biodiesel plant has been strategically located to source castor beans grown by family farmers. The target family farm type in this region specializes in beef and/or dairy production with low input pasture (approximately 30ha per farm), maize intercropped with beans (approximately 1ha per farm) and sugarcane (approximately 1ha per farm). We selected this region for a case study to explore management decisions of farmers, industry and policy makers that influence family farmer engagement with biodiesel production through cultivation of castor beans. To evaluate outcomes for family farmers engaging with the PNPB, we focused on how cultivation of castor beans impacts family farmers in terms of income levels, income stability and levels of milk production. We used an application of systems thinking known as Bayesian network modelling (BNM). BNM was chosen for its suitability to integrate different types of knowledge and to include quantitative and qualitative variables. The study was built on a body of scientific literature explaining why family farmers have not been cultivating castor beans for biodiesel production and a body of experiential knowledge of local actors (farmers, extension officers, policy makers, biodiesel manufacturers and researchers in North of Minas Gerais). The complete BNM consisted of a ‘cause and effect’ diagram where the strengths of the causal relationships were quantified with elicited opinions from surveyed local actors. We used the complete BNM to explore scenarios that could improve outcomes for family farmers and consequently increase their level of engagement. For example, we addressed subsidy structures of the PNPB, crop management, farm-level trade-offs and value-chain innovations. We demonstrate that decisions to support family farmer engagement with biodiesel are not singular. Engagement by family farmers requires simultaneously: improvements in technical crop management, reductions in farm-level cash constraints and innovations in the production chain such that engagement of family farmers goes beyond cultivation of one more low-value crop. Finally we discuss some methodological issues from this application of BNM to farming systems research.},\n bibtype = {article},\n author = {Florin, Madeleine J. and van Ittersum, Martin K. and van de Ven, Gerrie W.J.},\n doi = {10.1016/j.agsy.2013.07.002},\n journal = {Agricultural Systems}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This study focuses on family farmer engagement in the Brazilian national programme for Production and use of Biodiesel (PNPB). The Brazilian government has been promoting the role of family farmers as producers of biomass for biodiesel since 2004; however, fewer than expected family farmers have decided to produce biomass for biodiesel. The North of Minas Gerais is one region where a biodiesel plant has been strategically located to source castor beans grown by family farmers. The target family farm type in this region specializes in beef and/or dairy production with low input pasture (approximately 30ha per farm), maize intercropped with beans (approximately 1ha per farm) and sugarcane (approximately 1ha per farm). We selected this region for a case study to explore management decisions of farmers, industry and policy makers that influence family farmer engagement with biodiesel production through cultivation of castor beans. To evaluate outcomes for family farmers engaging with the PNPB, we focused on how cultivation of castor beans impacts family farmers in terms of income levels, income stability and levels of milk production. We used an application of systems thinking known as Bayesian network modelling (BNM). BNM was chosen for its suitability to integrate different types of knowledge and to include quantitative and qualitative variables. The study was built on a body of scientific literature explaining why family farmers have not been cultivating castor beans for biodiesel production and a body of experiential knowledge of local actors (farmers, extension officers, policy makers, biodiesel manufacturers and researchers in North of Minas Gerais). The complete BNM consisted of a ‘cause and effect’ diagram where the strengths of the causal relationships were quantified with elicited opinions from surveyed local actors. We used the complete BNM to explore scenarios that could improve outcomes for family farmers and consequently increase their level of engagement. For example, we addressed subsidy structures of the PNPB, crop management, farm-level trade-offs and value-chain innovations. We demonstrate that decisions to support family farmer engagement with biodiesel are not singular. Engagement by family farmers requires simultaneously: improvements in technical crop management, reductions in farm-level cash constraints and innovations in the production chain such that engagement of family farmers goes beyond cultivation of one more low-value crop. Finally we discuss some methodological issues from this application of BNM to farming systems research.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000716\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000716', event);\">\n    Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nash,  D.; Waters,  D.; Buldu,  A.; Wu,  Y.; Lin,  Y.; Yang,  W.; Song,  Y.; Shu,  J.; Qin,  W.;  and Hannah,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 46: 170-181. 8 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213000716\"\n     onclick=\"log_download('nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213000716', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.03.008\"\n     onclick=\"log_download('nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013', 'http://doi.org/10.1016/j.envsoft.2013.03.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nash-waters-buldu-wu-lin-yang-song-shu-etal-usingaconceptualbayesiannetworktoinvestigateenvironmentalmanagementofvegetableproductioninthelaketaihuregionofchina-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using a conceptual Bayesian network to investigate environmental management of vegetable production in the Lake Taihu region of China},\n type = {article},\n year = {2013},\n keywords = {Bayesian Network,China,Exports,Modelling,Nitrogen,Vegetable},\n pages = {170-181},\n volume = {46},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213000716},\n month = {8},\n id = {43f34b8d-12ab-3de0-bfef-40b25d3b2108},\n created = {2015-04-11T19:52:19.000Z},\n accessed = {2015-02-26},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Vegetable farms are one of many nitrogen (N) sources adversely affecting Lake Taihu in eastern China. Given the lack of quantitative “cause and effect” relationships and data relating to these systems, we developed a conceptual Bayesian network to investigate and demonstrate causal relationships and the effects of different mitigation strategies on N exports from vegetable farms in the Lake Taihu region. Structurally, the network comprised one primary transport factor, one primary source factor and three post-mobilisation strategies, and three output factors. In general the network suggests that N exports are more sensitive to transport factors (i.e. runoff volumes) than source factors (i.e. fertiliser application rates) although the cumulative effects of excessive fertiliser were not considered. Post-mobilisation mitigations such as wetlands and ecoditches appear to be particularly effective in decreasing N exports however their implementation on a regional scale may be limited by land availability. While optimising N inputs would be prudent, the network suggests that better irrigation practice, including improved irrigation scheduling, using less imported water and optimising rainfall utilisation would be more effective in achieving environmental goals than simply limiting N supply.},\n bibtype = {article},\n author = {Nash, David and Waters, David and Buldu, Andres and Wu, Yuming and Lin, Yaping and Yang, Weiqiu and Song, Yuzhi and Shu, Jianhua and Qin, Wei and Hannah, Murray},\n doi = {10.1016/j.envsoft.2013.03.008},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Vegetable farms are one of many nitrogen (N) sources adversely affecting Lake Taihu in eastern China. Given the lack of quantitative “cause and effect” relationships and data relating to these systems, we developed a conceptual Bayesian network to investigate and demonstrate causal relationships and the effects of different mitigation strategies on N exports from vegetable farms in the Lake Taihu region. Structurally, the network comprised one primary transport factor, one primary source factor and three post-mobilisation strategies, and three output factors. In general the network suggests that N exports are more sensitive to transport factors (i.e. runoff volumes) than source factors (i.e. fertiliser application rates) although the cumulative effects of excessive fertiliser were not considered. Post-mobilisation mitigations such as wetlands and ecoditches appear to be particularly effective in decreasing N exports however their implementation on a regional scale may be limited by land availability. While optimising N inputs would be prudent, the network suggests that better irrigation practice, including improved irrigation scheduling, using less imported water and optimising rainfall utilisation would be more effective in achieving environmental goals than simply limiting N supply.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479712003921\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479712003921', event);\">\n    Facing uncertainty in ecosystem services-based resource management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grêt-Regamey,  A.; Brunner,  S., H.; Altwegg,  J.;  and Bebi,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 127 Suppl: S145-54. 9 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479712003921\"\n     onclick=\"log_download('grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479712003921', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Facing uncertainty in ecosystem services-based resource management. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2012.07.028\"\n     onclick=\"log_download('grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013', 'http://doi.org/10.1016/j.jenvman.2012.07.028', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grtregamey-brunner-altwegg-bebi-facinguncertaintyinecosystemservicesbasedresourcemanagement-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Facing uncertainty in ecosystem services-based resource management.},\n type = {article},\n year = {2013},\n keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Ecosystem,Uncertainty},\n pages = {S145-54},\n volume = {127 Suppl},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479712003921},\n month = {9},\n id = {fa8ccc4c-6586-33a7-afda-0ca728827b7c},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-03-26},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.},\n bibtype = {article},\n author = {Grêt-Regamey, Adrienne and Brunner, Sibyl H and Altwegg, Jürg and Bebi, Peter},\n doi = {10.1016/j.jenvman.2012.07.028},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713003472\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713003472', event);\">\n    Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Carmona,  G.; Varela-Ortega,  C.;  and Bromley,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 128: 400-12. 10 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713003472\"\n     onclick=\"log_download('carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713003472', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2013.05.019\"\n     onclick=\"log_download('carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013', 'http://doi.org/10.1016/j.jenvman.2013.05.019', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('carmona-varelaortega-bromley-participatorymodellingtosupportdecisionmakinginwatermanagementunderuncertaintytwocomparativecasestudiesintheguadianariverbasinspain-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain.},\n type = {article},\n year = {2013},\n keywords = {Agriculture,Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Consumer Participation,Decision Making,Income,Models, Economic,Models, Theoretical,Questionnaires,Rivers,Spain,Uncertainty},\n pages = {400-12},\n volume = {128},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713003472},\n month = {10},\n day = {15},\n id = {a4674948-9d5e-3785-a9c3-ed8069a4f597},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-03-20},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each other&#x27;s views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.},\n bibtype = {article},\n author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},\n doi = {10.1016/j.jenvman.2013.05.019},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each other's views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713001709\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713001709', event);\">\n    Bayesian Networks as a screening tool for exposure assessment.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tighe,  M.; Pollino,  C., A.;  and Wilson,  S., C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 123: 68-76. 7 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479713001709\"\n     onclick=\"log_download('tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013', 'http://www.sciencedirect.com/science/article/pii/S0301479713001709', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian Networks as a screening tool for exposure assessment. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2013.03.018\"\n     onclick=\"log_download('tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013', 'http://doi.org/10.1016/j.jenvman.2013.03.018', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tighe-pollino-wilson-bayesiannetworksasascreeningtoolforexposureassessment-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian Networks as a screening tool for exposure assessment.},\n type = {article},\n year = {2013},\n keywords = {Australia,Bayes Theorem,Environmental Exposure,Environmental Exposure: analysis,Risk Assessment,Risk Assessment: methods,Soil Pollutants,Soil Pollutants: analysis},\n pages = {68-76},\n volume = {123},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479713001709},\n month = {7},\n day = {15},\n id = {d1800489-6042-3851-87b8-ec9256ddcf34},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A tiered approach to contamination exposure assessment is currently adopted in many countries. Increasing the site-specific information in exposure assessments is generally recommended when guideline values for contaminants in soil are exceeded. This work details a Bayesian Network (BN) approach to developing a site-specific environmental exposure assessment that focuses on the simple mapping and assessment of assumptions and the effect of new data on assessment outcomes. The BN approach was applied to a floodplain system in New South Wales, Australia, where site-specific information about elevated antimony (Sb) concentrations and distribution in soils was available. Guidelines for exposure assessment in Australia are used as a template for this site, although the approach is generic. The BN-based assessment used an iterative approach starting with limited soil Sb data (41 samples ranging from 0 to 18 mg kg-(1) Sb) and extending the model with more detailed Sb data (145 samples ranging from 0 to 40 mg kg-(1) Sb). The analyses identified dominant exposure pathways and assessed the sensitivity of these pathways to changes in assumptions and the level of site-specific information available. In particular, there was a 10.8% probability of exceeding the tolerable daily intake of Sb in the case study when the limited soil Sb data was used, which increased to 26.2% with the more detailed sampling regime. There was also a 47% decrease in the probability of overexposure to Sb when the dermal bioavailability of arsenic (a similar metalloid) was used as a surrogate measure instead of a default bioavailability of 100%. We conclude that the BN approach to soil exposure assessment has merit both in the context of Australian and international soil exposure assessments.},\n bibtype = {article},\n author = {Tighe, Matthew and Pollino, Carmel A and Wilson, Susan C},\n doi = {10.1016/j.jenvman.2013.03.018},\n journal = {Journal of environmental management}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A tiered approach to contamination exposure assessment is currently adopted in many countries. Increasing the site-specific information in exposure assessments is generally recommended when guideline values for contaminants in soil are exceeded. This work details a Bayesian Network (BN) approach to developing a site-specific environmental exposure assessment that focuses on the simple mapping and assessment of assumptions and the effect of new data on assessment outcomes. The BN approach was applied to a floodplain system in New South Wales, Australia, where site-specific information about elevated antimony (Sb) concentrations and distribution in soils was available. Guidelines for exposure assessment in Australia are used as a template for this site, although the approach is generic. The BN-based assessment used an iterative approach starting with limited soil Sb data (41 samples ranging from 0 to 18 mg kg-(1) Sb) and extending the model with more detailed Sb data (145 samples ranging from 0 to 40 mg kg-(1) Sb). The analyses identified dominant exposure pathways and assessed the sensitivity of these pathways to changes in assumptions and the level of site-specific information available. In particular, there was a 10.8% probability of exceeding the tolerable daily intake of Sb in the case study when the limited soil Sb data was used, which increased to 26.2% with the more detailed sampling regime. There was also a 47% decrease in the probability of overexposure to Sb when the dermal bioavailability of arsenic (a similar metalloid) was used as a surrogate measure instead of a default bioavailability of 100%. We conclude that the BN approach to soil exposure assessment has merit both in the context of Australian and international soil exposure assessments.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213001151\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213001151', event);\">\n    Selecting among five common modelling approaches for integrated environmental assessment and management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kelly (Letcher),  R., A.; Jakeman,  A., J.; Barreteau,  O.; Borsuk,  M., E.; ElSawah,  S.; Hamilton,  S., H.; Henriksen,  H., J.; Kuikka,  S.; Maier,  H., R.; Rizzoli,  A., E.; van Delden,  H.;  and Voinov,  A., A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 47: 159-181. 9 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213001151\"\n     onclick=\"log_download('kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213001151', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Selecting among five common modelling approaches for integrated environmental assessment and management [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.05.005\"\n     onclick=\"log_download('kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013', 'http://doi.org/10.1016/j.envsoft.2013.05.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kellyletcher-jakeman-barreteau-borsuk-elsawah-hamilton-henriksen-kuikka-etal-selectingamongfivecommonmodellingapproachesforintegratedenvironmentalassessmentandmanagement-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Selecting among five common modelling approaches for integrated environmental assessment and management},\n type = {article},\n year = {2013},\n keywords = {Agent-based model,Bayesian network,Coupled component model,Integrated assessment,Knowledge-based model,System dynamics},\n pages = {159-181},\n volume = {47},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001151},\n month = {9},\n id = {383ca63b-e6ee-3feb-b63d-fdb7f82b957b},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2014-07-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.},\n bibtype = {article},\n author = {Kelly (Letcher), Rebecca A. and Jakeman, Anthony J. and Barreteau, Olivier and Borsuk, Mark E. and ElSawah, Sondoss and Hamilton, Serena H. and Henriksen, Hans Jørgen and Kuikka, Sakari and Maier, Holger R. and Rizzoli, Andrea Emilio and van Delden, Hedwig and Voinov, Alexey A.},\n doi = {10.1016/j.envsoft.2013.05.005},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002472\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002472', event);\">\n    Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fernandes,  J., A.; Lozano,  J., A.; Inza,  I.; Irigoien,  X.; Pérez,  A.;  and Rodríguez,  J., D.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 40: 245-254. 2 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002472\"\n     onclick=\"log_download('fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002472', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.10.001\"\n     onclick=\"log_download('fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013', 'http://doi.org/10.1016/j.envsoft.2012.10.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fernandes-lozano-inza-irigoien-prez-rodrguez-supervisedpreprocessingapproachesinmultipleclassvariablesclassificationforfishrecruitmentforecasting-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting},\n type = {article},\n year = {2013},\n keywords = {Bayesian networks,Discretization,Environmental modelling,Feature subset selection,Missing imputation,Multi-dimensional classification,Recruitment forecasting,Supervised classification},\n pages = {245-254},\n volume = {40},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002472},\n month = {2},\n id = {26edd41d-4cf1-369a-876f-85ee33da467a},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs.},\n bibtype = {article},\n author = {Fernandes, Jose A. and Lozano, Jose A. and Inza, Iñaki and Irigoien, Xabier and Pérez, Aritz and Rodríguez, Juan D.},\n doi = {10.1016/j.envsoft.2012.10.001},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A multi-species approach to fisheries management requires taking into account the interactions between species in order to improve recruitment forecasting of the fish species. Recent advances in Bayesian networks direct the learning of models with several interrelated variables to be forecasted simultaneously. These models are known as multi-dimensional Bayesian network classifiers (MDBNs). Pre-processing steps are critical for the posterior learning of the model in these kinds of domains. Therefore, in the present study, a set of ‘state-of-the-art’ uni-dimensional pre-processing methods, within the categories of missing data imputation, feature discretization and feature subset selection, are adapted to be used with MDBNs. A framework that includes the proposed multi-dimensional supervised pre-processing methods, coupled with a MDBN classifier, is tested with synthetic datasets and the real domain of fish recruitment forecasting. The correctly forecasting of three fish species (anchovy, sardine and hake) simultaneously is doubled (from 17.3% to 29.5%) using the multi-dimensional approach in comparison to mono-species models. The probability assessments also show high improvement reducing the average error (estimated by means of Brier score) from 0.35 to 0.27. Finally, these differences are superior to the forecasting of species by pairs.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001892\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212001892', event);\">\n    A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sun,  Z.;  and Müller,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 45: 15-28. 7 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001892\"\n     onclick=\"log_download('sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212001892', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.06.007\"\n     onclick=\"log_download('sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013', 'http://doi.org/10.1016/j.envsoft.2012.06.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sun-mller-aframeworkformodelingpaymentsforecosystemserviceswithagentbasedmodelsbayesianbeliefnetworksandopiniondynamicsmodels-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models},\n type = {article},\n year = {2013},\n keywords = {Agent based modeling,Bayesian network,China,Human–environment interaction,IAMO-LUC,Land use change,Payments for environmental services,Social influence},\n pages = {15-28},\n volume = {45},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001892},\n month = {7},\n id = {34614a54-fa08-3246-a72b-42712c6676c3},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem services. The model combines agent-based modeling (ABM) with Bayesian belief networks (BBNs) and opinion dynamics models (ODM). The model endows agents with the ability to make land-use decisions at the household and plot levels. The decision-making process is captured with the BBNs that were constructed and calibrated with both qualitative and quantitative information, i.e., knowledge gained from group discussions with stakeholders and empirical survey data. To represent interpersonal interactions within social networks, the decision process is further modulated by the opinion dynamics model. The goals of the model are to improve the ability of ABM to emulate land-use decision making and thus provide a better understanding of the potential impacts of payments for ecosystem services on land use and household livelihoods. Our approach provides three important innovations. First, decision making is represented in a causal directed graph. Second, the model provides a natural framework for combining knowledge from experts and stakeholders with quantitative data. Third, the modular architecture and the software implementation can be customized with modest efforts. The model is therefore a flexible, general platform that can be tailored to other studies by mounting the appropriate case-specific “brain” into the agents. The model was calibrated for the Sloping Land Conversion Program (SLCP) in Yunnan, China using data from participatory mapping, focus group interviews, and a survey of 509 farm households in 17 villages.},\n bibtype = {article},\n author = {Sun, Zhanli and Müller, Daniel},\n doi = {10.1016/j.envsoft.2012.06.007},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We present an integrated modeling framework for simulating land-use decision making under the influence of payments for ecosystem services. The model combines agent-based modeling (ABM) with Bayesian belief networks (BBNs) and opinion dynamics models (ODM). The model endows agents with the ability to make land-use decisions at the household and plot levels. The decision-making process is captured with the BBNs that were constructed and calibrated with both qualitative and quantitative information, i.e., knowledge gained from group discussions with stakeholders and empirical survey data. To represent interpersonal interactions within social networks, the decision process is further modulated by the opinion dynamics model. The goals of the model are to improve the ability of ABM to emulate land-use decision making and thus provide a better understanding of the potential impacts of payments for ecosystem services on land use and household livelihoods. Our approach provides three important innovations. First, decision making is represented in a causal directed graph. Second, the model provides a natural framework for combining knowledge from experts and stakeholders with quantitative data. Third, the modular architecture and the software implementation can be customized with modest efforts. The model is therefore a flexible, general platform that can be tailored to other studies by mounting the appropriate case-specific “brain” into the agents. The model was calibrated for the Sloping Land Conversion Program (SLCP) in Yunnan, China using data from participatory mapping, focus group interviews, and a survey of 509 farm households in 17 villages.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213001989\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213001989', event);\">\n    Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Carmona,  G.; Varela-Ortega,  C.;  and Bromley,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 50: 144-157. 12 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815213001989\"\n     onclick=\"log_download('carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815213001989', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2013.09.007\"\n     onclick=\"log_download('carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013', 'http://doi.org/10.1016/j.envsoft.2013.09.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('carmona-varelaortega-bromley-supportingdecisionmakingunderuncertaintydevelopmentofaparticipatoryintegratedmodelforwatermanagementinthemiddleguadianariverbasin-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Supporting decision making under uncertainty: Development of a participatory integrated model for water management in the middle Guadiana river basin},\n type = {article},\n year = {2013},\n keywords = {Bayesian networks,Crop model,Economic model,Integrated assessment modelling,Participatory modelling,Water management},\n pages = {144-157},\n volume = {50},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815213001989},\n month = {12},\n id = {1a722ac0-453f-34ff-8a7c-98fa9198e16f},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.},\n bibtype = {article},\n author = {Carmona, Gema and Varela-Ortega, Consuelo and Bromley, John},\n doi = {10.1016/j.envsoft.2013.09.007},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://www.sciencedirect.com/science/article/pii/S0925857413003224', event);\">\n    Analysis of topographic and vegetative factors with data mining for landslide verification.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tsai,  F.; Lai,  J.; Chen,  W., W.;  and Lin,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Engineering</i>, 61: 669-677. 12 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0925857413003224\"\n     onclick=\"log_download('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://www.sciencedirect.com/science/article/pii/S0925857413003224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Analysis of topographic and vegetative factors with data mining for landslide verification [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoleng.2013.07.070\"\n     onclick=\"log_download('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013', 'http://doi.org/10.1016/j.ecoleng.2013.07.070', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tsai-lai-chen-lin-analysisoftopographicandvegetativefactorswithdataminingforlandslideverification-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Analysis of topographic and vegetative factors with data mining for landslide verification},\n type = {article},\n year = {2013},\n keywords = {Bayesian Network,Data mining,Decision Tree,Landslide,Slope stability,Vegetation index},\n pages = {669-677},\n volume = {61},\n websites = {http://www.sciencedirect.com/science/article/pii/S0925857413003224},\n month = {12},\n id = {a79bd6e1-4460-3443-86c7-1e0dc4e4cd8c},\n created = {2015-04-12T20:17:33.000Z},\n accessed = {2015-03-03},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.},\n bibtype = {article},\n author = {Tsai, Fuan and Lai, Jhe-Syuan and Chen, Walter W. and Lin, Tang-Huang},\n doi = {10.1016/j.ecoleng.2013.07.070},\n journal = {Ecological Engineering}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This study employed data mining techniques to analyze topographic and vegetative factors for the verification of landslides induced by heavy rainfall in a regional scale in Taiwan. Decision Tree and Bayesian Network data mining algorithms were implemented to extract knowledge from supplied landslide factors. Eleven topographic and vegetative factors were considered for landslide analysis. In addition to individual factors derived from digital terrain model and satellite images, combined factors were also generated from data fusion. Landslide data of the study site collected between 2004 and 2007 were used to generate rules with data mining and to construct models of landslide factors. The constructed landslide factor models were used to verify landslide detections and to predict potential landslides. The prediction results of landslide events in 2008 were then verified against field-collected ground truth to evaluate the effectiveness of the models. In this study, topographic and vegetative parameters have been proven to be significant factors for landslides in the study site. Preliminary experimental results also indicate that the constructed models with data mining can achieve high accuracy in landslide detection. However, when directly applying the models for the prediction of potential landslides, the results were not reliable due to spatial uncertainties of the data. To address this issue, a statistics-based mechanism was developed to reduce data uncertainties. The results demonstrate that after reducing data uncertainties, the models can produce more reliable results of landslide prediction in the study site, as the kappa coefficients in the prediction were substantially increased by 29% using Decision Tree and by 20% using Bayesian Network algorithms, respectively.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002319', event);\">\n    Prediction analysis of a wastewater treatment system using a Bayesian network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  D.; Yang,  H., Z.;  and Liang,  X., F.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 40: 140-150.  2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212002319\"\n     onclick=\"log_download('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://www.sciencedirect.com/science/article/pii/S1364815212002319', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Prediction analysis of a wastewater treatment system using a Bayesian network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.08.011\"\n     onclick=\"log_download('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013', 'http://doi.org/10.1016/j.envsoft.2012.08.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-yang-liang-predictionanalysisofawastewatertreatmentsystemusingabayesiannetwork-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Prediction analysis of a wastewater treatment system using a Bayesian network},\n type = {article},\n year = {2013},\n keywords = {Bayesian network,Inference,Modified sequencing batch reactor,Prediction analysis},\n pages = {140-150},\n volume = {40},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212002319},\n id = {70c3be7f-ee3a-352b-9820-4656d9bbc625},\n created = {2015-04-22T21:19:07.000Z},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.},\n bibtype = {article},\n author = {Li, Dan and Yang, Hai Zhen and Liang, Xiao Feng},\n doi = {10.1016/j.envsoft.2012.08.011},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wastewater treatment is a complicated dynamic process, the effectiveness of which is affected by microbial, chemical, and physical factors. At present, predicting the effluent quality of wastewater treatment systems is difficult because of complex biological reaction mechanisms that vary with both time and the physical attributes of the system. Bayesian networks are useful for addressing uncertainties in artificial intelligence applications. Their powerful inferential capability and convenient decision support mechanisms provide flexibility and applicability for describing and analyzing factors affecting wastewater treatment systems. In this study, a Bayesian network-based approach for modeling and predicting a wastewater treatment system based on Modified Sequencing Batch Reactor (MSBR) was proposed. Using the presented approach, a Bayesian network model for MSBR can be constructed using experiential information and physical data relating to influent loads, operating conditions, and effluent concentrations. Additionally, MSBR prediction analysis, wherein effluent concentration can be predicted from influent loads and operational conditions, can be performed. This approach can be applied, with minimal modifications, to other types of wastewater treatment plants.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2012\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2012')\"\n      onkeypress=\"toggleGroup('group_2012')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2012</span>\n      <span class=\"bibbase_group_count\">\n        \n        (11)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"chen-pollino-goodpracticeinbayesiannetworkmodelling-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001041\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-pollino-goodpracticeinbayesiannetworkmodelling-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212001041', event);\">\n    Good practice in Bayesian network modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  S., H.;  and Pollino,  C., A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 37: 134-145. 11 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001041\"\n     onclick=\"log_download('chen-pollino-goodpracticeinbayesiannetworkmodelling-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212001041', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Good practice in Bayesian network modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.03.012\"\n     onclick=\"log_download('chen-pollino-goodpracticeinbayesiannetworkmodelling-2012', 'http://doi.org/10.1016/j.envsoft.2012.03.012', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-pollino-goodpracticeinbayesiannetworkmodelling-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-pollino-goodpracticeinbayesiannetworkmodelling-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Good practice in Bayesian network modelling},\n type = {article},\n year = {2012},\n keywords = {Bayes network,Bayesian belief network,Ecological models,Good modelling practice,Integration,Model evaluation},\n pages = {134-145},\n volume = {37},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001041},\n month = {11},\n id = {2b4fbce7-9e6c-3add-a5bb-c5edf47da7ec},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs) are increasingly being used to model environmental systems, in order to: integrate multiple issues and system components; utilise information from different sources; and handle missing data and uncertainty. BNs also have a modular architecture that facilitates iterative model development. For a model to be of value in generating and sharing knowledge or providing decision support, it must be built using good modelling practice. This paper provides guidelines to developing and evaluating Bayesian network models of environmental systems, and presents a case study habitat suitability model for juvenile Astacopsis gouldi, the giant freshwater crayfish of Tasmania. The guidelines entail clearly defining the model objectives and scope, and using a conceptual model of the system to form the structure of the BN, which should be parsimonious yet capture all key components and processes. After the states and conditional probabilities of all variables are defined, the BN should be assessed by a suite of quantitative and qualitative forms of model evaluation. All the assumptions, uncertainties, descriptions and reasoning for each node and linkage, data and information sources, and evaluation results must be clearly documented. Following these standards will enable the modelling process and the model itself to be transparent, credible and robust, within its given limitations.},\n bibtype = {article},\n author = {Chen, Serena H. and Pollino, Carmel A.},\n doi = {10.1016/j.envsoft.2012.03.012},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs) are increasingly being used to model environmental systems, in order to: integrate multiple issues and system components; utilise information from different sources; and handle missing data and uncertainty. BNs also have a modular architecture that facilitates iterative model development. For a model to be of value in generating and sharing knowledge or providing decision support, it must be built using good modelling practice. This paper provides guidelines to developing and evaluating Bayesian network models of environmental systems, and presents a case study habitat suitability model for juvenile Astacopsis gouldi, the giant freshwater crayfish of Tasmania. The guidelines entail clearly defining the model objectives and scope, and using a conceptual model of the system to form the structure of the BN, which should be parsimonious yet capture all key components and processes. After the states and conditional probabilities of all variables are defined, the BN should be assessed by a suite of quantitative and qualitative forms of model evaluation. All the assumptions, uncertainties, descriptions and reasoning for each node and linkage, data and information sources, and evaluation results must be clearly documented. Following these standards will enable the modelling process and the model itself to be transparent, credible and robust, within its given limitations.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380012000245\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012', 'http://www.sciencedirect.com/science/article/pii/S0304380012000245', event);\">\n    Metrics for evaluating performance and uncertainty of Bayesian network models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Marcot,  B., G.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 230: 50-62. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380012000245\"\n     onclick=\"log_download('marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012', 'http://www.sciencedirect.com/science/article/pii/S0304380012000245', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Metrics for evaluating performance and uncertainty of Bayesian network models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2012.01.013\"\n     onclick=\"log_download('marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012', 'http://doi.org/10.1016/j.ecolmodel.2012.01.013', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('marcot-metricsforevaluatingperformanceanduncertaintyofbayesiannetworkmodels-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Metrics for evaluating performance and uncertainty of Bayesian network models},\n type = {article},\n year = {2012},\n keywords = {AIC,AUC,Akaike information criterion,BIC,BN,Bayesian information criterion,Bayesian network,Bayesian network model,CPT,Error rates,GCM,GHG,Model performance,Model validation,PPCI,PPCIMIN,PPD,PPPCIMAX,Probability analysis,ROC,SP,Sensitivity analysis,TSS,Uncertainty,VR,area under the (receiver operating) curve,conditional probability table,global circulation model,greenhouse gas,maximum PPCI value given one or more state probabi,minimum PPCI value given one or more state probabi,posterior probability certainty index,posterior probability distribution,receiver operating characteristic (curve),spherical payoff,true skill statistic,variance reduction},\n pages = {50-62},\n volume = {230},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380012000245},\n month = {4},\n id = {3348523f-73e2-388c-a877-9d4052212f08},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-02-18},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model variables, links, node states, conditional probabilities, and node cliques); assessing prediction performance (confusion tables, covariate- and conditional probability-weighted confusion error rates, area under receiver operating characteristic curves, k-fold cross-validation, spherical payoff, Schwarz’ Bayesian information criterion, true skill statistic, Cohen&#x27;s kappa); and evaluating uncertainty of model posterior probability distributions (Bayesian credible interval, posterior probability certainty index, certainty envelope, Gini coefficient). Examples are presented of applying the metrics to 3 real-world models of wildlife population analysis and management. Using such metrics can vitally bolster model credibility, acceptance, and appropriate application, particularly when informing management decisions.},\n bibtype = {article},\n author = {Marcot, Bruce G.},\n doi = {10.1016/j.ecolmodel.2012.01.013},\n journal = {Ecological Modelling}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents a selected set of existing and new metrics for gauging Bayesian network model performance and uncertainty. Selected existing and new metrics are discussed for conducting model sensitivity analysis (variance reduction, entropy reduction, case file simulation); evaluating scenarios (influence analysis); depicting model complexity (numbers of model variables, links, node states, conditional probabilities, and node cliques); assessing prediction performance (confusion tables, covariate- and conditional probability-weighted confusion error rates, area under receiver operating characteristic curves, k-fold cross-validation, spherical payoff, Schwarz’ Bayesian information criterion, true skill statistic, Cohen's kappa); and evaluating uncertainty of model posterior probability distributions (Bayesian credible interval, posterior probability certainty index, certainty envelope, Gini coefficient). Examples are presented of applying the metrics to 3 real-world models of wildlife population analysis and management. Using such metrics can vitally bolster model credibility, acceptance, and appropriate application, particularly when informing management decisions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029612000631\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012', 'http://www.sciencedirect.com/science/article/pii/S1878029612000631', event);\">\n    Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kumar,  V.; Rouquette,  J.;  and Lerner,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Procedia Environmental Sciences</i>, 13: 687-697.  2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029612000631\"\n     onclick=\"log_download('kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012', 'http://www.sciencedirect.com/science/article/pii/S1878029612000631', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.proenv.2012.01.062\"\n     onclick=\"log_download('kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012', 'http://doi.org/10.1016/j.proenv.2012.01.062', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kumar-rouquette-lerner-integratedmodellingforsustainabilityappraisalforurbanrivercorridorredevelopment-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Integrated modelling for Sustainability Appraisal for Urban River Corridor (re)-development},\n type = {article},\n year = {2012},\n keywords = {Bayesian Network,Integrated Modelling,Sustainability Appraisal,Urban River Corridor},\n pages = {687-697},\n volume = {13},\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029612000631},\n id = {2267e51e-912e-347d-ac26-635682b9676f},\n created = {2015-04-11T19:52:14.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Sustainability Appraisal (SA) is mandatory under the relevant legislation of UK (DCLG, 2008a) and applies to the preparation of Regional Spatial Strategies, Development Plans and Supplementary Planning documents. SA is a complex task that involves integration of social, environmental and economic considerations into formal plans and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical assessment can facilitate discussion, but these can only partially inform decision makers as many important aspects of sustainability are abstract and not quantifiable. Such abstract criteria however can be modelled using a Bayesian Network (BN), combining expert opinions, empirical evidence and other information such as model simulation, survey etc. This paper discusses the work of the URSULA project at the University of Sheffield, in which a participative and integrative approach to urban river corridor development, incorporating the principal of sustainability was used. The project used a case study site in Sheffield, UK, and three alternative scenarios were developed, incorporating a number of possible riverside design features. Scenarios were fully designed and visualised using a variety of different media and a sustainability appraisal was undertaken using a broad range of environmental, social and economic indicators. Experts’ assessment logics were captured through mind mapping and further expert elicitation was used to develop an integrated model for SA. The BN approach allows model complexity to be reduced to a level appropriate for an assessment process, whilst still taking complex system interactions implicitly into account. The integrated SA model is being used to develop better design by optimising different design elements in order to deliver an optimum (re)-development plan.},\n bibtype = {article},\n author = {Kumar, Vikas and Rouquette, J.R. and Lerner, D.N.},\n doi = {10.1016/j.proenv.2012.01.062},\n journal = {Procedia Environmental Sciences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Sustainability Appraisal (SA) is mandatory under the relevant legislation of UK (DCLG, 2008a) and applies to the preparation of Regional Spatial Strategies, Development Plans and Supplementary Planning documents. SA is a complex task that involves integration of social, environmental and economic considerations into formal plans and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical assessment can facilitate discussion, but these can only partially inform decision makers as many important aspects of sustainability are abstract and not quantifiable. Such abstract criteria however can be modelled using a Bayesian Network (BN), combining expert opinions, empirical evidence and other information such as model simulation, survey etc. This paper discusses the work of the URSULA project at the University of Sheffield, in which a participative and integrative approach to urban river corridor development, incorporating the principal of sustainability was used. The project used a case study site in Sheffield, UK, and three alternative scenarios were developed, incorporating a number of possible riverside design features. Scenarios were fully designed and visualised using a variety of different media and a sustainability appraisal was undertaken using a broad range of environmental, social and economic indicators. Experts’ assessment logics were captured through mind mapping and further expert elicitation was used to develop an integrated model for SA. The BN approach allows model complexity to be reduced to a level appropriate for an assessment process, whilst still taking complex system interactions implicitly into account. The integrated SA model is being used to develop better design by optimising different design elements in order to deliver an optimum (re)-development plan.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029612005658\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012', 'http://www.sciencedirect.com/science/article/pii/S1878029612005658', event);\">\n    Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  H.; Zhang,  J.; Liu,  X.; Yan,  G.;  and Liu,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Procedia Environmental Sciences</i>, 16: 192-201.  2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029612005658\"\n     onclick=\"log_download('zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012', 'http://www.sciencedirect.com/science/article/pii/S1878029612005658', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.proenv.2012.10.027\"\n     onclick=\"log_download('zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012', 'http://doi.org/10.1016/j.proenv.2012.10.027', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-zhang-liu-yan-liu-researchonmethodofhealthassessmentaboutthedestructionequipmentforhighriskhazardouschemicalwaste-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Research on Method of Health Assessment about the Destruction Equipment for High-risk Hazardous Chemical Waste},\n type = {article},\n year = {2012},\n keywords = {Bayesian Networks,Destruc*tion equipment,Health assessment,Health status,High-risk hazardous chemical wastes},\n pages = {192-201},\n volume = {16},\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029612005658},\n id = {42ee5947-da27-3dba-9e58-0291cce06870},\n created = {2015-04-11T19:52:14.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.},\n bibtype = {article},\n author = {Zhang, Hongyuan and Zhang, Jing and Liu, Xuecheng and Yan, Guohui and Liu, Yanzhao},\n doi = {10.1016/j.proenv.2012.10.027},\n journal = {Procedia Environmental Sciences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The destroying tasks of high-risk hazardous chemical waste have a strict request to the health status of destruction equipment.The paper proposes the health status classification method based on time between failures for the destruction of equipment, set up health status assessment model based on Time-varying Bayesian Networks and the time slice, which can take advantage of history fault information and health status monitoring indicator information to health status assessment for the destruction equipment, and which provides a reliable and safe evaluation method.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479711003975\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012', 'http://www.sciencedirect.com/science/article/pii/S0301479711003975', event);\">\n    Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Holzkämper,  A.; Kumar,  V.; Surridge,  B., W., J.; Paetzold,  A.;  and Lerner,  D., N.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 96(1): 116-27. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479711003975\"\n     onclick=\"log_download('holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012', 'http://www.sciencedirect.com/science/article/pii/S0301479711003975', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2011.10.016\"\n     onclick=\"log_download('holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012', 'http://doi.org/10.1016/j.jenvman.2011.10.016', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('holzkmper-kumar-surridge-paetzold-lerner-bringingdiverseknowledgesourcestogetherametamodelforsupportingintegratedcatchmentmanagement-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management.},\n type = {article},\n year = {2012},\n keywords = {Bayes Theorem,Conservation of Natural Resources,Conservation of Natural Resources: methods,Decision Making,England,Environment,Knowledge,Models, Theoretical,Water},\n pages = {116-27},\n volume = {96},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479711003975},\n month = {4},\n day = {15},\n id = {1bf4dbe7-b7d0-3be6-833a-826220dea6f5},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.},\n bibtype = {article},\n author = {Holzkämper, Annelie and Kumar, Vikas and Surridge, Ben W J and Paetzold, Achim and Lerner, David N},\n doi = {10.1016/j.jenvman.2011.10.016},\n journal = {Journal of environmental management},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212000539\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212000539', event);\">\n    Assessing the likelihood of realizing idealized goals: The case of urban water strategies.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Moglia,  M.; Perez,  P.;  and Burn,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 35: 50-60. 7 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212000539\"\n     onclick=\"log_download('moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212000539', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing the likelihood of realizing idealized goals: The case of urban water strategies [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.02.005\"\n     onclick=\"log_download('moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012', 'http://doi.org/10.1016/j.envsoft.2012.02.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('moglia-perez-burn-assessingthelikelihoodofrealizingidealizedgoalsthecaseofurbanwaterstrategies-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessing the likelihood of realizing idealized goals: The case of urban water strategies},\n type = {article},\n year = {2012},\n keywords = {Bayesian Networks (BNs),Integrated Urban Water Management,Subjective logic,Water aid},\n pages = {50-60},\n volume = {35},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000539},\n month = {7},\n id = {db6775b2-898c-33e5-a3c2-14926129a6c5},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space.},\n bibtype = {article},\n author = {Moglia, M. and Perez, P. and Burn, S.},\n doi = {10.1016/j.envsoft.2012.02.005},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212000643\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212000643', event);\">\n    Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pérez-Miñana,  E.; Krause,  P.;  and Thornton,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 35: 132-148. 7 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212000643\"\n     onclick=\"log_download('prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212000643', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.02.016\"\n     onclick=\"log_download('prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012', 'http://doi.org/10.1016/j.envsoft.2012.02.016', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prezmiana-krause-thornton-bayesiannetworksforthemanagementofgreenhousegasemissionsinthebritishagriculturalsector-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian Networks for the management of greenhouse gas emissions in the British agricultural sector},\n type = {article},\n year = {2012},\n keywords = {Bayesian Networks,Environmental factors,GHG emissions},\n pages = {132-148},\n volume = {35},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212000643},\n month = {7},\n id = {822361c4-6f80-3309-bbdc-c61ee09777aa},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm&#x27;s capital income.},\n bibtype = {article},\n author = {Pérez-Miñana, E. and Krause, P.J. and Thornton, J.},\n doi = {10.1016/j.envsoft.2012.02.016},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm's capital income.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001648\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212001648', event);\">\n    Commentary: IUCN classifications under uncertainty.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Akçakaya,  H., R.; Ferson,  S.; Burgman,  M., A.; Keith,  D., A.; Mace,  G., M.;  and Todd,  C., R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 38: 119-121. 12 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815212001648\"\n     onclick=\"log_download('akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012', 'http://www.sciencedirect.com/science/article/pii/S1364815212001648', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Commentary: IUCN classifications under uncertainty [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2012.05.009\"\n     onclick=\"log_download('akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012', 'http://doi.org/10.1016/j.envsoft.2012.05.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('akakaya-ferson-burgman-keith-mace-todd-commentaryiucnclassificationsunderuncertainty-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Commentary: IUCN classifications under uncertainty},\n type = {article},\n year = {2012},\n keywords = {Bayesian networks,Fuzzy logic,IUCN,Red list,Threatened species,Uncertainty},\n pages = {119-121},\n volume = {38},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815212001648},\n month = {12},\n id = {5190ac37-462d-3614-8391-0495edf5bb3c},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15–23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data.},\n bibtype = {article},\n author = {Akçakaya, H. Reşit and Ferson, Scott and Burgman, Mark A. and Keith, David A. and Mace, Georgina M. and Todd, Charles R.},\n doi = {10.1016/j.envsoft.2012.05.009},\n journal = {Environmental Modelling &amp; Software}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We comment on a recent article by Newton (Environ. Model. Softw. (2010), 25, 15–23), which proposed a method, based on a Bayesian belief networks, for classifying the threat status of species under the IUCN Red List Categories and Criteria, and compared this method to an earlier one that we had developed that is based on fuzzy logic. There are three types of differences between the results of the two methods, the most consequential of which is different threat status categories assigned to some species for which the input data were uncertain. We demonstrate that the results obtained using the fuzzy logic approach are consistent with IUCN Red List criteria and guidelines. The application of Bayesian Networks to the IUCN Red List criteria to assist uncertain risk assessments may yet have merit. However, in order to be consistent with IUCN Red List assessments, applications of Bayesian approaches to actual Red List assessments would need an explicit and objective method for assigning likelihoods based on uncertain data.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S2210537912000492\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012', 'http://www.sciencedirect.com/science/article/pii/S2210537912000492', event);\">\n    Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Diamantopoulou,  M., J.\n</span>\n\n  \n\n</span>\n\n  <i>Sustainable Computing: Informatics and Systems</i>, 2(4): 190-197. 12 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S2210537912000492\"\n     onclick=\"log_download('diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012', 'http://www.sciencedirect.com/science/article/pii/S2210537912000492', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.suscom.2012.10.002\"\n     onclick=\"log_download('diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012', 'http://doi.org/10.1016/j.suscom.2012.10.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('diamantopoulou-assessingareliablemodelingapproachoffeaturesoftreesthroughneuralnetworkmodelsforsustainableforests-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessing a reliable modeling approach of features of trees through neural network models for sustainable forests},\n type = {article},\n year = {2012},\n keywords = {Bayesian networks,Cascade correlation,Kalman learning rule,Multi-layer perceptron,Sustainable forest management},\n pages = {190-197},\n volume = {2},\n websites = {http://www.sciencedirect.com/science/article/pii/S2210537912000492},\n month = {12},\n id = {26050b06-9c88-35aa-95c6-34e2f10db391},\n created = {2015-04-11T20:33:12.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Financial exploitation of forests comprises an important part of man activity. There are efforts being made to conserve the sustainable exploitation while simultaneously avoiding degradation of the environment. One tool used in these efforts is the modeling of tree features, such as total tree height, sawn-timber tree height, merchantable tree height, and total or sawn-timber tree volume, which yields an estimate of the forest in finance recoverable goods. Sustainable forest management design must be supported by the adjustment of computational techniques. The purpose of this paper is to assess a reliable modeling approach for estimating individual tree heights for the maturity of trees for logging through determining the applicability of different types of neural network models and identifying a neural network procedure for accurate estimation of these variables. These models serve as an alternative to the traditional regression approach. All types of model estimations are evaluated and compared in this paper. Back Propagation Artificial Neural Network (BPANN), Cascade Correlation Artificial Neural Network (CCANN), and Generalized Regression Neural Network (GRNN) models are developed to estimate individual tree heights for the logging of mature trees, such as sawn-timber height and merchantable height. The results reported in this research suggest that the selected BPANN and CCANN models are reliable and demonstrate their adequacy and potential for estimating sawn-timber and merchantable tree height. The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy. Moreover, the NN models were found to be superior to the tested nonlinear regression models.},\n bibtype = {article},\n author = {Diamantopoulou, Maria J.},\n doi = {10.1016/j.suscom.2012.10.002},\n journal = {Sustainable Computing: Informatics and Systems},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Financial exploitation of forests comprises an important part of man activity. There are efforts being made to conserve the sustainable exploitation while simultaneously avoiding degradation of the environment. One tool used in these efforts is the modeling of tree features, such as total tree height, sawn-timber tree height, merchantable tree height, and total or sawn-timber tree volume, which yields an estimate of the forest in finance recoverable goods. Sustainable forest management design must be supported by the adjustment of computational techniques. The purpose of this paper is to assess a reliable modeling approach for estimating individual tree heights for the maturity of trees for logging through determining the applicability of different types of neural network models and identifying a neural network procedure for accurate estimation of these variables. These models serve as an alternative to the traditional regression approach. All types of model estimations are evaluated and compared in this paper. Back Propagation Artificial Neural Network (BPANN), Cascade Correlation Artificial Neural Network (CCANN), and Generalized Regression Neural Network (GRNN) models are developed to estimate individual tree heights for the logging of mature trees, such as sawn-timber height and merchantable height. The results reported in this research suggest that the selected BPANN and CCANN models are reliable and demonstrate their adequacy and potential for estimating sawn-timber and merchantable tree height. The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy. Moreover, the NN models were found to be superior to the tested nonlinear regression models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971511000676\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012', 'http://www.sciencedirect.com/science/article/pii/S0198971511000676', event);\">\n    A mobility constraint model to infer sensor behaviour in forest fire risk monitoring.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ballari,  D.; Wachowicz,  M.; Bregt,  A., K.;  and Manso-Callejo,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Computers, Environment and Urban Systems</i>, 36(1): 81-95. 1 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971511000676\"\n     onclick=\"log_download('ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012', 'http://www.sciencedirect.com/science/article/pii/S0198971511000676', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A mobility constraint model to infer sensor behaviour in forest fire risk monitoring [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compenvurbsys.2011.06.004\"\n     onclick=\"log_download('ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012', 'http://doi.org/10.1016/j.compenvurbsys.2011.06.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ballari-wachowicz-bregt-mansocallejo-amobilityconstraintmodeltoinfersensorbehaviourinforestfireriskmonitoring-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A mobility constraint model to infer sensor behaviour in forest fire risk monitoring},\n type = {article},\n year = {2012},\n keywords = {Bayesian networks,Forest fire risk monitoring,Mobile wireless sensor network,Mobility constraints,Sensor behaviour,Spatial coverage},\n pages = {81-95},\n volume = {36},\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971511000676},\n month = {1},\n id = {d61193c0-c196-318b-ba47-9e2d44e37b7d},\n created = {2015-04-11T22:23:05.000Z},\n accessed = {2015-03-06},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.},\n bibtype = {article},\n author = {Ballari, Daniela and Wachowicz, Monica and Bregt, Arnold K. and Manso-Callejo, Miguel},\n doi = {10.1016/j.compenvurbsys.2011.06.004},\n journal = {Computers, Environment and Urban Systems},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320712001577\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012', 'http://www.sciencedirect.com/science/article/pii/S0006320712001577', event);\">\n    Bayesian networks and the quest for reserve adequacy.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schapaugh,  A., W.;  and Tyre,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Biological Conservation</i>, 152: 178-186. 8 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320712001577\"\n     onclick=\"log_download('schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012', 'http://www.sciencedirect.com/science/article/pii/S0006320712001577', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian networks and the quest for reserve adequacy [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.biocon.2012.03.014\"\n     onclick=\"log_download('schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012', 'http://doi.org/10.1016/j.biocon.2012.03.014', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schapaugh-tyre-bayesiannetworksandthequestforreserveadequacy-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian networks and the quest for reserve adequacy},\n type = {article},\n year = {2012},\n keywords = {Bayesian network,Interior least tern,Persistence,Piping plover,Reserve adequacy,Reserve selection,Stochastic dynamic programming,Whooping crane},\n pages = {178-186},\n volume = {152},\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320712001577},\n month = {8},\n id = {62641700-0260-3c6e-ac80-3a1604b60fdd},\n created = {2015-04-12T20:17:32.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. We describe a method that integrates correlates of persistence for multiple species into a single currency – site quality. Site quality is, in turn, an explicit measure of performance used in optimization. We develop a Bayesian network to assess site quality, which assigns an expected value to a property based on criteria arrayed into a causal diagram. We then use stochastic dynamic programming to determine whether an organization should acquire or reject a site placed on the public market. Our framework for assessing sites and making land acquisition decisions represents a compromise between the use of generic spatial design criteria and more intensive computational tools, like spatially-explicit population models. There is certainly a loss of precision by using site quality as a surrogate for more direct measures of persistence. However, we believe this simplification is defensible when sufficient data, expertise, or other resources are lacking.},\n bibtype = {article},\n author = {Schapaugh, Adam W. and Tyre, Andrew J.},\n doi = {10.1016/j.biocon.2012.03.014},\n journal = {Biological Conservation}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. We describe a method that integrates correlates of persistence for multiple species into a single currency – site quality. Site quality is, in turn, an explicit measure of performance used in optimization. We develop a Bayesian network to assess site quality, which assigns an expected value to a property based on criteria arrayed into a causal diagram. We then use stochastic dynamic programming to determine whether an organization should acquire or reject a site placed on the public market. Our framework for assessing sites and making land acquisition decisions represents a compromise between the use of generic spatial design criteria and more intensive computational tools, like spatially-explicit population models. There is certainly a loss of precision by using site quality as a surrogate for more direct measures of persistence. However, we believe this simplification is defensible when sufficient data, expertise, or other resources are lacking.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2011\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2011')\"\n      onkeypress=\"toggleGroup('group_2011')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2011</span>\n      <span class=\"bibbase_group_count\">\n        \n        (14)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211001022\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211001022', event);\">\n    Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Young,  W., A.; Millie,  D., F.; Weckman,  G., R.; Anderson,  J., S.; Klarer,  D., M.;  and Fahnenstiel,  G., L.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(10): 1199-1210. 10 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211001022\"\n     onclick=\"log_download('young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211001022', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2011.04.004\"\n     onclick=\"log_download('young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011', 'http://doi.org/10.1016/j.envsoft.2011.04.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('young-millie-weckman-anderson-klarer-fahnenstiel-modelingnetecosystemmetabolismwithanartificialneuralnetworkandbayesianbeliefnetwork-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network},\n type = {article},\n year = {2011},\n keywords = {Artificial neural networks,Bayesian belief networks,Knowledge extraction,Net ecosystem metabolism},\n pages = {1199-1210},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001022},\n month = {10},\n id = {9abb4fc4-588f-32bf-9854-9b2c13bed6e9},\n created = {2015-04-11T18:33:36.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.},\n bibtype = {article},\n author = {Young, William A. and Millie, David F. and Weckman, Gary R. and Anderson, Jerone S. and Klarer, David M. and Fahnenstiel, Gary L.},\n doi = {10.1016/j.envsoft.2011.04.004},\n journal = {Environmental Modelling &amp; Software},\n number = {10}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Artificial neural networks (ANNs) and Bayesian belief networks (BBNs) utilizing select environmental variables were developed and evaluated, with the intent to model net ecosystem metabolism (a proxy for system trophic state) within a freshwater wetland. Network modeling was completed independently for distinct data subsets, representing periods of ‘low’ and ‘high’ water levels throughout in the wetland. ANNs and BBNs were ‘benchmarked’ against traditional parametric analyses, with network architectures outperforming regression models. ANNs delivered the greatest predictive accuracy for NEM and did not require expert knowledge about system variables for their development. BBNs provided users with an interactive diagram depicting predictor interaction and the qualitative/quantitative effects of variable dynamics upon NEM, thereby affording better information extraction. Importantly, BBNs accommodated the imbalanced nature of the dataset and appeared less affected (than ANNs) with variable auto-correlation traits that are typically observed within large and ‘noisy’ environmental datasets.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210000915\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210000915', event);\">\n    Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ticehurst,  J.; Curtis,  A.;  and Merritt,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(1): 52-65. 1 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210000915\"\n     onclick=\"log_download('ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210000915', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2010.03.032\"\n     onclick=\"log_download('ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011', 'http://doi.org/10.1016/j.envsoft.2010.03.032', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ticehurst-curtis-merritt-usingbayesiannetworkstocomplementconventionalanalysestoexplorelandholdermanagementofnativevegetation-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation},\n type = {article},\n year = {2011},\n keywords = {Adoption,Bayesian Networks,Natural resource management,Policy development},\n pages = {52-65},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000915},\n month = {1},\n id = {d2c4459f-07d8-3c2d-bbfd-ea3722ab6385},\n created = {2015-04-11T19:51:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Influencing the management of private landholders is a key element of improving the condition of Australia’s natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.},\n bibtype = {article},\n author = {Ticehurst, J.L and Curtis, A. and Merritt, W.S.},\n doi = {10.1016/j.envsoft.2010.03.032},\n journal = {Environmental Modelling &amp; Software},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Influencing the management of private landholders is a key element of improving the condition of Australia’s natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S030438001000551X', event);\">\n    Combining state and transition models with dynamic Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nicholson,  A., E.;  and Flores,  M., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 222(3): 555-566. 2 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"\n     onclick=\"log_download('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S030438001000551X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Combining state and transition models with dynamic Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2010.10.010\"\n     onclick=\"log_download('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://doi.org/10.1016/j.ecolmodel.2010.10.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Combining state and transition models with dynamic Bayesian networks},\n type = {article},\n year = {2011},\n keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},\n pages = {555-566},\n volume = {222},\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},\n month = {2},\n id = {a7a054c9-1e05-3e86-8633-252c31c686f8},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},\n bibtype = {article},\n author = {Nicholson, Ann E. and Flores, M. Julia},\n doi = {10.1016/j.ecolmodel.2010.10.010},\n journal = {Ecological Modelling},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1574954111000045\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011', 'http://www.sciencedirect.com/science/article/pii/S1574954111000045', event);\">\n    A data mining approach to predictive vegetation mapping using probabilistic graphical models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Dlamini,  W., M.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Informatics</i>, 6(2): 111-124. 3 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1574954111000045\"\n     onclick=\"log_download('dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011', 'http://www.sciencedirect.com/science/article/pii/S1574954111000045', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A data mining approach to predictive vegetation mapping using probabilistic graphical models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecoinf.2010.12.005\"\n     onclick=\"log_download('dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011', 'http://doi.org/10.1016/j.ecoinf.2010.12.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dlamini-adataminingapproachtopredictivevegetationmappingusingprobabilisticgraphicalmodels-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A data mining approach to predictive vegetation mapping using probabilistic graphical models},\n type = {article},\n year = {2011},\n keywords = {Bayesian network,Data mining,Expectation-maximization,Graphical model,Predictive vegetation mapping},\n pages = {111-124},\n volume = {6},\n websites = {http://www.sciencedirect.com/science/article/pii/S1574954111000045},\n month = {3},\n id = {11a286ee-60c8-38cb-a2a6-634a98587984},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-02-16},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.},\n bibtype = {article},\n author = {Dlamini, Wisdom M.},\n doi = {10.1016/j.ecoinf.2010.12.005},\n journal = {Ecological Informatics},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper develops a novel method to model and predict the spatial distribution of vegetation types in Swaziland using physiographic and bioclimatic variables. The method uses a data mining approach implemented within a probabilistic graphical model to match two observed hierarchical levels of vegetation. The classification uses Bayesian networks (BN) and the parameterization is based on the expectation-maximization (EM) algorithm. The model is tested on a random sample of mapped vegetation types in Swaziland and allowed for the identification of the key environmental variables that are most important for capturing the vegetation spatial distribution. We show that while elevation and geology are the most important variables explaining the spatial distribution patterns of vegetation for both models, the influence of the climatic and other variables on the vegetation at the two levels differ. The overall distribution of the predicted vegetation classes was very similar to their distribution on the observed vegetation map. Overall the error rate was found to be 9.35% for a model of 16 vegetation classes and 4.9% for the one with 5 classes, indicating the excellent classification accuracy of the approach despite the complex landscape of the study area. Possible sources of error and some limitations are discussed and conclusions are drawn including suggestions for further investigation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X11004693\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011', 'http://www.sciencedirect.com/science/article/pii/S0025326X11004693', event);\">\n    A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lecklin,  T.; Ryömä,  R.;  and Kuikka,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Marine pollution bulletin</i>, 62(12): 2822-35. 12 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0025326X11004693\"\n     onclick=\"log_download('lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011', 'http://www.sciencedirect.com/science/article/pii/S0025326X11004693', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpolbul.2011.08.045\"\n     onclick=\"log_download('lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011', 'http://doi.org/10.1016/j.marpolbul.2011.08.045', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lecklin-rym-kuikka-abayesiannetworkforanalyzingbiologicalacuteandlongtermimpactsofanoilspillinthegulfoffinland-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network for analyzing biological acute and long-term impacts of an oil spill in the Gulf of Finland.},\n type = {article},\n year = {2011},\n keywords = {Animals,Aquatic Organisms,Aquatic Organisms: drug effects,Bayes Theorem,Computer Simulation,Environmental Monitoring,Environmental Monitoring: methods,Finland,Fresh Water,Fresh Water: chemistry,Models, Theoretical,Oceans and Seas,Petroleum,Petroleum Pollution,Petroleum: toxicity,Plants,Plants: drug effects,Population Dynamics,Reproduction,Species Specificity,Water Pollutants, Chemical,Water Pollutants, Chemical: chemistry,Water Pollutants, Chemical: toxicity},\n pages = {2822-35},\n volume = {62},\n websites = {http://www.sciencedirect.com/science/article/pii/S0025326X11004693},\n month = {12},\n id = {0cfe363b-d1c2-36b8-9ee4-3c0b8f3d308d},\n created = {2015-04-11T19:52:02.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.},\n bibtype = {article},\n author = {Lecklin, Tiina and Ryömä, Riitta and Kuikka, Sakari},\n doi = {10.1016/j.marpolbul.2011.08.045},\n journal = {Marine pollution bulletin},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Knowledge of oil-induced impacts from the literature and experts were used to develop a Bayesian network to evaluate the biological consequences of an oil accident in the low-saline Gulf of Finland (GOF). Analysis was carried out for selected groups of organisms. Subnetworks were divided into subgroups according to a predicted response to oil exposure. Two scenario analyses are presented: the most probable and the worst-case accident. The impact of the most probable accident in the GOF is rather small. In most of the groups studied oil-induced long-term effects are evaluated to be minor at least from the perspective of the whole GOF. After the worst-case accident negative effects are more likely. The model predicts that the most vulnerable groups are auks and ducks. Amphipods, gulls and to a lesser extend littoral fishes and seals may show delayed recovery after an accident. Also annual plant species may be susceptible to oil-induced disturbances.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0169204611000697\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011', 'http://www.sciencedirect.com/science/article/pii/S0169204611000697', event);\">\n    Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  McCloskey,  J., T.; Lilieholm,  R., J.;  and Cronan,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Landscape and Urban Planning</i>, 101(2): 190-203. 5 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0169204611000697\"\n     onclick=\"log_download('mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011', 'http://www.sciencedirect.com/science/article/pii/S0169204611000697', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.landurbplan.2011.02.011\"\n     onclick=\"log_download('mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011', 'http://doi.org/10.1016/j.landurbplan.2011.02.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mccloskey-lilieholm-cronan-usingbayesianbeliefnetworkstoidentifypotentialcompatibilitiesandconflictsbetweendevelopmentandlandscapeconservation-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Bayesian belief networks to identify potential compatibilities and conflicts between development and landscape conservation},\n type = {article},\n year = {2011},\n keywords = {Bayesian networks,Conservation,Development,GIS,Land use,Smart Growth},\n pages = {190-203},\n volume = {101},\n websites = {http://www.sciencedirect.com/science/article/pii/S0169204611000697},\n month = {5},\n id = {3d0bde03-c6af-3992-8432-3c72eef0f719},\n created = {2015-04-11T19:52:02.000Z},\n accessed = {2015-01-14},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine&#x27;s Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales.},\n bibtype = {article},\n author = {McCloskey, Jon T. and Lilieholm, Robert J. and Cronan, Christopher},\n doi = {10.1016/j.landurbplan.2011.02.011},\n journal = {Landscape and Urban Planning},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine's Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029611008954\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S1878029611008954', event);\">\n    A Trust Model Based on Cloud Model and Bayesian Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jin,  B.; Wang,  Y.; Liu,  Z.;  and Xue,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Procedia Environmental Sciences</i>, 11: 452-459.  2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029611008954\"\n     onclick=\"log_download('jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S1878029611008954', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Trust Model Based on Cloud Model and Bayesian Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.proenv.2011.12.072\"\n     onclick=\"log_download('jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011', 'http://doi.org/10.1016/j.proenv.2011.12.072', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jin-wang-liu-xue-atrustmodelbasedoncloudmodelandbayesiannetworks-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Trust Model Based on Cloud Model and Bayesian Networks},\n type = {article},\n year = {2011},\n keywords = {cloud model ;Bayesian network,context aware,trust model,unceratinty},\n pages = {452-459},\n volume = {11},\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029611008954},\n id = {832ba102-96b9-3e71-917e-fe967b5c591a},\n created = {2015-04-11T19:52:14.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.},\n bibtype = {article},\n author = {Jin, Bo and Wang, Yong and Liu, Zhenyan and Xue, Jingfeng},\n doi = {10.1016/j.proenv.2011.12.072},\n journal = {Procedia Environmental Sciences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  the Internet has been becoming the most important infrastructure for distributed applications which are composed of online services. In such open and dynamic environment, service selection becomes a challenge. The approaches based on subjective trust models are more adaptive and efficient than traditional binary logic based approaches. Most well known trust models use probability or fuzzy set theory to hold randomness or fuzziness respectively. Only cloud model based models consider both aspects of uncertainty. Although cloud model is ideal for representing trust degrees, it is not efficient for context aware trust evaluation and dynamic updates. By contrast, Bayesian network as an uncertain reasoning tool is more efficient for dynamic trust evaluation. An uncertain trust model that combines cloud model and Bayesian network is proposed in this paper.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029611001411\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011', 'http://www.sciencedirect.com/science/article/pii/S1878029611001411', event);\">\n    Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mustafaa,  Y.; Tolpekin,  V.;  and Stein,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Procedia Environmental Sciences</i>, 7: 74-79.  2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1878029611001411\"\n     onclick=\"log_download('mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011', 'http://www.sciencedirect.com/science/article/pii/S1878029611001411', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.proenv.2011.07.014\"\n     onclick=\"log_download('mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011', 'http://doi.org/10.1016/j.proenv.2011.07.014', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mustafaa-tolpekin-stein-applicationoftheemalgorithmforbayesiannetworkmodellingtoimproveforestgrowthestimates-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Application of the EM-algorithm for Bayesian Network Modelling to Improve Forest Growth Estimates},\n type = {article},\n year = {2011},\n keywords = {EM-algorithm,Gaussian Bayesian networks (GBNs),Moderate Resolution Imaging Spectroradiometer (MOD,leaf area index (LAI)},\n pages = {74-79},\n volume = {7},\n websites = {http://www.sciencedirect.com/science/article/pii/S1878029611001411},\n id = {499bacd1-d3b3-347b-8c68-3547a1cb097a},\n created = {2015-04-11T19:52:14.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Leaf area index (LAI) is a biophysical variable that is related to atmosphere-biosphere exchange of CO2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products (LAI MODIS). The LAI MODIS has been used to improve the physiological principles predicting growth (3-PG) model within a Bayesian Network (BN) set-up. The MODIS time series, however, contains gaps caused by persistent clouds, cloud contamination, and other retrieval problems. We therefore formulated the EM-algorithm to estimate the missing MODIS LAI values. The EM-algorithm is applied to three different cases: successive and not successive two winter seasons, and not successive missing MODIS LAI during the time study of 26 successive months at which the performance of the BN is assessed. Results show that the MODIS LAI is estimated such that the maximum value of the mean absolute error between the original MODIS LAI and the estimated MODIS LAI by EM-algorithm is 0.16. This is a low value, and shows the success of our approach. Moreover, the BN output improves when the EM-algorithm is carried out to estimate the inconsecutive missing MODIS LAI such that the root mean square error reduces from 1.57 to 1.49. We conclude that the EM-algorithm within a BN can handle the missing MODIS LAI values and that it improves estimation of the LAI.},\n bibtype = {article},\n author = {Mustafaa, Y.T. and Tolpekin, V. and Stein, A.},\n doi = {10.1016/j.proenv.2011.07.014},\n journal = {Procedia Environmental Sciences}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Leaf area index (LAI) is a biophysical variable that is related to atmosphere-biosphere exchange of CO2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical products (LAI MODIS). The LAI MODIS has been used to improve the physiological principles predicting growth (3-PG) model within a Bayesian Network (BN) set-up. The MODIS time series, however, contains gaps caused by persistent clouds, cloud contamination, and other retrieval problems. We therefore formulated the EM-algorithm to estimate the missing MODIS LAI values. The EM-algorithm is applied to three different cases: successive and not successive two winter seasons, and not successive missing MODIS LAI during the time study of 26 successive months at which the performance of the BN is assessed. Results show that the MODIS LAI is estimated such that the maximum value of the mean absolute error between the original MODIS LAI and the estimated MODIS LAI by EM-algorithm is 0.16. This is a low value, and shows the success of our approach. Moreover, the BN output improves when the EM-algorithm is carried out to estimate the inconsecutive missing MODIS LAI such that the root mean square error reduces from 1.57 to 1.49. We conclude that the EM-algorithm within a BN can handle the missing MODIS LAI values and that it improves estimation of the LAI.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210000940\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210000940', event);\">\n    An integrated approach to linking economic valuation and catchment modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kragt,  M.; Newham,  L.; Bennett,  J.;  and Jakeman,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(1): 92-102. 1 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210000940\"\n     onclick=\"log_download('kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210000940', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An integrated approach to linking economic valuation and catchment modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2010.04.002\"\n     onclick=\"log_download('kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011', 'http://doi.org/10.1016/j.envsoft.2010.04.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kragt-newham-bennett-jakeman-anintegratedapproachtolinkingeconomicvaluationandcatchmentmodelling-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An integrated approach to linking economic valuation and catchment modelling},\n type = {article},\n year = {2011},\n keywords = {Bayesian networks,Catchment scale modelling,Choice experiments,Environmental values,Integrated water resources management,Knowledge integration,Model development},\n pages = {92-102},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210000940},\n month = {1},\n id = {afa3520f-faa3-30b8-b122-20ad1cbb0bf7},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-03-02},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.},\n bibtype = {article},\n author = {Kragt, M.E. and Newham, L.T.H. and Bennett, J. and Jakeman, A.J.},\n doi = {10.1016/j.envsoft.2010.04.002},\n journal = {Environmental Modelling &amp; Software},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210002355\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210002355', event);\">\n    An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  \n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(2): 163-172. 2 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210002355\"\n     onclick=\"log_download('anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815210002355', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('anevaluationofautomatedstructurelearningwithbayesiannetworksanapplicationtoestuarinechlorophylldynamics-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics},\n type = {article},\n year = {2011},\n pages = {163-172},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210002355},\n month = {2},\n id = {b34304ce-36ef-3bbc-9b08-97f45089a527},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We develop a Bayesian network (BN) model that describes estuarine chlorophyll dynamics in the upper section of the Neuse River Estuary in North Carolina, using automated constraint based structure learning algorithms. We examine the functionality and usefulness of the structure learning algorithms in building model topology with real-time data under different scenarios. Generated BN models are evaluated and a final model is selected. Model results indicate that although the effect of water temperature and river flow on chlorophyll dynamics has remained unchanged following the implementation of the nitrogen Total Maximum Daily Load (TMDL) program; the response of chlorophyll levels to nutrient concentrations has been altered. The results stress the importance of incorporating expert defined constraints and links in conjunction with the automated structure learning algorithms to generate more plausible structures and minimize the sensitivity of the learning algorithms. This hybrid approach towards structure learning allows for the incorporation of existing knowledge while limiting the scope of the learning algorithms to defining the links between environmental variables for which the expert has little or no information.},\n bibtype = {article},\n author = {},\n journal = {Environmental Modelling &amp; Software},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We develop a Bayesian network (BN) model that describes estuarine chlorophyll dynamics in the upper section of the Neuse River Estuary in North Carolina, using automated constraint based structure learning algorithms. We examine the functionality and usefulness of the structure learning algorithms in building model topology with real-time data under different scenarios. Generated BN models are evaluated and a final model is selected. Model results indicate that although the effect of water temperature and river flow on chlorophyll dynamics has remained unchanged following the implementation of the nitrogen Total Maximum Daily Load (TMDL) program; the response of chlorophyll levels to nutrient concentrations has been altered. The results stress the importance of incorporating expert defined constraints and links in conjunction with the automated structure learning algorithms to generate more plausible structures and minimize the sensitivity of the learning algorithms. This hybrid approach towards structure learning allows for the incorporation of existing knowledge while limiting the scope of the learning algorithms to defining the links between environmental variables for which the expert has little or no information.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211000843\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211000843', event);\">\n    Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nash,  D.;  and Hannah,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(9): 1079-1088. 9 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211000843\"\n     onclick=\"log_download('nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211000843', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2011.03.009\"\n     onclick=\"log_download('nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011', 'http://doi.org/10.1016/j.envsoft.2011.03.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nash-hannah-usingmontecarlosimulationsandbayesiannetworkstoquantifyanddemonstratetheimpactoffertiliserbestmanagementpractices-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Monte-Carlo simulations and Bayesian Networks to quantify and demonstrate the impact of fertiliser best management practices},\n type = {article},\n year = {2011},\n keywords = {BMP,Bayesian Network,Best Management Practice,Best management practice,Fertiliser,Grazing,Monte-Carlo,P,Phosphorus,TP,Total Phosphorus},\n pages = {1079-1088},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211000843},\n month = {9},\n id = {39b2c2ec-c120-3402-9509-c0efa9004de8},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. &lt;10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results.},\n bibtype = {article},\n author = {Nash, David and Hannah, Murray},\n doi = {10.1016/j.envsoft.2011.03.009},\n journal = {Environmental Modelling &amp; Software},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Nutrient exports from agriculture contribute to eutrophication of rivers and lakes. In many jurisdictions “Best Management Practices” (BMP’s) are the cornerstone of mitigation efforts. In this paper we examine the use of Monte-Carlo simulations to combine fertiliser distribution, grazing and runoff data, and regression equations developed from field-scale monitoring, to estimate the maximal effect of fertiliser BMP’s on phosphorus (P) exports. The simulation data are then compared with a Bayesian Network that can be used to quickly evaluate the effects of different management scenarios on P exports and communicate those results to landholders. Both techniques demonstrate that for systems similar to those for which the regression equations were derived, improved fertiliser management is unlikely to have a major impact on Total P (TP) exports (i.e. <10%). While the contribution of fertiliser to TP exports in a general sense is relatively small, this study suggests that aberrant behaviour (i.e. fertiliser application immediately preceding rainfall runoff) can dramatically increase P exports. The major factor affecting TP exports appears to be the systematic or background P which includes native P and P from previously applied amendments. For communicating the effects of different management scenarios to landholders, Bayesian Networks are shown to be generally superior to Monte-Carlo techniques. However, the study suggests care is needed in selecting the states for the Bayesian Networks and demonstrates that at the extremes, the discretisation required by Bayesian Network software can produce misleading results.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211001472\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211001472', event);\">\n    Bayesian networks in environmental modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aguilera,  P.; Fernández,  A.; Fernández,  R.; Rumí,  R.;  and Salmerón,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 26(12): 1376-1388. 12 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815211001472\"\n     onclick=\"log_download('aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011', 'http://www.sciencedirect.com/science/article/pii/S1364815211001472', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian networks in environmental modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2011.06.004\"\n     onclick=\"log_download('aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011', 'http://doi.org/10.1016/j.envsoft.2011.06.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aguilera-fernndez-fernndez-rum-salmern-bayesiannetworksinenvironmentalmodelling-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian networks in environmental modelling},\n type = {article},\n year = {2011},\n keywords = {Bayesian networks,Environment,Model implementation,Review,Software},\n pages = {1376-1388},\n volume = {26},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815211001472},\n month = {12},\n id = {5fc3a716-77d9-3535-a52b-c3f36d379eee},\n created = {2015-04-11T19:52:28.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems. The goal of this review is to show how BNs are being used in environmental modelling. We are interested in the application of BNs, from January 1990 to December 2010, in the areas of the ISI Web of Knowledge related to Environmental Sciences. It is noted that only the 4.2% of the papers have been published under this item. The different steps that configure modelling via BNs have been revised: aim of the model, data pre-processing, model learning, validation and software. Our literature review indicates that BNs have barely been used for Environmental Science and their potential is, as yet, largely unexploited.},\n bibtype = {article},\n author = {Aguilera, P.A. and Fernández, A. and Fernández, R. and Rumí, R. and Salmerón, A.},\n doi = {10.1016/j.envsoft.2011.06.004},\n journal = {Environmental Modelling &amp; Software},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems. The goal of this review is to show how BNs are being used in environmental modelling. We are interested in the application of BNs, from January 1990 to December 2010, in the areas of the ISI Web of Knowledge related to Environmental Sciences. It is noted that only the 4.2% of the papers have been published under this item. The different steps that configure modelling via BNs have been revised: aim of the model, data pre-processing, model learning, validation and software. Our literature review indicates that BNs have barely been used for Environmental Science and their potential is, as yet, largely unexploited.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320710004763\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011', 'http://www.sciencedirect.com/science/article/pii/S0006320710004763', event);\">\n    State-and-transition modelling for Adaptive Management of native woodlands.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rumpff,  L.; Duncan,  D.; Vesk,  P.; Keith,  D.;  and Wintle,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Biological Conservation</i>, 144(4): 1224-1236. 4 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0006320710004763\"\n     onclick=\"log_download('rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011', 'http://www.sciencedirect.com/science/article/pii/S0006320710004763', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"State-and-transition modelling for Adaptive Management of native woodlands [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.biocon.2010.10.026\"\n     onclick=\"log_download('rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011', 'http://doi.org/10.1016/j.biocon.2010.10.026', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rumpff-duncan-vesk-keith-wintle-stateandtransitionmodellingforadaptivemanagementofnativewoodlands-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {State-and-transition modelling for Adaptive Management of native woodlands},\n type = {article},\n year = {2011},\n keywords = {Adaptive Management,Bayesian network,Native vegetation,Process model,Restoration,State-and-transition},\n pages = {1224-1236},\n volume = {144},\n websites = {http://www.sciencedirect.com/science/article/pii/S0006320710004763},\n month = {4},\n id = {eb2a4f53-5347-397e-90c4-cb09a8a9d2f0},\n created = {2015-04-12T20:17:32.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Adaptive Management (AM) is widely advocated as an approach to dealing with uncertainty in natural resource management as it provides an explicit framework for motivating, designing and interpreting the results of monitoring. One of the major factors impeding implementation is the failure to use appropriate process models; a core element of AM. Process models represent beliefs about the properties and dynamics of an ecological system and ecosystem responses to management. Quantitative models of ecosystem response help resolve ambiguity about the efficacy of management and facilitate iterative updating of knowledge using monitoring data. We report on the use of a state-and-transition model (STM) in the Adaptive Management of native woodland vegetation in south-eastern Australia. The STM is implemented as a Bayesian network, making it simple to communicate and update with new data as they arise. Application of the model is demonstrated using case-study and simulation data. We show how the model may be used to predict the probability of achieving desirable state transitions at restoration sites and how monitoring of those sites can be used to update the model (learn) and adapt (review restoration strategies). After just one monitoring/learning cycle, 7years after the first investments, we found that updated models predict markedly different transition probabilities compared with initial models based on expert opinion. This has strong implications for the apparent cost-efficiency of restoration strategies. The STM approach provides a sound theoretical basis for restoration decisions, while the Bayesian network implementation provides a workable framework for using the STM adaptively.},\n bibtype = {article},\n author = {Rumpff, L. and Duncan, D.H. and Vesk, P.A. and Keith, D.A. and Wintle, B.A.},\n doi = {10.1016/j.biocon.2010.10.026},\n journal = {Biological Conservation},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Adaptive Management (AM) is widely advocated as an approach to dealing with uncertainty in natural resource management as it provides an explicit framework for motivating, designing and interpreting the results of monitoring. One of the major factors impeding implementation is the failure to use appropriate process models; a core element of AM. Process models represent beliefs about the properties and dynamics of an ecological system and ecosystem responses to management. Quantitative models of ecosystem response help resolve ambiguity about the efficacy of management and facilitate iterative updating of knowledge using monitoring data. We report on the use of a state-and-transition model (STM) in the Adaptive Management of native woodland vegetation in south-eastern Australia. The STM is implemented as a Bayesian network, making it simple to communicate and update with new data as they arise. Application of the model is demonstrated using case-study and simulation data. We show how the model may be used to predict the probability of achieving desirable state transitions at restoration sites and how monitoring of those sites can be used to update the model (learn) and adapt (review restoration strategies). After just one monitoring/learning cycle, 7years after the first investments, we found that updated models predict markedly different transition probabilities compared with initial models based on expert opinion. This has strong implications for the apparent cost-efficiency of restoration strategies. The STM approach provides a sound theoretical basis for restoration decisions, while the Bayesian network implementation provides a workable framework for using the STM adaptively.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S030438001000551X', event);\">\n    Combining state and transition models with dynamic Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nicholson,  A., E.;  and Flores,  M., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 222(3): 555-566. 2 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S030438001000551X\"\n     onclick=\"log_download('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://www.sciencedirect.com/science/article/pii/S030438001000551X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Combining state and transition models with dynamic Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2010.10.010\"\n     onclick=\"log_download('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011', 'http://doi.org/10.1016/j.ecolmodel.2010.10.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nicholson-flores-combiningstateandtransitionmodelswithdynamicbayesiannetworks-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Combining state and transition models with dynamic Bayesian networks},\n type = {article},\n year = {2011},\n keywords = {Bayesian networks,Dynamic Bayesian networks,Rangeland management,State-and-transition models,System dynamics},\n pages = {555-566},\n volume = {222},\n websites = {http://www.sciencedirect.com/science/article/pii/S030438001000551X},\n month = {2},\n id = {2168ced9-6983-35c2-99f2-f939103c2901},\n created = {2015-04-12T20:17:35.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.},\n bibtype = {article},\n author = {Nicholson, Ann E. and Flores, M. Julia},\n doi = {10.1016/j.ecolmodel.2010.10.010},\n journal = {Ecological Modelling},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks – so-called dynamic Bayesian networks (DBNs) – for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2010\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2010')\"\n      onkeypress=\"toggleGroup('group_2010')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2010</span>\n      <span class=\"bibbase_group_count\">\n        \n        (12)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002035\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002035', event);\">\n    A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Dlamini,  W., M.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 25(2): 199-208. 2 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002035\"\n     onclick=\"log_download('dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002035', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2009.08.002\"\n     onclick=\"log_download('dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010', 'http://doi.org/10.1016/j.envsoft.2009.08.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dlamini-abayesianbeliefnetworkanalysisoffactorsinfluencingwildfireoccurrenceinswaziland-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland},\n type = {article},\n year = {2010},\n keywords = {Bayesian belief network,Geographic information system,Probabilistic inference,Swaziland,Wildfire},\n pages = {199-208},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002035},\n month = {2},\n id = {777ffc68-b80c-3b09-b39c-50d6de96dc04},\n created = {2015-04-11T15:45:45.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites&#x27; Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001–2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.},\n bibtype = {article},\n author = {Dlamini, Wisdom M.},\n doi = {10.1016/j.envsoft.2009.08.002},\n journal = {Environmental Modelling &amp; Software},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The impacts of wildfires on ecosystems and the factors contributing to their occurrence are increasingly receiving global attention. Advances in satellite remote sensing and information technology provide an opportunity to study these complex interrelationships. A Bayesian belief network (BBN) model was developed from a set of 12 biotic, abiotic and human variables to determine factors that influence wildfire activity in Swaziland using wildfire data from the Terra and Aqua satellites' Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2001–2007. These were geospatially integrated in the geographic information system (GIS) software ArcView and input into the software Netica for BBN analyses. Land cover, elevation, and climate (mean annual rainfall and mean annual temperature) were found to be strong predictors of wildfire occurrence, while aspect had the least influence on the wildfire occurrence. The model had a high predictive accuracy with an error rate of 9.62%, and an area under the receiver-operating characteristic (ROC) curve of 0.961. The study demonstrates how domain or field knowledge and limited empirical and GIS data can be combined within a BBN model to assist in determining key fire management interventions and lays the foundation for the future development of advanced and dynamic models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481520800220X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010', 'http://www.sciencedirect.com/science/article/pii/S136481520800220X', event);\">\n    Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Martínez-Santos,  P.; Henriksen,  H.; Zorrilla,  P.;  and Martínez-Alfaro,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 25(11): 1439-1449. 11 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481520800220X\"\n     onclick=\"log_download('martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010', 'http://www.sciencedirect.com/science/article/pii/S136481520800220X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2008.11.011\"\n     onclick=\"log_download('martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010', 'http://doi.org/10.1016/j.envsoft.2008.11.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('martnezsantos-henriksen-zorrilla-martnezalfaro-comparativereflectionsontheuseofmodellingtoolsinconflictivewatermanagementsettingsthemanchaoccidentalaquiferspain-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Comparative reflections on the use of modelling tools in conflictive water management settings: The Mancha Occidental aquifer, Spain},\n type = {article},\n year = {2010},\n keywords = {Aquifer,Bayesian belief networks,Groundwater modelling,Integrated assessment,Mancha Occidental,Participatory modelling},\n pages = {1439-1449},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481520800220X},\n month = {11},\n id = {27f510ec-0ee6-3836-ba11-331e4c3ce528},\n created = {2015-04-11T18:33:35.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Participatory methods provide an increasingly accepted path to integrated assessment. This paper reflects on the role of two participatory modelling initiatives implemented in a highly conflictive setting: the Mancha Occidental aquifer, Spain. The methodologies are described within the context of the case study, examining their potential relevance to integrated assessment from a conceptual standpoint. The strengths and weaknesses of each approach are analysed in absolute and relative terms, attending to the different stages of the modelling process. The focus then shifts to explore the implications of this work within the context of participatory integrated assessment and scenario analysis. This serves the purpose of establishing the reasons why the tools have been useful in the eyes of stakeholders, and how the case-specific findings of this project may be relevant to other settings.},\n bibtype = {article},\n author = {Martínez-Santos, P. and Henriksen, H.J. and Zorrilla, P. and Martínez-Alfaro, P.E.},\n doi = {10.1016/j.envsoft.2008.11.011},\n journal = {Environmental Modelling &amp; Software},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Participatory methods provide an increasingly accepted path to integrated assessment. This paper reflects on the role of two participatory modelling initiatives implemented in a highly conflictive setting: the Mancha Occidental aquifer, Spain. The methodologies are described within the context of the case study, examining their potential relevance to integrated assessment from a conceptual standpoint. The strengths and weaknesses of each approach are analysed in absolute and relative terms, attending to the different stages of the modelling process. The focus then shifts to explore the implications of this work within the context of participatory integrated assessment and scenario analysis. This serves the purpose of establishing the reasons why the tools have been useful in the eyes of stakeholders, and how the case-specific findings of this project may be relevant to other settings.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002618\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002618', event);\">\n    Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lynam,  T.; Drewry,  J.; Higham,  W.;  and Mitchell,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 25(11): 1291-1301. 11 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002618\"\n     onclick=\"log_download('lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002618', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2009.09.013\"\n     onclick=\"log_download('lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010', 'http://doi.org/10.1016/j.envsoft.2009.09.013', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lynam-drewry-higham-mitchell-adaptivemodellingforadaptivewaterqualitymanagementinthegreatbarrierreefregionaustralia-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia},\n type = {article},\n year = {2010},\n keywords = {Adaptive management,Adaptive modelling,Bayesian Belief Network,Great Barrier Reef,Learning support,Water quality},\n pages = {1291-1301},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002618},\n month = {11},\n id = {9e63a1d1-b78a-3e51-8c45-3f012125a461},\n created = {2015-04-11T19:07:35.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The development and use of a Bayesian Belief Network (BBN) model, within an adaptive management process for the management of water quality in the Mackay Whitsunday region of Queensland, Australia is described. The management goal is firstly to set achievable targets for water quality entering the Great Barrier Reef lagoon from the Mackay Whitsunday natural resource management region and then secondly to define and implement a strategy to achieve these targets. The BBN serves as an adaptive framework that managers and scientists may use to articulate what they know about the managed system. It then provides a tool to guide where, when and what interventions (including research) are most likely to achieve management outcomes. Importantly the BBN provides a platform for collective learning. BBN estimates of total suspended sediment (TSS) loads and event mean concentrations (EMCs) were compared to observed data and results from current best practice models. The BBN estimates were reasonable relative to empirical observations. Example results from the BBN are thereafter used to illustrate the use of the model in estimating the likelihood of exceeding water quality targets with and without proposed actions to improve water quality. Example results are also used to illustrate what spatial or land use elements might contribute most to exceeding water quality targets. Finally key limitations of the tool are discussed and important learnings from the process are highlighted.},\n bibtype = {article},\n author = {Lynam, Tim and Drewry, John and Higham, Will and Mitchell, Carl},\n doi = {10.1016/j.envsoft.2009.09.013},\n journal = {Environmental Modelling &amp; Software},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The development and use of a Bayesian Belief Network (BBN) model, within an adaptive management process for the management of water quality in the Mackay Whitsunday region of Queensland, Australia is described. The management goal is firstly to set achievable targets for water quality entering the Great Barrier Reef lagoon from the Mackay Whitsunday natural resource management region and then secondly to define and implement a strategy to achieve these targets. The BBN serves as an adaptive framework that managers and scientists may use to articulate what they know about the managed system. It then provides a tool to guide where, when and what interventions (including research) are most likely to achieve management outcomes. Importantly the BBN provides a platform for collective learning. BBN estimates of total suspended sediment (TSS) loads and event mean concentrations (EMCs) were compared to observed data and results from current best practice models. The BBN estimates were reasonable relative to empirical observations. Example results from the BBN are thereafter used to illustrate the use of the model in estimating the likelihood of exceeding water quality targets with and without proposed actions to improve water quality. Example results are also used to illustrate what spatial or land use elements might contribute most to exceeding water quality targets. Finally key limitations of the tool are discussed and important learnings from the process are highlighted.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380009007947', event);\">\n    Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  S.; Mengersen,  K.; de Waal,  A.; Marnewick,  K.; Cilliers,  D.; Houser,  A., M.;  and Boast,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 221(4): 641-651. 2 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009007947\"\n     onclick=\"log_download('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380009007947', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2009.11.012\"\n     onclick=\"log_download('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010', 'http://doi.org/10.1016/j.ecolmodel.2009.11.012', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-mengersen-dewaal-marnewick-cilliers-houser-boast-modellingcheetahrelocationsuccessinsouthernafricausinganiterativebayesiannetworkdevelopmentcycle-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle},\n type = {article},\n year = {2010},\n keywords = {Acinonyx jubatus,Bayesian network,Cheetah metapopulation,IBNDC,Iterative approach,Predator human conflict,Relocation},\n pages = {641-651},\n volume = {221},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009007947},\n month = {2},\n id = {efbda3bc-67d8-309a-8188-fee0c8a80d3b},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.},\n bibtype = {article},\n author = {Johnson, Sandra and Mengersen, Kerrie and de Waal, Alta and Marnewick, Kelly and Cilliers, Deon and Houser, Ann Marie and Boast, Lorraine},\n doi = {10.1016/j.ecolmodel.2009.11.012},\n journal = {Ecological Modelling},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380010003777', event);\">\n    Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liedloff,  A., C.;  and Smith,  C., S.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 221(21): 2565-2575. 10 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"\n     onclick=\"log_download('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380010003777', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Predicting a ‘tree change’ in Australia&#x27;s tropical savannas: Combining different types of models to understand complex ecosystem behaviour [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2010.07.022\"\n     onclick=\"log_download('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://doi.org/10.1016/j.ecolmodel.2010.07.022', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predicting a ‘tree change’ in Australia&#x27;s tropical savannas: Combining different types of models to understand complex ecosystem behaviour},\n type = {article},\n year = {2010},\n keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},\n pages = {2565-2575},\n volume = {221},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},\n month = {10},\n id = {90ca0fff-a0db-3b88-a996-692a49ce2441},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia&#x27;s tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},\n bibtype = {article},\n author = {Liedloff, Adam C. and Smith, Carl S.},\n doi = {10.1016/j.ecolmodel.2010.07.022},\n journal = {Ecological Modelling},\n number = {21}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377409003576\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010', 'http://www.sciencedirect.com/science/article/pii/S0378377409003576', event);\">\n    Negotiating participatory irrigation management in the Indian Himalayas.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Saravanan,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Water Management</i>, 97(5): 651-658. 5 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377409003576\"\n     onclick=\"log_download('saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010', 'http://www.sciencedirect.com/science/article/pii/S0378377409003576', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Negotiating participatory irrigation management in the Indian Himalayas [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agwat.2009.12.003\"\n     onclick=\"log_download('saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010', 'http://doi.org/10.1016/j.agwat.2009.12.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('saravanan-negotiatingparticipatoryirrigationmanagementintheindianhimalayas-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Negotiating participatory irrigation management in the Indian Himalayas},\n type = {article},\n year = {2010},\n keywords = {Bayesian network,Institutional integration,Integrated water management,Policy modelling,South Asia},\n pages = {651-658},\n volume = {97},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377409003576},\n month = {5},\n id = {03d55546-ca56-351b-b7a8-66ee6994cadc},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-03-31},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Participatory irrigation management (PIM) reforms are implemented in India to facilitate farmers’ participation in irrigation management, through water user groups. Although thousands of user groups have been formed, a closer examination reveals inefficient water use, social power capture by rural elites in the name of participation, inadequate support from government institutions and government&#x27;s inability to alleviate poverty. Currently, there is inadequate understanding of the linkage between socio-cultural, institutional and ecological factors affecting the outcome of the PIM reforms in India. Drawing from a case study village in the Shiwalik region of the Indian Himalayas, the paper identifies the role of diverse actors to exploit historic and ecological factors to derail the PIM reforms to frame water management problems. Using a combination of research methods and with application of a Bayesian network, the paper explores the inter-linkages between socio-cultural, institutional and ecological factors in derailing the PIM reforms. The paper reveals that PIM policies are never implemented, but integrated through the negotiation with other diverse policies and socio-cultural settings in (re)shaping water resources management. The analysis demonstrates that water is managed by multifaceted governance arrangements. In this governance arrangement state-centric or market-oriented or community-centered institutional arrangements are not superior to each other, rather they incrementally and cumulatively superimpose to (re)shape water resources management. In this process, integration represents a complex blend of statutory and socially embedded actors bringing with them diverse rules to negotiate, along with contextual factors. The findings call for laying out broad principles/ideologies in the policy statements of the statutory public actors that allow other actors to integrate, adapt and make policy processes dynamic. To facilitate this processes, the paper calls for statutory public actors to regulate water distribution, build capacity of actors and offer diverse forums for actors share and debate on the available information to take informed water-related decisions for a sustainable future.},\n bibtype = {article},\n author = {Saravanan, V.S.},\n doi = {10.1016/j.agwat.2009.12.003},\n journal = {Agricultural Water Management},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Participatory irrigation management (PIM) reforms are implemented in India to facilitate farmers’ participation in irrigation management, through water user groups. Although thousands of user groups have been formed, a closer examination reveals inefficient water use, social power capture by rural elites in the name of participation, inadequate support from government institutions and government's inability to alleviate poverty. Currently, there is inadequate understanding of the linkage between socio-cultural, institutional and ecological factors affecting the outcome of the PIM reforms in India. Drawing from a case study village in the Shiwalik region of the Indian Himalayas, the paper identifies the role of diverse actors to exploit historic and ecological factors to derail the PIM reforms to frame water management problems. Using a combination of research methods and with application of a Bayesian network, the paper explores the inter-linkages between socio-cultural, institutional and ecological factors in derailing the PIM reforms. The paper reveals that PIM policies are never implemented, but integrated through the negotiation with other diverse policies and socio-cultural settings in (re)shaping water resources management. The analysis demonstrates that water is managed by multifaceted governance arrangements. In this governance arrangement state-centric or market-oriented or community-centered institutional arrangements are not superior to each other, rather they incrementally and cumulatively superimpose to (re)shape water resources management. In this process, integration represents a complex blend of statutory and socially embedded actors bringing with them diverse rules to negotiate, along with contextual factors. The findings call for laying out broad principles/ideologies in the policy statements of the statutory public actors that allow other actors to integrate, adapt and make policy processes dynamic. To facilitate this processes, the paper calls for statutory public actors to regulate water distribution, build capacity of actors and offer diverse forums for actors share and debate on the available information to take informed water-related decisions for a sustainable future.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308597X09001626\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010', 'http://www.sciencedirect.com/science/article/pii/S0308597X09001626', event);\">\n    Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Haapasaari,  P.;  and Karjalainen,  T., P.\n</span>\n\n  \n\n</span>\n\n  <i>Marine Policy</i>, 34(3): 477-486. 5 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308597X09001626\"\n     onclick=\"log_download('haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010', 'http://www.sciencedirect.com/science/article/pii/S0308597X09001626', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marpol.2009.10.002\"\n     onclick=\"log_download('haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010', 'http://doi.org/10.1016/j.marpol.2009.10.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('haapasaari-karjalainen-formalizingexpertknowledgetocomparealternativemanagementplanssociologicalperspectivetothefuturemanagementofbalticsalmonstocks-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Formalizing expert knowledge to compare alternative management plans: Sociological perspective to the future management of Baltic salmon stocks},\n type = {article},\n year = {2010},\n keywords = {Baltic salmon,Bayesian network,Commitment,Expert knowledge,Implementation uncertainty,Management plan,Stakeholders},\n pages = {477-486},\n volume = {34},\n websites = {http://www.sciencedirect.com/science/article/pii/S0308597X09001626},\n month = {5},\n id = {a30b55db-89e3-3dc7-852c-22231aaba337},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.},\n bibtype = {article},\n author = {Haapasaari, Päivi and Karjalainen, Timo P.},\n doi = {10.1016/j.marpol.2009.10.002},\n journal = {Marine Policy},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Designing and implementing long-term management plans is difficult both because of the complexity of the fisheries system, and the behaviour of humans. We compared four alternative management plans for the Baltic salmon stocks through approaching experts who interpreted and expressed the views of different stakeholder groups on the options. The focus of the study was on stakeholders’ commitment to the alternative management plans. Committing enhances the probability of achieving the ultimate objective of a plan, while if stakeholders do not commit, the effects of the plan may be less predictable. Thus commitment is an important part of implementation uncertainty in fisheries management. We present how we coupled qualitative analysis with probabilistic Bayesian networks in analysing expert knowledge related to alternative long term management plans in terms of group commitment. Using a Bayesian net provides potential for creating a holistic picture of a fishery by combining the data describing fishers’ commitment with biological data regarding fish stock dynamics and with economic data analyzing economically sound fisheries management.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0141113609001032\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010', 'http://www.sciencedirect.com/science/article/pii/S0141113609001032', event);\">\n    An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  S.; Fielding,  F.; Hamilton,  G.;  and Mengersen,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Marine Environmental Research</i>, 69(1): 27-37. 2 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0141113609001032\"\n     onclick=\"log_download('johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010', 'http://www.sciencedirect.com/science/article/pii/S0141113609001032', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.marenvres.2009.07.004\"\n     onclick=\"log_download('johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010', 'http://doi.org/10.1016/j.marenvres.2009.07.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-fielding-hamilton-mengersen-anintegratedbayesiannetworkapproachtolyngbyamajusculabloominitiation-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An Integrated Bayesian Network approach to Lyngbya majuscula bloom initiation},\n type = {article},\n year = {2010},\n keywords = {Bayesian network,Cyanobacteria,DOOBN,Dynamic,IBN,Lyngbya majuscula,OOBN,Object oriented},\n pages = {27-37},\n volume = {69},\n websites = {http://www.sciencedirect.com/science/article/pii/S0141113609001032},\n month = {2},\n id = {32672e3a-e7fd-34b5-befa-92b0a26378f9},\n created = {2015-04-11T19:52:18.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Blooms of the cyanobacteria Lyngbya majuscula have occurred for decades around the world. However, with the increase in size and frequency of these blooms, coupled with the toxicity of such algae and their increased biomass, they have become substantial environmental and health issues. It is therefore imperative to develop a better understanding of the scientific and management factors impacting on Lyngbya bloom initiation. This paper suggests an Integrated Bayesian Network (IBN) approach that facilitates the merger of the research being conducted by various parties on Lyngbya. Pivotal to this approach are two Bayesian networks modelling the management and scientific factors of bloom initiation. The research found that Bayesian Networks (BN) and specifically Object Oriented BNs (OOBN) and Dynamic OOBNs facilitate an integrated approach to modelling ecological issues of concern. The merger of multiple models which explore different aspects of the problem through an IBN approach can apply to many multi-faceted environmental problems.},\n bibtype = {article},\n author = {Johnson, Sandra and Fielding, Fiona and Hamilton, Grant and Mengersen, Kerrie},\n doi = {10.1016/j.marenvres.2009.07.004},\n journal = {Marine Environmental Research},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Blooms of the cyanobacteria Lyngbya majuscula have occurred for decades around the world. However, with the increase in size and frequency of these blooms, coupled with the toxicity of such algae and their increased biomass, they have become substantial environmental and health issues. It is therefore imperative to develop a better understanding of the scientific and management factors impacting on Lyngbya bloom initiation. This paper suggests an Integrated Bayesian Network (IBN) approach that facilitates the merger of the research being conducted by various parties on Lyngbya. Pivotal to this approach are two Bayesian networks modelling the management and scientific factors of bloom initiation. The research found that Bayesian Networks (BN) and specifically Object Oriented BNs (OOBN) and Dynamic OOBNs facilitate an integrated approach to modelling ecological issues of concern. The merger of multiple models which explore different aspects of the problem through an IBN approach can apply to many multi-faceted environmental problems.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002679\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002679', event);\">\n    Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Molina,  J.; Bromley,  J.; García-Aróstegui,  J.; Sullivan,  C.;  and Benavente,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 25(4): 383-397. 4 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209002679\"\n     onclick=\"log_download('molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815209002679', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2009.10.007\"\n     onclick=\"log_download('molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010', 'http://doi.org/10.1016/j.envsoft.2009.10.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('molina-bromley-garcaarstegui-sullivan-benavente-integratedwaterresourcesmanagementofoverexploitedhydrogeologicalsystemsusingobjectorientedbayesiannetworks-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Integrated water resources management of overexploited hydrogeological systems using Object-Oriented Bayesian Networks},\n type = {article},\n year = {2010},\n keywords = {Aquifer overexploitation,Decision support systems,Integrated water management,Object-Oriented Bayesian Networks,Stakeholders&#x27; engagement},\n pages = {383-397},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209002679},\n month = {4},\n id = {3b9044a5-6c1e-392d-8748-0ccc0a0747f5},\n created = {2015-04-11T19:52:26.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Object-Oriented Bayesian Networks (OOBNs) have been used increasingly over the past few decades in fields as diverse as medicine, transport and aeronautics. In this paper, OOBNs are applied to the domain of integrated water management and used as a Decision Support System (DSS). This pioneering study, set in the Altiplano region of Murcia in Southern Spain, describes a method for the integrated analysis of a complex water system supplied by groundwater from four aquifers. This method is based on the development of a multivariable integrated technique based on Bayes&#x27; theorem. After identifying all relevant factors related to water management in the area these were then translated to variables within a Bayesian Network (BN) and the relationships between them investigated. Each network represented one of the four aquifer units. These individual BNs were then linked to form an OOBN which was used to represent the complex real-world situation. In this way a DSS to simulate the entire water system was constructed using a group of conventional Bns, linked to produce an OOBN. The main stakeholders of the region contributed to network design and construction throughout the entire process. The paper shows how this type of DSS can be used to evaluate the impacts of a range of management strategies that are available to local planners.},\n bibtype = {article},\n author = {Molina, J.L. and Bromley, J. and García-Aróstegui, J.L. and Sullivan, C. and Benavente, J.},\n doi = {10.1016/j.envsoft.2009.10.007},\n journal = {Environmental Modelling &amp; Software},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Object-Oriented Bayesian Networks (OOBNs) have been used increasingly over the past few decades in fields as diverse as medicine, transport and aeronautics. In this paper, OOBNs are applied to the domain of integrated water management and used as a Decision Support System (DSS). This pioneering study, set in the Altiplano region of Murcia in Southern Spain, describes a method for the integrated analysis of a complex water system supplied by groundwater from four aquifers. This method is based on the development of a multivariable integrated technique based on Bayes' theorem. After identifying all relevant factors related to water management in the area these were then translated to variables within a Bayesian Network (BN) and the relationships between them investigated. Each network represented one of the four aquifer units. These individual BNs were then linked to form an OOBN which was used to represent the complex real-world situation. In this way a DSS to simulate the entire water system was constructed using a group of conventional Bns, linked to produce an OOBN. The main stakeholders of the region contributed to network design and construction throughout the entire process. The paper shows how this type of DSS can be used to evaluate the impacts of a range of management strategies that are available to local planners.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210001222\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815210001222', event);\">\n    Hybrid Bayesian network classifiers: Application to species distribution models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aguilera,  P.; Fernández,  A.; Reche,  F.;  and Rumí,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 25(12): 1630-1639. 12 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815210001222\"\n     onclick=\"log_download('aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010', 'http://www.sciencedirect.com/science/article/pii/S1364815210001222', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Hybrid Bayesian network classifiers: Application to species distribution models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2010.04.016\"\n     onclick=\"log_download('aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010', 'http://doi.org/10.1016/j.envsoft.2010.04.016', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aguilera-fernndez-reche-rum-hybridbayesiannetworkclassifiersapplicationtospeciesdistributionmodels-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Hybrid Bayesian network classifiers: Application to species distribution models},\n type = {article},\n year = {2010},\n keywords = {Classification,Conservation planning,Hybrid Bayesian networks,Mixtures of truncated exponentials},\n pages = {1630-1639},\n volume = {25},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815210001222},\n month = {12},\n id = {d0abd407-543b-3e72-a742-dc64d2f0e3ec},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks are one of the most powerful tools in the design of expert systems located in an uncertainty framework. However, normally their application is determined by the discretization of the continuous variables. In this paper the naïve Bayes (NB) and tree augmented naïve Bayes (TAN) models are developed. They are based on Mixtures of Truncated Exponentials (MTE) designed to deal with discrete and continuous variables in the same network simultaneously without any restriction. The aim is to characterize the habitat of the spur-thighed tortoise (Testudo graeca graeca), using several continuous environmental variables, and one discrete (binary) variable representing the presence or absence of the tortoise. These models are compared with the full discrete models and the results show a better classification rate for the continuous one. Therefore, the application of continuous models instead of discrete ones avoids loss of statistical information due to the discretization. Moreover, the results of the TAN continuous model show a more spatially accurate distribution of the tortoise. The species is located in the Doñana Natural Park, and in semiarid habitats. The proposed continuous models based on MTEs are valid for the study of species predictive distribution modelling.},\n bibtype = {article},\n author = {Aguilera, P.A. and Fernández, A. and Reche, F. and Rumí, R.},\n doi = {10.1016/j.envsoft.2010.04.016},\n journal = {Environmental Modelling &amp; Software},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks are one of the most powerful tools in the design of expert systems located in an uncertainty framework. However, normally their application is determined by the discretization of the continuous variables. In this paper the naïve Bayes (NB) and tree augmented naïve Bayes (TAN) models are developed. They are based on Mixtures of Truncated Exponentials (MTE) designed to deal with discrete and continuous variables in the same network simultaneously without any restriction. The aim is to characterize the habitat of the spur-thighed tortoise (Testudo graeca graeca), using several continuous environmental variables, and one discrete (binary) variable representing the presence or absence of the tortoise. These models are compared with the full discrete models and the results show a better classification rate for the continuous one. Therefore, the application of continuous models instead of discrete ones avoids loss of statistical information due to the discretization. Moreover, the results of the TAN continuous model show a more spatially accurate distribution of the tortoise. The species is located in the Doñana Natural Park, and in semiarid habitats. The proposed continuous models based on MTEs are valid for the study of species predictive distribution modelling.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380010003777', event);\">\n    Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liedloff,  A., C.;  and Smith,  C., S.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 221(21): 2565-2575. 10 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380010003777\"\n     onclick=\"log_download('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://www.sciencedirect.com/science/article/pii/S0304380010003777', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Predicting a ‘tree change’ in Australia&#x27;s tropical savannas: Combining different types of models to understand complex ecosystem behaviour [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2010.07.022\"\n     onclick=\"log_download('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010', 'http://doi.org/10.1016/j.ecolmodel.2010.07.022', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liedloff-smith-predictingatreechangeinaustraliastropicalsavannascombiningdifferenttypesofmodelstounderstandcomplexecosystembehaviour-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predicting a ‘tree change’ in Australia&#x27;s tropical savannas: Combining different types of models to understand complex ecosystem behaviour},\n type = {article},\n year = {2010},\n keywords = {Bayesian networks,Fire management,Flames,Grazing management,Probabilistic modelling,Simulation modelling,Tree density,Woody thickening},\n pages = {2565-2575},\n volume = {221},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380010003777},\n month = {10},\n id = {4337bf37-9106-3918-a95f-74583cbba3ad},\n created = {2015-04-12T19:14:40.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia&#x27;s tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.},\n bibtype = {article},\n author = {Liedloff, Adam C. and Smith, Carl S.},\n doi = {10.1016/j.ecolmodel.2010.07.022},\n journal = {Ecological Modelling},\n number = {21}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/5b0fc647-7cd5-8227-629e-8cf067527c6a/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010', 'https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/5b0fc647-7cd5-8227-629e-8cf067527c6a/full_text.pdf.pdf', event);\">\n    Bayesian networks: A guide for their application in natural resource management and policy What is the objective of the model? Testing model scenarios Evaluation of models (sensitivity and accuracy) Parameterise model (quantitative and qualitative) Describe the model variables (assign states) Transform conceptual model into influence diagram Conceptual model of how the system works.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  \n</span>\n\n  \n\n</span>\n\n  Technical Report  2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/5b0fc647-7cd5-8227-629e-8cf067527c6a/full_text.pdf.pdf\"\n     onclick=\"log_download('bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010', 'https://bibbase.org/service/mendeley/95e10851-cdf3-31de-9f82-1ab629e601b0/file/5b0fc647-7cd5-8227-629e-8cf067527c6a/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Bayesian networks: A guide for their application in natural resource management and policy What is the objective of the model? Testing model scenarios Evaluation of models (sensitivity and accuracy) Parameterise model (quantitative and qualitative) Describe the model variables (assign states) Transform conceptual model into influence diagram Conceptual model of how the system works [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"www.landscapelogic.org.au\"\n     onclick=\"log_download('bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010', 'www.landscapelogic.org.au', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian networks: A guide for their application in natural resource management and policy What is the objective of the model? Testing model scenarios Evaluation of models (sensitivity and accuracy) Parameterise model (quantitative and qualitative) Describe the model variables (assign states) Transform conceptual model into influence diagram Conceptual model of how the system works [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bayesiannetworksaguidefortheirapplicationinnaturalresourcemanagementandpolicywhatistheobjectiveofthemodeltestingmodelscenariosevaluationofmodelssensitivityandaccuracyparameterisemodelquantitativeandqualitativedescribethemodelvariablesassignstatestransformconceptualmodelintoinfluencediagramconceptualmodelofhowthesystemworks-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@techreport{\n title = {Bayesian networks: A guide for their application in natural resource management and policy What is the objective of the model? Testing model scenarios Evaluation of models (sensitivity and accuracy) Parameterise model (quantitative and qualitative) Describe the model variables (assign states) Transform conceptual model into influence diagram Conceptual model of how the system works},\n type = {techreport},\n year = {2010},\n websites = {www.landscapelogic.org.au},\n id = {591a715b-2aec-3587-82db-2aebb3b8dd72},\n created = {2020-03-05T01:26:27.645Z},\n accessed = {2020-03-04},\n file_attached = {true},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2020-03-05T01:26:36.102Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {techreport},\n author = {}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2009\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2009')\"\n      onkeypress=\"toggleGroup('group_2009')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2009</span>\n      <span class=\"bibbase_group_count\">\n        \n        (7)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009001525\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009', 'http://www.sciencedirect.com/science/article/pii/S0304380009001525', event);\">\n    Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Renken,  H.;  and Mumby,  P., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 220(9-10): 1305-1314. 5 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380009001525\"\n     onclick=\"log_download('renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009', 'http://www.sciencedirect.com/science/article/pii/S0304380009001525', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2009.02.022\"\n     onclick=\"log_download('renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009', 'http://doi.org/10.1016/j.ecolmodel.2009.02.022', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('renken-mumby-modellingthedynamicsofcoralreefmacroalgaeusingabayesianbeliefnetworkapproach-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach},\n type = {article},\n year = {2009},\n keywords = {Bayesian belief network,Diadema antillarum,Dictyota spp.,Grazing pressure,Macroalgal dynamics,Nutrients,Scaridae},\n pages = {1305-1314},\n volume = {220},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380009001525},\n month = {5},\n id = {7cf595bd-9144-3165-be59-04863302f07c},\n created = {2015-04-11T15:45:45.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.},\n bibtype = {article},\n author = {Renken, Henk and Mumby, Peter J.},\n doi = {10.1016/j.ecolmodel.2009.02.022},\n journal = {Ecological Modelling},\n number = {9-10}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Macroalgae are a major benthic component of coral reefs and their dynamics influence the resilience of coral reefs to disturbance. However, the relative importance of physical and ecological processes in driving macroalgal dynamics is poorly understood. Here we develop a Bayesian belief network (BBN) model to integrate many of these processes and predict the growth of coral reef macroalgae. Bayesian belief networks use probabilistic relationships rather than deterministic rules to quantify the cause and effect assumptions. The model was developed using both new empirical data and quantified relationships elicited from previous studies. We demonstrate the efficacy of the BBN to predict the dynamics of a common Caribbean macroalgal genus Dictyota. Predictions of the model have an average accuracy of 55% (implying that 55% of the predicted categories of Dictyota cover were assigned to the correct class). Sensitivity analysis suggested that macroalgal dynamics were primarily driven by top–down processes of grazing rather than bottom–up nutrification. BBNs provide a useful framework for modelling complex systems, identifying gaps in our scientific understanding and communicating the complexities of the associated uncertainties in an explicit manner to stakeholders. We anticipate that accuracies will improve as new data are added to the model.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815208001527\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815208001527', event);\">\n    An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Farmani,  R.; Henriksen,  H., J.;  and Savic,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 24(3): 303-310. 3 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815208001527\"\n     onclick=\"log_download('farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815208001527', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2008.08.005\"\n     onclick=\"log_download('farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009', 'http://doi.org/10.1016/j.envsoft.2008.08.005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('farmani-henriksen-savic-anevolutionarybayesianbeliefnetworkmethodologyforoptimummanagementofgroundwatercontamination-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination},\n type = {article},\n year = {2009},\n keywords = {Bayesian belief network,Evolutionary optimization,Multi-objective,Uncertainty,Water resources management},\n pages = {303-310},\n volume = {24},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001527},\n month = {3},\n id = {a9ab7039-fc72-3b3b-a9fb-d02b3c6fb47d},\n created = {2015-04-11T18:33:35.000Z},\n accessed = {2015-02-19},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.},\n bibtype = {article},\n author = {Farmani, Raziyeh and Henriksen, Hans Jørgen and Savic, Dragan},\n doi = {10.1016/j.envsoft.2008.08.005},\n journal = {Environmental Modelling &amp; Software},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380008004420\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009', 'http://www.sciencedirect.com/science/article/pii/S0304380008004420', event);\">\n    Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Langmead,  O.; McQuatters-Gollop,  A.; Mee,  L., D.; Friedrich,  J.; Gilbert,  A., J.; Gomoiu,  M.; Jackson,  E., L.; Knudsen,  S.; Minicheva,  G.;  and Todorova,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 220(21): 2927-2939. 11 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380008004420\"\n     onclick=\"log_download('langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009', 'http://www.sciencedirect.com/science/article/pii/S0304380008004420', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2008.09.011\"\n     onclick=\"log_download('langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009', 'http://doi.org/10.1016/j.ecolmodel.2008.09.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('langmead-mcquattersgollop-mee-friedrich-gilbert-gomoiu-jackson-knudsen-etal-recoveryordeclineofthenorthwesternblackseaasocietalchoicerevealedbysocioecologicalmodelling-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Recovery or decline of the northwestern Black Sea: A societal choice revealed by socio-ecological modelling},\n type = {article},\n year = {2009},\n keywords = {Bayesian belief network (BBN),Black Sea,DPSIR,Eutrophication,Marine socio-ecological systems},\n pages = {2927-2939},\n volume = {220},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380008004420},\n month = {11},\n id = {9204e42d-e51a-375c-b9b1-7c0626665bcf},\n created = {2015-04-11T19:07:36.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea&#x27;s ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.},\n bibtype = {article},\n author = {Langmead, Olivia and McQuatters-Gollop, Abigail and Mee, Laurence D. and Friedrich, Jana and Gilbert, Alison J. and Gomoiu, Marian-Traian and Jackson, Emma L. and Knudsen, Ståle and Minicheva, Galina and Todorova, Valentina},\n doi = {10.1016/j.ecolmodel.2008.09.011},\n journal = {Ecological Modelling},\n number = {21}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  During recent decades anthropogenic activities have dramatically impacted the Black Sea ecosystem. High levels of riverine nutrient input during the 1970s and 1980s caused eutrophic conditions including intense algal blooms resulting in hypoxia and the subsequent collapse of benthic habitats on the northwestern shelf. Intense fishing pressure also depleted stocks of many apex predators, contributing to an increase in planktivorous fish that are now the focus of fishing efforts. Additionally, the Black Sea's ecosystem changed even further with the introduction of exotic species. Economic collapse of the surrounding socialist republics in the early 1990s resulted in decreased nutrient loading which has allowed the Black Sea ecosystem to start to recover, but under rapidly changing economic and political conditions, future recovery is uncertain. In this study we use a multidisciplinary approach to integrate information from socio-economic and ecological systems to model the effects of future development scenarios on the marine environment of the northwestern Black Sea shelf. The Driver–Pressure–State-Impact-Response framework was used to construct conceptual models, explicitly mapping impacts of socio-economic Drivers on the marine ecosystem. Bayesian belief networks (BBNs), a stochastic modelling technique, were used to quantify these causal relationships, operationalise models and assess the effects of alternative development paths on the Black Sea ecosystem. BBNs use probabilistic dependencies as a common metric, allowing the integration of quantitative and qualitative information. Under the Baseline Scenario, recovery of the Black Sea appears tenuous as the exploitation of environmental resources (agriculture, fishing and shipping) increases with continued economic development of post-Soviet countries. This results in the loss of wetlands through drainage and reclamation. Water transparency decreases as phytoplankton bloom and this deterioration in water quality leads to the degradation of coastal plant communities (Cystoseira, seagrass) and also Phyllophora habitat on the shelf. Decomposition of benthic plants results in hypoxia killing flora and fauna associated with these habitats. Ecological pressure from these factors along with constant levels of fishing activity results in target stocks remaining depleted. Of the four Alternative Scenarios, two show improvements on the Baseline ecosystem condition, with improved waste water treatment and reduced fishing pressure, while the other two show a worsening, due to increased natural resource exploitation leading to rapid reversal of any recent ecosystem recovery. From this we conclude that variations in economic policy have significant consequences for the health of the Black Sea, and ecosystem recovery is directly linked to social–economic choices.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479707003465\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009', 'http://www.sciencedirect.com/science/article/pii/S0301479707003465', event);\">\n    Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aitkenhead,  M., J.;  and Aalders,  I., H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 90(1): 236-50. 1 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479707003465\"\n     onclick=\"log_download('aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009', 'http://www.sciencedirect.com/science/article/pii/S0301479707003465', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Predicting land cover using GIS, Bayesian and evolutionary algorithm methods. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2007.09.010\"\n     onclick=\"log_download('aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009', 'http://doi.org/10.1016/j.jenvman.2007.09.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aitkenhead-aalders-predictinglandcoverusinggisbayesianandevolutionaryalgorithmmethods-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.},\n type = {article},\n year = {2009},\n keywords = {Algorithms,Bayes Theorem,Biological Evolution,Conservation of Natural Resources,Ecosystem,Environment,Geography,Models, Theoretical,Probability,Scotland,Software},\n pages = {236-50},\n volume = {90},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479707003465},\n month = {1},\n id = {dd17dce9-55c0-3c0d-8b3c-e0151478561c},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.},\n bibtype = {article},\n author = {Aitkenhead, M J and Aalders, I H},\n doi = {10.1016/j.jenvman.2007.09.010},\n journal = {Journal of environmental management},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209001224\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815209001224', event);\">\n    Reforestation planning using Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ordóñez Galán,  C.; Matías,  J.; Rivas,  T.;  and Bastante,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 24(11): 1285-1292. 11 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209001224\"\n     onclick=\"log_download('ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815209001224', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Reforestation planning using Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2009.05.009\"\n     onclick=\"log_download('ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009', 'http://doi.org/10.1016/j.envsoft.2009.05.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ordezgaln-matas-rivas-bastante-reforestationplanningusingbayesiannetworks-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reforestation planning using Bayesian networks},\n type = {article},\n year = {2009},\n keywords = {Bayesian networks,Environmental variables,GIS,Machine learning,Reforestation},\n pages = {1285-1292},\n volume = {24},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001224},\n month = {11},\n id = {e3ab2c9a-49e3-3ad0-8389-7ef8721d92ad},\n created = {2015-04-11T19:52:26.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The aim of this research was to construct a reforestation model for woodland located in the basin of the river Liébana (NW Spain). This is essentially a pattern recognition problem: the class labels are types of woodland, and the variables for each point are environmental coordinates (referring to altitude, slope, rainfall, lithology, etc.). The model trained using data for existing wooded areas will serve as a guideline for the reforestation of deforested areas. Nonetheless, with a view to tackling reforestation from a more informed perspective, of interest is an interpretable model of relationships existing not just between woodland type and environmental variables but also between and among the environmental variables themselves. For this reason we used Bayesian networks, as a tool that is capable of constructing a causal model of the relationships existing between all the variables represented in the model. The prediction results obtained were compared with those for classical linear techniques, neural networks and support vector machines.},\n bibtype = {article},\n author = {Ordóñez Galán, C. and Matías, J.M. and Rivas, T. and Bastante, F.G.},\n doi = {10.1016/j.envsoft.2009.05.009},\n journal = {Environmental Modelling &amp; Software},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The aim of this research was to construct a reforestation model for woodland located in the basin of the river Liébana (NW Spain). This is essentially a pattern recognition problem: the class labels are types of woodland, and the variables for each point are environmental coordinates (referring to altitude, slope, rainfall, lithology, etc.). The model trained using data for existing wooded areas will serve as a guideline for the reforestation of deforested areas. Nonetheless, with a view to tackling reforestation from a more informed perspective, of interest is an interpretable model of relationships existing not just between woodland type and environmental variables but also between and among the environmental variables themselves. For this reason we used Bayesian networks, as a tool that is capable of constructing a causal model of the relationships existing between all the variables represented in the model. The prediction results obtained were compared with those for classical linear techniques, neural networks and support vector machines.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815208001126\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815208001126', event);\">\n    Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mesbah,  S., M.; Kerachian,  R.;  and Nikoo,  M., R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 24(2): 238-246. 2 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815208001126\"\n     onclick=\"log_download('mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815208001126', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2008.06.007\"\n     onclick=\"log_download('mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009', 'http://doi.org/10.1016/j.envsoft.2008.06.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mesbah-kerachian-nikoo-developingrealtimeoperatingrulesfortradingdischargepermitsinriversapplicationofbayesiannetworks-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks},\n type = {article},\n year = {2009},\n keywords = {Bayesian Networks (BNs),Extended Trading Ratio System (ETRS),Monte Carlo simulation,Real time operating rules,The Zarjub River,Trading discharge permits (TDP)},\n pages = {238-246},\n volume = {24},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815208001126},\n month = {2},\n id = {2807af2e-21af-3c39-9611-97201287e493},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.},\n bibtype = {article},\n author = {Mesbah, Seyyed Morteza and Kerachian, Reza and Nikoo, Mohammad Reza},\n doi = {10.1016/j.envsoft.2008.06.007},\n journal = {Environmental Modelling &amp; Software},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209001431\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815209001431', event);\">\n    Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Malekmohammadi,  B.; Kerachian,  R.;  and Zahraie,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 24(12): 1420-1432. 12 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815209001431\"\n     onclick=\"log_download('malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009', 'http://www.sciencedirect.com/science/article/pii/S1364815209001431', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2009.06.008\"\n     onclick=\"log_download('malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009', 'http://doi.org/10.1016/j.envsoft.2009.06.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('malekmohammadi-kerachian-zahraie-developingmonthlyoperatingrulesforacascadesystemofreservoirsapplicationofbayesiannetworks-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing monthly operating rules for a cascade system of reservoirs: Application of Bayesian Networks},\n type = {article},\n year = {2009},\n keywords = {Bayesian Networks (BNs),Long-term and short-term operation optimization,Reservoir operating rules,Varying chromosome Length Genetic Algorithm (VLGA)},\n pages = {1420-1432},\n volume = {24},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815209001431},\n month = {12},\n id = {5985fd58-d279-3ed0-8700-3328fc628910},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In this paper, a Bayesian Network (BN) is utilized for developing monthly operating rules for a cascade system of reservoirs which is mainly aimed to control floods and supply irrigation needs. BN is trained and verified using the results of a reservoir operation optimization model, which optimizes monthly releases from cascade reservoirs. The inputs of the BN are monthly inflows, reservoir storages at the beginning of the month, and downstream water demands. The trained BN provides the probability distribution functions of reservoirs&#x27; releases for each set of input data. The long-term optimization model in monthly scale is formulated to minimize the expected flood and agricultural water deficit damages. The optimization model is developed using an extended version of the Varying chromosome Length Genetic Algorithm (VLGA-II). To incorporate reservoir preparedness for controlling the probable floods in each month, damages associated with floods with different return periods have been considered in the optimization model. For this purpose, a short-term optimization model which provides the optimal hourly releases during floods is utilized and linked to a flood damage estimation model. Damages due to deficit in supplying agricultural water demands are also calculated based on the functions of crop yield responses to deficit irrigation. The developed models are applied to the cascade system of the Dez and Bakhtiari Reservoirs in Southwest of Iran. The result of the trained BN is compared with the rules developed using classical and fuzzy linear regressions and it is shown that the total damage obtained by the BN-based operating rules is about 60 percent less than the total damage obtained using the fuzzy and classical regression analyses. The average relative error in estimating optimal releases is also reduced about 30 percent by using the BN-based rules.},\n bibtype = {article},\n author = {Malekmohammadi, Bahram and Kerachian, Reza and Zahraie, Banafsheh},\n doi = {10.1016/j.envsoft.2009.06.008},\n journal = {Environmental Modelling &amp; Software},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper, a Bayesian Network (BN) is utilized for developing monthly operating rules for a cascade system of reservoirs which is mainly aimed to control floods and supply irrigation needs. BN is trained and verified using the results of a reservoir operation optimization model, which optimizes monthly releases from cascade reservoirs. The inputs of the BN are monthly inflows, reservoir storages at the beginning of the month, and downstream water demands. The trained BN provides the probability distribution functions of reservoirs' releases for each set of input data. The long-term optimization model in monthly scale is formulated to minimize the expected flood and agricultural water deficit damages. The optimization model is developed using an extended version of the Varying chromosome Length Genetic Algorithm (VLGA-II). To incorporate reservoir preparedness for controlling the probable floods in each month, damages associated with floods with different return periods have been considered in the optimization model. For this purpose, a short-term optimization model which provides the optimal hourly releases during floods is utilized and linked to a flood damage estimation model. Damages due to deficit in supplying agricultural water demands are also calculated based on the functions of crop yield responses to deficit irrigation. The developed models are applied to the cascade system of the Dez and Bakhtiari Reservoirs in Southwest of Iran. The result of the trained BN is compared with the rules developed using classical and fuzzy linear regressions and it is shown that the total damage obtained by the BN-based operating rules is about 60 percent less than the total damage obtained using the fuzzy and classical regression analyses. The average relative error in estimating optimal releases is also reduced about 30 percent by using the BN-based rules.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2008\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2008')\"\n      onkeypress=\"toggleGroup('group_2008')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2008</span>\n      <span class=\"bibbase_group_count\">\n        \n        (9)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"borsuk-encyclopediaofecology-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/B9780080454054001440\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'borsuk-encyclopediaofecology-2008', 'http://www.sciencedirect.com/science/article/pii/B9780080454054001440', event);\">\n    Encyclopedia of Ecology.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Borsuk,  M.\n</span>\n\n  \n\n</span>\n\n  Elsevier,  2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/B9780080454054001440\"\n     onclick=\"log_download('borsuk-encyclopediaofecology-2008', 'http://www.sciencedirect.com/science/article/pii/B9780080454054001440', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Encyclopedia of Ecology [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/B978-008045405-4.00144-0\"\n     onclick=\"log_download('borsuk-encyclopediaofecology-2008', 'http://doi.org/10.1016/B978-008045405-4.00144-0', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/borsuk-encyclopediaofecology-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('borsuk-encyclopediaofecology-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@book{\n title = {Encyclopedia of Ecology},\n type = {book},\n year = {2008},\n source = {Encyclopedia of Ecology},\n keywords = {Artificial intelligence,Bayesian networks,Belief networks,Causal analysis,Causality,Graphical models,Hierarchical Bayes,Inference,Influence diagrams,Learning,Prediction,Probability networks},\n pages = {307-317},\n websites = {http://www.sciencedirect.com/science/article/pii/B9780080454054001440},\n publisher = {Elsevier},\n id = {af635c49-de74-3eb9-ae1c-c6a1593ce15f},\n created = {2015-04-11T15:50:45.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {By succinctly and effectively translating causal assertions between variables into patterns of probabilistic dependence, Bayesian networks (BNs) facilitate logical and holistic reasoning under uncertainty in complex systems. Such reasoning is necessary for accurate analysis, synthesis, prediction, diagnosis, and decision making. A definition of BNs is first provided and a simple ecological example is introduced that will be used throughout the remainder of the article to illustrate basic concepts. Methods for constructing BNs are next described, including specification of model structure and conditional probabilities, both deliberately and automatically from case data. This is followed by a description of how BNs can be used for prediction, inference, explanation, intervention, and decision. Finally, some special cases of BNs are presented including hierarchical, dynamic, and integrated models. These show how BNs can be used to integrate across scales, disciplines, and levels of complexity.},\n bibtype = {book},\n author = {Borsuk, M.E.},\n doi = {10.1016/B978-008045405-4.00144-0}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  By succinctly and effectively translating causal assertions between variables into patterns of probabilistic dependence, Bayesian networks (BNs) facilitate logical and holistic reasoning under uncertainty in complex systems. Such reasoning is necessary for accurate analysis, synthesis, prediction, diagnosis, and decision making. A definition of BNs is first provided and a simple ecological example is introduced that will be used throughout the remainder of the article to illustrate basic concepts. Methods for constructing BNs are next described, including specification of model structure and conditional probabilities, both deliberately and automatically from case data. This is followed by a description of how BNs can be used for prediction, inference, explanation, intervention, and decision. Finally, some special cases of BNs are presented including hierarchical, dynamic, and integrated models. These show how BNs can be used to integrate across scales, disciplines, and levels of complexity.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1881836608800018\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008', 'http://www.sciencedirect.com/science/article/pii/S1881836608800018', event);\">\n    Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ushada,  M.;  and Murase,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Engineering in Agriculture, Environment and Food</i>, 1(2): 45-50.  2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1881836608800018\"\n     onclick=\"log_download('ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008', 'http://www.sciencedirect.com/science/article/pii/S1881836608800018', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S1881-8366(08)80001-8\"\n     onclick=\"log_download('ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008', 'http://doi.org/10.1016/S1881-8366(08)80001-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ushada-murase-patternextractionfromhumanpreferencereasoningusingconditionalprobabilitycooccurrencesmatrixoftextureanalysis-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pattern Extraction from Human Preference Reasoning Using Conditional Probability Co-occurrences Matrix of Texture Analysis},\n type = {article},\n year = {2008},\n keywords = {Bayesian belief network,conditional probability,knowledge,moss greening produce,preference,texture analysis},\n pages = {45-50},\n volume = {1},\n websites = {http://www.sciencedirect.com/science/article/pii/S1881836608800018},\n id = {56b90f2e-e48c-3fe7-b9aa-39d9e2f838fb},\n created = {2015-04-11T17:43:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.},\n bibtype = {article},\n author = {Ushada, Mirwan and Murase, Haruhiko},\n doi = {10.1016/S1881-8366(08)80001-8},\n journal = {Engineering in Agriculture, Environment and Food},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A new approach is proposed for extraction of features from human preferences reasoning. Conditional Probability Table (CPT) is a mentality representation to control the reasoning in Bayesian Belief Network (BBN). A software tool was developed using texture analysis with a co-occurrences matrix algorithm. As a case study, it was tested on BBN of moss (Rhacomitrium canescens) produce preferences. The result successfully represented features extracted as specific patterns. It is applicable as a new computational method for reducing many concrete parameters (Dimensionality) and extracting the information from CPT in five textural features. These features are essential as abstractive parameters for designing customized agro-industrial production to provide every consumer with a produce that matches his or her unique preferences.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479707001922\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008', 'http://www.sciencedirect.com/science/article/pii/S0301479707001922', event);\">\n    Reflections on the use of Bayesian belief networks for adaptive management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Henriksen,  H., J.;  and Barlebo,  H., C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 88(4): 1025-36. 9 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479707001922\"\n     onclick=\"log_download('henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008', 'http://www.sciencedirect.com/science/article/pii/S0301479707001922', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Reflections on the use of Bayesian belief networks for adaptive management. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2007.05.009\"\n     onclick=\"log_download('henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008', 'http://doi.org/10.1016/j.jenvman.2007.05.009', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('henriksen-barlebo-reflectionsontheuseofbayesianbeliefnetworksforadaptivemanagement-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reflections on the use of Bayesian belief networks for adaptive management.},\n type = {article},\n year = {2008},\n keywords = {Bayes Theorem,European Union,Water Supply},\n pages = {1025-36},\n volume = {88},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479707001922},\n month = {9},\n id = {40d1bc21-002a-3bc1-a529-ccbcbef80351},\n created = {2015-04-11T18:33:33.000Z},\n accessed = {2015-03-20},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers&#x27; experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.},\n bibtype = {article},\n author = {Henriksen, Hans Jørgen and Barlebo, Heidi Christiansen},\n doi = {10.1016/j.jenvman.2007.05.009},\n journal = {Journal of environmental management},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers' experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X08000966\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008', 'http://www.sciencedirect.com/science/article/pii/S0308521X08000966', event);\">\n    Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bashari,  H.; Smith,  C.;  and Bosch,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Systems</i>, 99(1): 23-34. 12 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X08000966\"\n     onclick=\"log_download('bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008', 'http://www.sciencedirect.com/science/article/pii/S0308521X08000966', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agsy.2008.09.003\"\n     onclick=\"log_download('bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008', 'http://doi.org/10.1016/j.agsy.2008.09.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bashari-smith-bosch-developingdecisionsupporttoolsforrangelandmanagementbycombiningstateandtransitionmodelsandbayesianbeliefnetworks-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks},\n type = {article},\n year = {2008},\n keywords = {Adaptive management,Bayesian belief network,Decision support,Queensland,Rangeland management,State and transition model},\n pages = {23-34},\n volume = {99},\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X08000966},\n month = {12},\n id = {60306c81-7a67-3eae-b843-225b6347b7c0},\n created = {2015-04-11T18:33:34.000Z},\n accessed = {2015-04-01},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {State and transition models provide a simple and versatile way of describing vegetation dynamics in rangelands. However, state and transition models are traditionally descriptive, which has limited their practical application to rangeland management decision support. This paper demonstrates an approach to rangeland management decision support that combines a state and transition model with a Bayesian belief network to provide a relatively simple and updatable rangeland dynamics model that can accommodate uncertainty and be used for scenario, diagnostic, and sensitivity analysis. A state and transition model, developed by the authors for subtropical grassland in south-east Queensland, Australia, is used as an example. From the state and transition model, an influence diagram was built to show the possible transitions among states and the factors influencing each transition. The influence diagram was populated with probabilities to produce a predictive model in the form of a Bayesian belief network. The behaviour of the model was tested using scenario and sensitivity analysis, revealing that selective grazing, grazing pressure, and soil nutrition were believed to influence most transitions, while fire frequency and the frequency of good wet seasons were also important in some transitions. Overall, the integration of a state and transition model with a Bayesian belief network provided a useful way to utilise the knowledge embedded in a state and transition model for predictive purposes. Using a Bayesian belief network in the modelling approach allowed uncertainty and variability to be explicitly accommodated in the modelling process, and expert knowledge to be utilised in model development. The methods used also supported learning from monitoring data, thereby supporting adaptive rangeland management.},\n bibtype = {article},\n author = {Bashari, H. and Smith, C. and Bosch, O.J.H.},\n doi = {10.1016/j.agsy.2008.09.003},\n journal = {Agricultural Systems},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  State and transition models provide a simple and versatile way of describing vegetation dynamics in rangelands. However, state and transition models are traditionally descriptive, which has limited their practical application to rangeland management decision support. This paper demonstrates an approach to rangeland management decision support that combines a state and transition model with a Bayesian belief network to provide a relatively simple and updatable rangeland dynamics model that can accommodate uncertainty and be used for scenario, diagnostic, and sensitivity analysis. A state and transition model, developed by the authors for subtropical grassland in south-east Queensland, Australia, is used as an example. From the state and transition model, an influence diagram was built to show the possible transitions among states and the factors influencing each transition. The influence diagram was populated with probabilities to produce a predictive model in the form of a Bayesian belief network. The behaviour of the model was tested using scenario and sensitivity analysis, revealing that selective grazing, grazing pressure, and soil nutrition were believed to influence most transitions, while fire frequency and the frequency of good wet seasons were also important in some transitions. Overall, the integration of a state and transition model with a Bayesian belief network provided a useful way to utilise the knowledge embedded in a state and transition model for predictive purposes. Using a Bayesian belief network in the modelling approach allowed uncertainty and variability to be explicitly accommodated in the modelling process, and expert knowledge to be utilised in model development. The methods used also supported learning from monitoring data, thereby supporting adaptive rangeland management.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0921800908000827\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008', 'http://www.sciencedirect.com/science/article/pii/S0921800908000827', event);\">\n    Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Barton,  D.; Saloranta,  T.; Moe,  S.; Eggestad,  H.;  and Kuikka,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Economics</i>, 66(1): 91-104. 5 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0921800908000827\"\n     onclick=\"log_download('barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008', 'http://www.sciencedirect.com/science/article/pii/S0921800908000827', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolecon.2008.02.012\"\n     onclick=\"log_download('barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008', 'http://doi.org/10.1016/j.ecolecon.2008.02.012', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('barton-saloranta-moe-eggestad-kuikka-bayesianbeliefnetworksasametamodellingtoolinintegratedriverbasinmanagementprosandconsinevaluatingnutrientabatementdecisionsunderuncertaintyinanorwegianriverbasin-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian belief networks as a meta-modelling tool in integrated river basin management — Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin},\n type = {article},\n year = {2008},\n keywords = {Bayesian networks,Benefit–cost analysis,Decision analysis,Eutrophication,Influence diagrams,Uncertainty,Water Framework Directive},\n pages = {91-104},\n volume = {66},\n websites = {http://www.sciencedirect.com/science/article/pii/S0921800908000827},\n month = {5},\n id = {8eea9de3-e133-3100-8084-d4f26e98112b},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-02-19},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing cost-effectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.},\n bibtype = {article},\n author = {Barton, D.N. and Saloranta, T. and Moe, S.J. and Eggestad, H.O. and Kuikka, S.},\n doi = {10.1016/j.ecolecon.2008.02.012},\n journal = {Ecological Economics},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A Bayesian network approach is used to conduct decision analysis of nutrient abatement measures in the Morsa catchment, South Eastern Norway. The paper demonstrates the use of Bayesian networks as a meta-modelling tool in integrated river basin management (IRBM) for structuring and combining the probabilistic information available in existing cost-effectiveness studies, eutrophication models and data, non-market valuation studies and expert opinion. The Bayesian belief network is used to evaluate eutrophication mitigation costs relative to benefits, as part of the economic analysis under the EU Water Framework Directive (WFD). Pros and cons of Bayesian networks as reported in the literature are reviewed in light of the results from our Morsa catchment model. The reported advantages of Bayesian networks in promoting integrated, inter-disciplinary evaluation of uncertainty in IRBM, as well as the apparent advantages for risk communication with stakeholders, are offset in our case by the cost of obtaining reliable probabilistic data and meta-model validation procedures.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380008000768\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008', 'http://www.sciencedirect.com/science/article/pii/S0304380008000768', event);\">\n    Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wilson,  D., S.; Stoddard,  M., A.;  and Puettmann,  K., J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 214(2-4): 210-218. 6 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380008000768\"\n     onclick=\"log_download('wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008', 'http://www.sciencedirect.com/science/article/pii/S0304380008000768', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2008.02.003\"\n     onclick=\"log_download('wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008', 'http://doi.org/10.1016/j.ecolmodel.2008.02.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wilson-stoddard-puettmann-monitoringamphibianpopulationswithincompletesurveyinformationusingabayesianprobabilisticmodel-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Monitoring amphibian populations with incomplete survey information using a Bayesian probabilistic model},\n type = {article},\n year = {2008},\n keywords = {Amphibian monitoring,Ascaphus truei,Bayesian networks,Dicamptodon tenebrosus,Hierarchical Bayesian models,Rhyacotriton spp.},\n pages = {210-218},\n volume = {214},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380008000768},\n month = {6},\n id = {b9c62cf5-6e60-39c6-8883-19a93b8353aa},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs) are a probabilistic modeling platform that connect variables through a series of conditional dependences. We demonstrate their utility for broad-scale conservation of amphibian populations where different types of information may be available within the region. Wildlife conservation decisions for most species are made jointly with other objectives and are tightly constrained by finances. Bayesian networks allow the use of all available information in predictions, and can provide managers with the best available information for making decisions. Habitat models were developed as a hierarchical Bayesian (HB) model for aquatic amphibian populations in the temperate Oregon Coast Range, USA. Predictions for new streams sections were made jointly using a Bayesian network to allow the inclusion of different types of available information. Missing habitat variables were modeled based on habitat survey information. Uncertainty in the true (but unknown) habitat variables were incorporated into the prediction intervals. Further, the probabilistic approach allowed us to incorporate survey information for co-occurring species to help make better predictions. Such species information was connected through the Bayesian network by the conditional dependence that arises from shared habitat variables. The utility of Bayesian networks was shown for these populations for broad-scale risk management. In contrast to deterministic models, the probabilistic nature of Bayesian networks is a natural platform for incorporating uncertainty in predictions and inference.},\n bibtype = {article},\n author = {Wilson, Duncan S. and Stoddard, Margo A. and Puettmann, Klaus J.},\n doi = {10.1016/j.ecolmodel.2008.02.003},\n journal = {Ecological Modelling},\n number = {2-4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs) are a probabilistic modeling platform that connect variables through a series of conditional dependences. We demonstrate their utility for broad-scale conservation of amphibian populations where different types of information may be available within the region. Wildlife conservation decisions for most species are made jointly with other objectives and are tightly constrained by finances. Bayesian networks allow the use of all available information in predictions, and can provide managers with the best available information for making decisions. Habitat models were developed as a hierarchical Bayesian (HB) model for aquatic amphibian populations in the temperate Oregon Coast Range, USA. Predictions for new streams sections were made jointly using a Bayesian network to allow the inclusion of different types of available information. Missing habitat variables were modeled based on habitat survey information. Uncertainty in the true (but unknown) habitat variables were incorporated into the prediction intervals. Further, the probabilistic approach allowed us to incorporate survey information for co-occurring species to help make better predictions. Such species information was connected through the Bayesian network by the conditional dependence that arises from shared habitat variables. The utility of Bayesian networks was shown for these populations for broad-scale risk management. In contrast to deterministic models, the probabilistic nature of Bayesian networks is a natural platform for incorporating uncertainty in predictions and inference.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://www.sciencedirect.com/science/article/pii/S1476945X08000147', event);\">\n    A systems approach to unravel complex water management institutions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Saravanan,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Complexity</i>, 5(3): 202-215. 9 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"\n     onclick=\"log_download('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://www.sciencedirect.com/science/article/pii/S1476945X08000147', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A systems approach to unravel complex water management institutions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecocom.2008.04.003\"\n     onclick=\"log_download('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://doi.org/10.1016/j.ecocom.2008.04.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A systems approach to unravel complex water management institutions},\n type = {article},\n year = {2008},\n keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},\n pages = {202-215},\n volume = {5},\n websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},\n month = {9},\n id = {03e1c5c5-ca0e-39f7-aac8-77dfa167f9e9},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent&#x27;s capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},\n bibtype = {article},\n author = {Saravanan, V.S.},\n doi = {10.1016/j.ecocom.2008.04.003},\n journal = {Ecological Complexity},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479706003975\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008', 'http://www.sciencedirect.com/science/article/pii/S0301479706003975', event);\">\n    Classifying environmentally significant urban land uses with satellite imagery.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Park,  M.;  and Stenstrom,  M., K.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of environmental management</i>, 86(1): 181-92. 1 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479706003975\"\n     onclick=\"log_download('park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008', 'http://www.sciencedirect.com/science/article/pii/S0301479706003975', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Classifying environmentally significant urban land uses with satellite imagery. [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jenvman.2006.12.010\"\n     onclick=\"log_download('park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008', 'http://doi.org/10.1016/j.jenvman.2006.12.010', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('park-stenstrom-classifyingenvironmentallysignificanturbanlanduseswithsatelliteimagery-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Classifying environmentally significant urban land uses with satellite imagery.},\n type = {article},\n year = {2008},\n keywords = {Bayes Theorem,California,Cities,Commerce,Environment,Housing,Industry,Recreation,Satellite Communications,Transportation,Water,Water Supply},\n pages = {181-92},\n volume = {86},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479706003975},\n month = {1},\n id = {2cca927c-aedc-3a85-9720-a78cdd55dc8a},\n created = {2015-04-11T19:52:20.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.},\n bibtype = {article},\n author = {Park, Mi-Hyun and Stenstrom, Michael K},\n doi = {10.1016/j.jenvman.2006.12.010},\n journal = {Journal of environmental management},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://www.sciencedirect.com/science/article/pii/S1476945X08000147', event);\">\n    A systems approach to unravel complex water management institutions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Saravanan,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Complexity</i>, 5(3): 202-215. 9 2008.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1476945X08000147\"\n     onclick=\"log_download('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://www.sciencedirect.com/science/article/pii/S1476945X08000147', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A systems approach to unravel complex water management institutions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecocom.2008.04.003\"\n     onclick=\"log_download('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008', 'http://doi.org/10.1016/j.ecocom.2008.04.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('saravanan-asystemsapproachtounravelcomplexwatermanagementinstitutions-2008')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A systems approach to unravel complex water management institutions},\n type = {article},\n year = {2008},\n keywords = {Bayesian network,Complex systems,India,Institutional analysis,Integrated management},\n pages = {202-215},\n volume = {5},\n websites = {http://www.sciencedirect.com/science/article/pii/S1476945X08000147},\n month = {9},\n id = {7ae5fbce-67db-300e-8963-c3bf52f746a5},\n created = {2015-04-12T20:17:32.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent&#x27;s capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.},\n bibtype = {article},\n author = {Saravanan, V.S.},\n doi = {10.1016/j.ecocom.2008.04.003},\n journal = {Ecological Complexity},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The study unravels the complexity of water management institutions by analysing the interactive nature of actors and rules to a particular water-related problem, using a systems approach in a hamlet in the Indian Himalayas. The approach builds on the strengths of institutional analysis development framework, but makes amendments to suit complex and adaptive water management institutions. It applies multiple research methods to collect both qualitative and quantitative information at different contextual levels. The information collected is applied in Bayesian belief network model to identify differential rules in influencing water management. Systems perspective in a problem context helped to comprehensively understand the socio-political process of water management by identifying broad array of actors and rules constraining water management, and at the same time identify actors and rules facilitating agents and their agency for a change in the water management process. In this socio-political process, the study reveals human entities – stakeholders, actors and agents – occupy different positions, which they actively shift in a problem context and when agents pursue ‘projects’ by integrating diverse rules and resources to remain adaptive. It is this adaptive and dynamic behaviour that contemporary programmes and policies fail to acknowledge. In this dynamic behaviour of the transformative capacity or power is everywhere, but they are displayed, maintained and upheld, only when agents pursue their ‘project’ by negotiating with other agents. The paper highlights the importance of comprehensive approach, in contrast to simplistic, linear and single package reforms to manage water. Such approach calls for conscious designing of rules and, at the same time, enabling actors to design rules. A conscious designing of rules is required to regulate water distribution, to build the capabilities of the poor, and to be adaptive to institutional and bio-physical crises. It calls for the development of infrastructures to further actors and agent's capabilities to design rules for informed water-related decisions. Such an approach will contribute towards sustainable water resource management.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2007\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2007')\"\n      onkeypress=\"toggleGroup('group_2007')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2007</span>\n      <span class=\"bibbase_group_count\">\n        \n        (11)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://www.sciencedirect.com/science/article/pii/S0198971507000154', event);\">\n    Modelling land-use decisions under conditions of uncertainty.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ma,  L.; Arentze,  T.; Borgers,  A.;  and Timmermans,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Computers, Environment and Urban Systems</i>, 31(4): 461-476. 7 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"\n     onclick=\"log_download('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://www.sciencedirect.com/science/article/pii/S0198971507000154', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling land-use decisions under conditions of uncertainty [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compenvurbsys.2007.02.002\"\n     onclick=\"log_download('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://doi.org/10.1016/j.compenvurbsys.2007.02.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling land-use decisions under conditions of uncertainty},\n type = {article},\n year = {2007},\n keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},\n pages = {461-476},\n volume = {31},\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},\n month = {7},\n id = {436883e2-d0c0-3ff3-9a43-47ea1496df8e},\n created = {2015-04-11T15:16:23.000Z},\n accessed = {2015-03-18},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},\n bibtype = {article},\n author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},\n doi = {10.1016/j.compenvurbsys.2007.02.002},\n journal = {Computers, Environment and Urban Systems},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://www.sciencedirect.com/science/article/pii/S0198971507000154', event);\">\n    Modelling land-use decisions under conditions of uncertainty.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ma,  L.; Arentze,  T.; Borgers,  A.;  and Timmermans,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Computers, Environment and Urban Systems</i>, 31(4): 461-476. 7 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0198971507000154\"\n     onclick=\"log_download('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://www.sciencedirect.com/science/article/pii/S0198971507000154', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling land-use decisions under conditions of uncertainty [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compenvurbsys.2007.02.002\"\n     onclick=\"log_download('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007', 'http://doi.org/10.1016/j.compenvurbsys.2007.02.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ma-arentze-borgers-timmermans-modellinglandusedecisionsunderconditionsofuncertainty-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling land-use decisions under conditions of uncertainty},\n type = {article},\n year = {2007},\n keywords = {Bayesian belief networks,Decision making under uncertainty,Decision networks,Land-use planning,Planning support systems,Sampling},\n pages = {461-476},\n volume = {31},\n websites = {http://www.sciencedirect.com/science/article/pii/S0198971507000154},\n month = {7},\n id = {60cdd308-554e-3906-bbf0-382586eb071c},\n created = {2015-04-11T17:37:59.000Z},\n accessed = {2015-03-18},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.},\n bibtype = {article},\n author = {Ma, Linda and Arentze, Theo and Borgers, Aloys and Timmermans, Harry},\n doi = {10.1016/j.compenvurbsys.2007.02.002},\n journal = {Computers, Environment and Urban Systems},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Suitability assessments of candidate locations for a particular land-use are typically uncertain, as future changes in land-use patterns may have an impact on performances while these changes are hard to predict. Most planning support tools for location decisions do not take such uncertainty into account. To address this problem of uncertainty, we propose a ‘Bayesian decision network’ approach. In this approach, the possible courses of actions, causal knowledge and preferences of a decision maker are represented in a network of causal relationships between a set of variables. Uncertainty about future land-use developments, which may influence outcomes of location decisions, can be represented as conditional probabilities in these networks. However, estimating these probabilities for a given study area is not a trivial problem, as the space of all possible future scenarios is approximately infinitely large. In this paper, we propose and test a sampling method for this estimation purpose. As an illustrative case, we specify a decision network model of a retail location planning problem, investigate parameters of the sampling method and explore the extent to which different ways of coping with uncertainty affects outcomes of decisions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006003541', event);\">\n    Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pollino,  C., A.; White,  A., K.;  and Hart,  B., T.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 201(1): 37-59. 2 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"\n     onclick=\"log_download('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006003541', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2006.07.032\"\n     onclick=\"log_download('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://doi.org/10.1016/j.ecolmodel.2006.07.032', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},\n type = {article},\n year = {2007},\n keywords = {Bayesian networks,Endangered species,Hypotheses},\n pages = {37-59},\n volume = {201},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},\n month = {2},\n id = {5d0ffe0d-cdb0-326f-9f54-ba86da63d807},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},\n bibtype = {article},\n author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},\n doi = {10.1016/j.ecolmodel.2006.07.032},\n journal = {Ecological Modelling},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006006089\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006006089', event);\">\n    Advantages and challenges of Bayesian networks in environmental modelling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  \n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 203(3-4): 312-318. 5 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006006089\"\n     onclick=\"log_download('advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006006089', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Advantages and challenges of Bayesian networks in environmental modelling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('advantagesandchallengesofbayesiannetworksinenvironmentalmodelling-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Advantages and challenges of Bayesian networks in environmental modelling},\n type = {article},\n year = {2007},\n pages = {312-318},\n volume = {203},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006006089},\n month = {5},\n id = {983df284-5049-3b1c-92dd-fc5e567896b1},\n created = {2015-04-11T19:51:58.000Z},\n accessed = {2014-07-14},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian networks (BNs) are an increasingly popular method of modelling uncertain and complex domains such as ecosystems and environmental management. At best, they provide a robust and mathematically coherent framework for the analysis of this kind of problems. However, there are certain pitfalls as well. In this paper, I summarise the pros and cons of the use of Bayesian networks especially in the context of environmental modelling and management. I will also give references to relevant publications, and introduce some software products that can be used to build Bayesian networks.},\n bibtype = {article},\n author = {},\n journal = {Ecological Modelling},\n number = {3-4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian networks (BNs) are an increasingly popular method of modelling uncertain and complex domains such as ecosystems and environmental management. At best, they provide a robust and mathematically coherent framework for the analysis of this kind of problems. However, there are certain pitfalls as well. In this paper, I summarise the pros and cons of the use of Bayesian networks especially in the context of environmental modelling and management. I will also give references to relevant publications, and introduce some software products that can be used to build Bayesian networks.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481520600137X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007', 'http://www.sciencedirect.com/science/article/pii/S136481520600137X', event);\">\n    Bayesian networks in planning a large aquifer in Eastern Mancha, Spain.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Martín de Santa Olalla,  F.; Dominguez,  A.; Ortega,  F.; Artigao,  A.;  and Fabeiro,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1089-1100. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481520600137X\"\n     onclick=\"log_download('martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007', 'http://www.sciencedirect.com/science/article/pii/S136481520600137X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian networks in planning a large aquifer in Eastern Mancha, Spain [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.05.020\"\n     onclick=\"log_download('martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007', 'http://doi.org/10.1016/j.envsoft.2006.05.020', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('martndesantaolalla-dominguez-ortega-artigao-fabeiro-bayesiannetworksinplanningalargeaquiferineasternmanchaspain-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian networks in planning a large aquifer in Eastern Mancha, Spain},\n type = {article},\n year = {2007},\n keywords = {Aquifer,Bayesian networks,Integrated management,Irrigated land,Stakeholders},\n pages = {1089-1100},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481520600137X},\n month = {8},\n id = {f5832962-d077-3d3c-bc27-5c021c6ad676},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The Eastern Mancha Aquifer is located in the south-east of the Iberian Peninsula and is included in the hydrogeological unit of the same name. This aquifer is the main source of water for urban, industrial and agricultural supply within its area of influence. Over the past 30years, the transformation of dry crop lands in the area of this Unit into irrigated crop lands, through groundwater capture, has caused precise declines in piezometric levels of the aquifer, as extraction volumes have exceeded recharge water volumes. This work illustrates the results obtained by using Bayesian networks in the sustainable planning of the Eastern Mancha aquifer. The actions through which this goal can be met are the partial substitution of groundwater with surface water, the improvement of irrigation efficiency and the adequate control of water use.},\n bibtype = {article},\n author = {Martín de Santa Olalla, Francisco and Dominguez, Alfonso and Ortega, Fernando and Artigao, Alfonso and Fabeiro, Concepción},\n doi = {10.1016/j.envsoft.2006.05.020},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The Eastern Mancha Aquifer is located in the south-east of the Iberian Peninsula and is included in the hydrogeological unit of the same name. This aquifer is the main source of water for urban, industrial and agricultural supply within its area of influence. Over the past 30years, the transformation of dry crop lands in the area of this Unit into irrigated crop lands, through groundwater capture, has caused precise declines in piezometric levels of the aquifer, as extraction volumes have exceeded recharge water volumes. This work illustrates the results obtained by using Bayesian networks in the sustainable planning of the Eastern Mancha aquifer. The actions through which this goal can be met are the partial substitution of groundwater with surface water, the improvement of irrigation efficiency and the adequate control of water use.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000788\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000788', event);\">\n    Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pollino,  C., A.; Woodberry,  O.; Nicholson,  A.; Korb,  K.;  and Hart,  B., T.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1140-1152. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000788\"\n     onclick=\"log_download('pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000788', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.03.006\"\n     onclick=\"log_download('pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007', 'http://doi.org/10.1016/j.envsoft.2006.03.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pollino-woodberry-nicholson-korb-hart-parameterisationandevaluationofabayesiannetworkforuseinanecologicalriskassessment-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment},\n type = {article},\n year = {2007},\n keywords = {Bayesian network,Ecological risk assessment,Ecology,Fish},\n pages = {1140-1152},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000788},\n month = {8},\n id = {c1d8f2b7-97e4-3a66-beda-57aa9fd2f928},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).},\n bibtype = {article},\n author = {Pollino, Carmel A. and Woodberry, Owen and Nicholson, Ann and Korb, Kevin and Hart, Barry T.},\n doi = {10.1016/j.envsoft.2006.03.006},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206001435\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206001435', event);\">\n    Bayesian Networks and participatory modelling in water resource management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Castelletti,  A.;  and Soncini-Sessa,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1075-1088. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206001435\"\n     onclick=\"log_download('castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206001435', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian Networks and participatory modelling in water resource management [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.06.003\"\n     onclick=\"log_download('castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007', 'http://doi.org/10.1016/j.envsoft.2006.06.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('castelletti-soncinisessa-bayesiannetworksandparticipatorymodellinginwaterresourcemanagement-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian Networks and participatory modelling in water resource management},\n type = {article},\n year = {2007},\n keywords = {Bayesian Networks,Decision making,Model integration,Participatory modelling,Water resources planning},\n pages = {1075-1088},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001435},\n month = {8},\n id = {b80f9f8d-5320-37b3-a179-4ff6db8b8547},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.},\n bibtype = {article},\n author = {Castelletti, A. and Soncini-Sessa, R.},\n doi = {10.1016/j.envsoft.2006.06.003},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000491\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000491', event);\">\n    Public participation modelling using Bayesian networks in management of groundwater contamination.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Henriksen,  H., J.; Rasmussen,  P.; Brandt,  G.; von Bülow,  D.;  and Jensen,  F., V.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1101-1113. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000491\"\n     onclick=\"log_download('henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000491', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Public participation modelling using Bayesian networks in management of groundwater contamination [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.01.008\"\n     onclick=\"log_download('henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007', 'http://doi.org/10.1016/j.envsoft.2006.01.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('henriksen-rasmussen-brandt-vonblow-jensen-publicparticipationmodellingusingbayesiannetworksinmanagementofgroundwatercontamination-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Public participation modelling using Bayesian networks in management of groundwater contamination},\n type = {article},\n year = {2007},\n keywords = {Active involvement,Bayesian networks,EDSS,Groundwater management,MERIT,Negotiation,Pesticides,Planning,Public participatory modelling,Stakeholders},\n pages = {1101-1113},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000491},\n month = {8},\n id = {934f4a5c-91a2-3116-8f90-19f6396acf0b},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Negotiation and active involvement with participation of water managers, experts, stakeholders and representatives of the general public requires decision support tools (Environmental Decision Support Systems; EDSS) that build on transparency and flexibility in order to reach sound action plans and management instruments. One possible EDSS for active involvement of stakeholders is application of Bayesian networks (Bns). The paper gives an example of a case study (The Danish case) where farmers and hydrologists disputed the degree to which pesticide application affected the quality of deep groundwater. Instead of selecting one opinion or another, the decision was made to include both in the Bns. By adopting this approach, it was possible to view the results from either point of view, accepting the reality of the situation, not becoming mired in an insoluble conflict, and in this way laying the foundation for future compromises. The paper explores Bns as a tool for acting on and dealing with management of groundwater protection. Bns allow stakeholders&#x27; divergent values, interests and beliefs to be surfaced and negotiated in participatory processes for areas where conventional physically based groundwater models are insufficient due to lack of data, physical understanding, flexibility or lack of integration capability. In this way, the agency will be able to address the institutional arrangement influencing groundwater protection in all its complexity.},\n bibtype = {article},\n author = {Henriksen, Hans Jørgen and Rasmussen, Per and Brandt, Gyrite and von Bülow, Dorthe and Jensen, Finn V.},\n doi = {10.1016/j.envsoft.2006.01.008},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Negotiation and active involvement with participation of water managers, experts, stakeholders and representatives of the general public requires decision support tools (Environmental Decision Support Systems; EDSS) that build on transparency and flexibility in order to reach sound action plans and management instruments. One possible EDSS for active involvement of stakeholders is application of Bayesian networks (Bns). The paper gives an example of a case study (The Danish case) where farmers and hydrologists disputed the degree to which pesticide application affected the quality of deep groundwater. Instead of selecting one opinion or another, the decision was made to include both in the Bns. By adopting this approach, it was possible to view the results from either point of view, accepting the reality of the situation, not becoming mired in an insoluble conflict, and in this way laying the foundation for future compromises. The paper explores Bns as a tool for acting on and dealing with management of groundwater protection. Bns allow stakeholders' divergent values, interests and beliefs to be surfaced and negotiated in participatory processes for areas where conventional physically based groundwater models are insufficient due to lack of data, physical understanding, flexibility or lack of integration capability. In this way, the agency will be able to address the institutional arrangement influencing groundwater protection in all its complexity.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206001344\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206001344', event);\">\n    Coupling real-time control and socio-economic issues in participatory river basin planning.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Castelletti,  A.;  and Soncini-Sessa,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1114-1128. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206001344\"\n     onclick=\"log_download('castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206001344', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Coupling real-time control and socio-economic issues in participatory river basin planning [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.05.018\"\n     onclick=\"log_download('castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007', 'http://doi.org/10.1016/j.envsoft.2006.05.018', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('castelletti-soncinisessa-couplingrealtimecontrolandsocioeconomicissuesinparticipatoryriverbasinplanning-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Coupling real-time control and socio-economic issues in participatory river basin planning},\n type = {article},\n year = {2007},\n keywords = {Bayesian Networks,Integrated Water Resource Management,Model integration,Participation,Reservoir operation},\n pages = {1114-1128},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206001344},\n month = {8},\n id = {580f894f-d644-37c5-ad08-eae4a743a324},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.},\n bibtype = {article},\n author = {Castelletti, A. and Soncini-Sessa, R.},\n doi = {10.1016/j.envsoft.2006.05.018},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper an approach for coupling real-time control and socio-economic issues in participatory river basin planning is presented through a case study. It relies on the use of Bayesian Networks (Bns) to describe in a probabilistic way the behaviour of farmers within an irrigation district in response to some planning actions. Bayesian Networks are coupled with classical stochastic hydrological models in a decision-making framework concerning the real-time control of a water reservoir network. The approach is embedded within the framework of the Participatory and Integrated Planning (PIP) procedure.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000764\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000764', event);\">\n    A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ticehurst,  J., L.; Newham,  L., T.; Rissik,  D.; Letcher,  R., A.;  and Jakeman,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 22(8): 1129-1139. 8 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815206000764\"\n     onclick=\"log_download('ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007', 'http://www.sciencedirect.com/science/article/pii/S1364815206000764', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2006.03.003\"\n     onclick=\"log_download('ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007', 'http://doi.org/10.1016/j.envsoft.2006.03.003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ticehurst-newham-rissik-letcher-jakeman-abayesiannetworkapproachforassessingthesustainabilityofcoastallakesinnewsouthwalesaustralia-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia},\n type = {article},\n year = {2007},\n keywords = {Bayesian network,Coastal lakes,Decision support,Environmental management,Integrated assessment,Pathogens,Sustainability},\n pages = {1129-1139},\n volume = {22},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815206000764},\n month = {8},\n id = {b32c69b2-ca0d-3ddb-93b2-8e9e7fbe8cfe},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.},\n bibtype = {article},\n author = {Ticehurst, Jenifer L. and Newham, Lachlan T.H. and Rissik, David and Letcher, Rebecca A. and Jakeman, Anthony J.},\n doi = {10.1016/j.envsoft.2006.03.003},\n journal = {Environmental Modelling &amp; Software},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006003541', event);\">\n    Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pollino,  C., A.; White,  A., K.;  and Hart,  B., T.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Modelling</i>, 201(1): 37-59. 2 2007.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0304380006003541\"\n     onclick=\"log_download('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://www.sciencedirect.com/science/article/pii/S0304380006003541', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ecolmodel.2006.07.032\"\n     onclick=\"log_download('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007', 'http://doi.org/10.1016/j.ecolmodel.2006.07.032', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pollino-white-hart-examinationofconflictsandimprovedstrategiesforthemanagementofanendangeredeucalyptspeciesusingbayesiannetworks-2007')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks},\n type = {article},\n year = {2007},\n keywords = {Bayesian networks,Endangered species,Hypotheses},\n pages = {37-59},\n volume = {201},\n websites = {http://www.sciencedirect.com/science/article/pii/S0304380006003541},\n month = {2},\n id = {c6a17f4b-1f28-3b4b-9550-5d882a385c0c},\n created = {2015-04-12T20:17:32.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.},\n bibtype = {article},\n author = {Pollino, Carmel A. and White, Andrea K. and Hart, Barry T.},\n doi = {10.1016/j.ecolmodel.2006.07.032},\n journal = {Ecological Modelling},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2005\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2005')\"\n      onkeypress=\"toggleGroup('group_2005')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2005</span>\n      <span class=\"bibbase_group_count\">\n        \n        (2)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377405000818\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005', 'http://www.sciencedirect.com/science/article/pii/S0378377405000818', event);\">\n    Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Martín de Santa Olalla,  F.; Domínguez,  A.; Artigao,  A.; Fabeiro,  C.;  and Ortega,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Water Management</i>, 77(1-3): 21-36. 8 2005.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378377405000818\"\n     onclick=\"log_download('martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005', 'http://www.sciencedirect.com/science/article/pii/S0378377405000818', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.agwat.2004.09.029\"\n     onclick=\"log_download('martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005', 'http://doi.org/10.1016/j.agwat.2004.09.029', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('martndesantaolalla-domnguez-artigao-fabeiro-ortega-integratedwaterresourcesmanagementofthehydrogeologicaluniteasternmanchausingbayesianbeliefnetworks-2005')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Integrated water resources management of the Hydrogeological Unit “Eastern Mancha” using Bayesian Belief Networks},\n type = {article},\n year = {2005},\n keywords = {Bayesian Networks,Irrigated land,Overexploitation,Stakeholders},\n pages = {21-36},\n volume = {77},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378377405000818},\n month = {8},\n id = {eeeb90f3-7bd6-33de-87b5-af5d9033a066},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Included into the objectives of the EU Water Framework Directive (Directive 2000/60/EC) there are the correct management of the water resources and the involvement of the stakeholders in the decision process. Bayesian Networks, mathematical models based on the probability theory, have been used recently to solve environmental problems. This methodology meets the relevant requirements to the effect that it is fully comprehensive and integrated, as it deals with the water resource as a whole and encourages the participation of all those people and groups who are somehow involved in its use or management. A Bayesian Network was developed by means of stakeholders participation which is intended to be useful in the decision-making process related to water resource management in the Hydrogeological Unit “Eastern Mancha”. The main problem in the region is the risk of overexploitation of the local aquifer, brought about by a considerable increase, over the last 25 years, in the surface area of irrigated arable land. The results offered by the tool show that the current situation is non-sustainable concerning the aquifer exploitation. There are several ways to solve this situation. The first one could be decreasing the current volume of ground water for irrigation, but this solution would not be welcome by the farmers due to losses of income. The second one is replacing groundwater for irrigation by surface water, where the main problem would be the considerable expenses in infrastructures.},\n bibtype = {article},\n author = {Martín de Santa Olalla, F.J. and Domínguez, A. and Artigao, A. and Fabeiro, C. and Ortega, J.F.},\n doi = {10.1016/j.agwat.2004.09.029},\n journal = {Agricultural Water Management},\n number = {1-3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Included into the objectives of the EU Water Framework Directive (Directive 2000/60/EC) there are the correct management of the water resources and the involvement of the stakeholders in the decision process. Bayesian Networks, mathematical models based on the probability theory, have been used recently to solve environmental problems. This methodology meets the relevant requirements to the effect that it is fully comprehensive and integrated, as it deals with the water resource as a whole and encourages the participation of all those people and groups who are somehow involved in its use or management. A Bayesian Network was developed by means of stakeholders participation which is intended to be useful in the decision-making process related to water resource management in the Hydrogeological Unit “Eastern Mancha”. The main problem in the region is the risk of overexploitation of the local aquifer, brought about by a considerable increase, over the last 25 years, in the surface area of irrigated arable land. The results offered by the tool show that the current situation is non-sustainable concerning the aquifer exploitation. There are several ways to solve this situation. The first one could be decreasing the current volume of ground water for irrigation, but this solution would not be welcome by the farmers due to losses of income. The second one is replacing groundwater for irrigation by surface water, where the main problem would be the considerable expenses in infrastructures.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815204000404\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005', 'http://www.sciencedirect.com/science/article/pii/S1364815204000404', event);\">\n    The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bromley,  J.; Jackson,  N.; Clymer,  O.; Giacomello,  A.;  and Jensen,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 20(2): 231-242. 2 2005.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1364815204000404\"\n     onclick=\"log_download('bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005', 'http://www.sciencedirect.com/science/article/pii/S1364815204000404', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.envsoft.2003.12.021\"\n     onclick=\"log_download('bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005', 'http://doi.org/10.1016/j.envsoft.2003.12.021', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bromley-jackson-clymer-giacomello-jensen-theuseofhugintodevelopbayesiannetworksasanaidtointegratedwaterresourceplanning-2005')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The use of Hugin® to develop Bayesian networks as an aid to integrated water resource planning},\n type = {article},\n year = {2005},\n keywords = {Bayesian network,Integrated water resource management,Stakeholder participation,Uncertainty},\n pages = {231-242},\n volume = {20},\n websites = {http://www.sciencedirect.com/science/article/pii/S1364815204000404},\n month = {2},\n id = {ffad8d16-04b8-3fd8-9c56-255e6e9249a2},\n created = {2015-04-11T19:52:27.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Integrated management is the key to the sustainable development of Europe&#x27;s water resources. This means that decisions need to be taken in the light of not only environmental considerations, but also their economic, social, and political impacts; it also requires the active participation of stakeholders in the decision making process. The problem is to find a practical way to achieve these aims. One approach is to use Bayesian networks (Bns): networks allow a range of different factors to be linked together, based on probabilistic dependencies, and at the same time provide a framework within which the contributions of stakeholders can be taken into account. A further strength is that Bns explicitly include the element of uncertainty related to any strategy or decision. The links are based on whatever data are available. This may be an extensive data set, output from a model or, in the absence of data, can be based on expert opinion. Networks are being developed for four catchments in Europe as part of the MERIT project; these are in the UK, Denmark, Italy and Spain. In each case stakeholder groups are contributing to the design of the networks that are used as a focus for the consultation process. As an example, the application to water management of a UK basin is discussed.},\n bibtype = {article},\n author = {Bromley, J. and Jackson, N.A. and Clymer, O.J. and Giacomello, A.M. and Jensen, F.V.},\n doi = {10.1016/j.envsoft.2003.12.021},\n journal = {Environmental Modelling &amp; Software},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Integrated management is the key to the sustainable development of Europe's water resources. This means that decisions need to be taken in the light of not only environmental considerations, but also their economic, social, and political impacts; it also requires the active participation of stakeholders in the decision making process. The problem is to find a practical way to achieve these aims. One approach is to use Bayesian networks (Bns): networks allow a range of different factors to be linked together, based on probabilistic dependencies, and at the same time provide a framework within which the contributions of stakeholders can be taken into account. A further strength is that Bns explicitly include the element of uncertainty related to any strategy or decision. The links are based on whatever data are available. This may be an extensive data set, output from a model or, in the absence of data, can be based on expert opinion. Networks are being developed for four catchments in Europe as part of the MERIT project; these are in the UK, Denmark, Italy and Spain. In each case stakeholder groups are contributing to the design of the networks that are used as a focus for the consultation process. As an example, the application to water management of a UK basin is discussed.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2004\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2004')\"\n      onkeypress=\"toggleGroup('group_2004')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2004</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0011916404900549\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004', 'http://www.sciencedirect.com/science/article/pii/S0011916404900549', event);\">\n    Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ghabayen,  S.; McKee,  M.;  and Kemblowski,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Desalination</i>, 161(2): 191-201. 2 2004.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0011916404900549\"\n     onclick=\"log_download('ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004', 'http://www.sciencedirect.com/science/article/pii/S0011916404900549', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0011-9164(04)90054-9\"\n     onclick=\"log_download('ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004', 'http://doi.org/10.1016/S0011-9164(04)90054-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ghabayen-mckee-kemblowski-characterizationofuncertaintiesintheoperationandeconomicsoftheproposedseawaterdesalinationplantinthegazastrip-2004')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Characterization of uncertainties in the operation and economics of the proposed seawater desalination plant in the Gaza Strip},\n type = {article},\n year = {2004},\n keywords = {Bayesian belief networks,Desalination,Gaza Strip,Optimization,Reverse osmosis,Uncertainty},\n pages = {191-201},\n volume = {161},\n websites = {http://www.sciencedirect.com/science/article/pii/S0011916404900549},\n month = {2},\n id = {6bb987ae-3066-32eb-afbb-2564d7beae75},\n created = {2015-04-11T17:43:55.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In the Gaza Strip, the available freshwater sources are severely polluted and overused. Desalination of seawater through reverse osmosis (RO) has become the most realistic option to meet a rapidly growing water demand. It is estimated that the Gaza Strip will need to develop a seawater desalination capacity of about 120,000 m3/d by the year 2008, and an additional 30,000 m3/d by the year 2016 in order to maintain a fresh water balance in the coastal aquifer and to fulfill the water demand for different uses in a sustainable manner. Cost and reliability of a large RO facility are still subject to much uncertainty. The cost of seawater desalination by RO systems varies with facility size and lifetime, financing conditions, intake type and pre-treatment requirements, power requirements, recovery rate, chemicals cost, spare parts cost, and membrane replacement cost. The permeate salinity is a function of feed water temperature, recovery rate, and permeate flux. The quantity of water produced depends mainly on plant size, recovery rate, and operating load factor. Many of these parameters are subject to a great deal of uncertainty. The objective of this work is to develop a probabilistic model for the simulation of seawater reverse osmosis processes using a Bayesian belief network (BBN) approach. This model represents a new application of probabilistic modeling tools to a large-scale complex system. The model is used to: (1) characterize the different uncertainties involved in the RO process; (2) optimize the RO process reliability and cost; and (3) study how uncertainty in unit capital cost, unit operation and maintenance (O&amp;M) cost, and permeate quality is related to different input variables. The model utilizes information from journal articles, books, expert opinions, and technical reports related to the study area, and can be used to support operators and decision makers in the design of RO systems and formulation of operational policies. The structure of the model is not specific to the Gaza Strip and can be easily populated with data from any large-scale RO plant in any part of the world.},\n bibtype = {article},\n author = {Ghabayen, Said and McKee, Mac and Kemblowski, Mariush},\n doi = {10.1016/S0011-9164(04)90054-9},\n journal = {Desalination},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In the Gaza Strip, the available freshwater sources are severely polluted and overused. Desalination of seawater through reverse osmosis (RO) has become the most realistic option to meet a rapidly growing water demand. It is estimated that the Gaza Strip will need to develop a seawater desalination capacity of about 120,000 m3/d by the year 2008, and an additional 30,000 m3/d by the year 2016 in order to maintain a fresh water balance in the coastal aquifer and to fulfill the water demand for different uses in a sustainable manner. Cost and reliability of a large RO facility are still subject to much uncertainty. The cost of seawater desalination by RO systems varies with facility size and lifetime, financing conditions, intake type and pre-treatment requirements, power requirements, recovery rate, chemicals cost, spare parts cost, and membrane replacement cost. The permeate salinity is a function of feed water temperature, recovery rate, and permeate flux. The quantity of water produced depends mainly on plant size, recovery rate, and operating load factor. Many of these parameters are subject to a great deal of uncertainty. The objective of this work is to develop a probabilistic model for the simulation of seawater reverse osmosis processes using a Bayesian belief network (BBN) approach. This model represents a new application of probabilistic modeling tools to a large-scale complex system. The model is used to: (1) characterize the different uncertainties involved in the RO process; (2) optimize the RO process reliability and cost; and (3) study how uncertainty in unit capital cost, unit operation and maintenance (O&M) cost, and permeate quality is related to different input variables. The model utilizes information from journal articles, books, expert opinions, and technical reports related to the study area, and can be used to support operators and decision makers in the design of RO systems and formulation of operational policies. The structure of the model is not specific to the Gaza Strip and can be easily populated with data from any large-scale RO plant in any part of the world.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2003\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2003')\"\n      onkeypress=\"toggleGroup('group_2003')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2003</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X02000069\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003', 'http://www.sciencedirect.com/science/article/pii/S0308521X02000069', event);\">\n    Participatory decision support for agricultural management. A case study from Sri Lanka.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Cain,  J.; Jinapala,  K.; Makin,  I.; Somaratna,  P.; Ariyaratna,  B.;  and Perera,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Agricultural Systems</i>, 76(2): 457-482. 5 2003.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0308521X02000069\"\n     onclick=\"log_download('cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003', 'http://www.sciencedirect.com/science/article/pii/S0308521X02000069', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Participatory decision support for agricultural management. A case study from Sri Lanka [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0308-521X(02)00006-9\"\n     onclick=\"log_download('cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003', 'http://doi.org/10.1016/S0308-521X(02)00006-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('cain-jinapala-makin-somaratna-ariyaratna-perera-participatorydecisionsupportforagriculturalmanagementacasestudyfromsrilanka-2003')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Participatory decision support for agricultural management. A case study from Sri Lanka},\n type = {article},\n year = {2003},\n keywords = {Agricultural management,Agricultural policy,Bayesian network,Decision support system,Integrated management,Sri Lanka,Stakeholder participation},\n pages = {457-482},\n volume = {76},\n websites = {http://www.sciencedirect.com/science/article/pii/S0308521X02000069},\n month = {5},\n id = {ea7f2f84-1ccf-376d-a2da-1cfe7620b78a},\n created = {2015-04-11T19:52:01.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Agricultural policy makers were helped to construct and use a decision support system (DSS) to identify problems and assess potential solutions for a river basin in Sri Lanka. Through building the DSS themselves, policy makers should reach better decisions. The main aim of the study was to test whether this could be done using a tool called a Bayesian network (BN) which is accessible to non-specialists and able to provide a generic, flexible framework for the construction of DSS. Results from a workshop indicated that the approach showed promise, providing a common framework for discussion and allowing policy makers to structure complex systems from a multi-disciplinary perspective. The need for a multi-disciplinary perspective was clearly demonstrated. The study also suggested improvements to the ways in which BNs can be used in practice. Further workshops with farmers highlighted the importance of involving them in the planning process and suggested more effective ways of doing this while using BNs.},\n bibtype = {article},\n author = {Cain, J.D and Jinapala, K and Makin, I.W and Somaratna, P.G and Ariyaratna, B.R and Perera, L.R},\n doi = {10.1016/S0308-521X(02)00006-9},\n journal = {Agricultural Systems},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Agricultural policy makers were helped to construct and use a decision support system (DSS) to identify problems and assess potential solutions for a river basin in Sri Lanka. Through building the DSS themselves, policy makers should reach better decisions. The main aim of the study was to test whether this could be done using a tool called a Bayesian network (BN) which is accessible to non-specialists and able to provide a generic, flexible framework for the construction of DSS. Results from a workshop indicated that the approach showed promise, providing a common framework for discussion and allowing policy makers to structure complex systems from a multi-disciplinary perspective. The need for a multi-disciplinary perspective was clearly demonstrated. The study also suggested improvements to the ways in which BNs can be used in practice. Further workshops with farmers highlighted the importance of involving them in the planning process and suggested more effective ways of doing this while using BNs.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2002\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2002')\"\n      onkeypress=\"toggleGroup('group_2002')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2002</span>\n      <span class=\"bibbase_group_count\">\n        \n        (3)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://www.sciencedirect.com/science/article/pii/S0301479701905079', event);\">\n    Belief network models of land manager decisions and land use change.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bacon,  P.; Cain,  J.;  and Howard,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Environmental Management</i>, 65(1): 1-23. 5 2002.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"\n     onclick=\"log_download('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://www.sciencedirect.com/science/article/pii/S0301479701905079', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Belief network models of land manager decisions and land use change [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1006/jema.2001.0507\"\n     onclick=\"log_download('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://doi.org/10.1006/jema.2001.0507', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Belief network models of land manager decisions and land use change},\n type = {article},\n year = {2002},\n keywords = {conflict resolution, conservation, decision models},\n pages = {1-23},\n volume = {65},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},\n month = {5},\n id = {644a8604-5091-3090-9bf5-2d5e8e303042},\n created = {2015-04-11T15:16:23.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},\n bibtype = {article},\n author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},\n doi = {10.1006/jema.2001.0507},\n journal = {Journal of Environmental Management},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://www.sciencedirect.com/science/article/pii/S0301479701905079', event);\">\n    Belief network models of land manager decisions and land use change.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bacon,  P.; Cain,  J.;  and Howard,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Environmental Management</i>, 65(1): 1-23. 5 2002.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0301479701905079\"\n     onclick=\"log_download('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://www.sciencedirect.com/science/article/pii/S0301479701905079', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Belief network models of land manager decisions and land use change [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1006/jema.2001.0507\"\n     onclick=\"log_download('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002', 'http://doi.org/10.1006/jema.2001.0507', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bacon-cain-howard-beliefnetworkmodelsoflandmanagerdecisionsandlandusechange-2002')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Belief network models of land manager decisions and land use change},\n type = {article},\n year = {2002},\n keywords = {conflict resolution, conservation, decision models},\n pages = {1-23},\n volume = {65},\n websites = {http://www.sciencedirect.com/science/article/pii/S0301479701905079},\n month = {5},\n id = {b0ff7057-ddd3-325a-b3b4-c0b07cdab630},\n created = {2015-04-11T17:55:11.000Z},\n accessed = {2015-03-12},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.},\n bibtype = {article},\n author = {Bacon, P.J. and Cain, J.D. and Howard, D.C.},\n doi = {10.1006/jema.2001.0507},\n journal = {Journal of Environmental Management},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A two-stage model of land use change is described, which is driven by the types of decisions that land managers make when changing their broad styles of use. The first stage uses decision modelling techniques to assess if a manager is currently satisfied with the present situation, when compared to various potential alternatives. If this evaluation indicates satisfaction, it is assumed that the present land use will continue. However, if it indicates dissatisfaction, Belief Network techniques are used to estimate, in more detail, both how dissatisfied the manager is and whether the costs of changing, from the present use to a potentially better one, will be out-weighed by the anticipated benefits. The proposed models can use a variety of cost and benefit criteria (e.g. financial, social and ecological). The approach is illustrated with a case-study of the factors that might influence changes from farming to forestry in marginal upland areas of the UK.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X02000055\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002', 'http://www.sciencedirect.com/science/article/pii/S1470160X02000055', event);\">\n    A meta-assessment for elasmobranchs based on dietary data and Bayesian networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hammond,  T.;  and Ellis,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Ecological Indicators</i>, 1(3): 197-211. 3 2002.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1470160X02000055\"\n     onclick=\"log_download('hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002', 'http://www.sciencedirect.com/science/article/pii/S1470160X02000055', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A meta-assessment for elasmobranchs based on dietary data and Bayesian networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S1470-160X(02)00005-5\"\n     onclick=\"log_download('hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002', 'http://doi.org/10.1016/S1470-160X(02)00005-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hammond-ellis-ametaassessmentforelasmobranchsbasedondietarydataandbayesiannetworks-2002')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A meta-assessment for elasmobranchs based on dietary data and Bayesian networks},\n type = {article},\n year = {2002},\n keywords = {Bayesian networks,Elasmobranchs,Fisheries management,Food webs,Threatened species},\n pages = {197-211},\n volume = {1},\n websites = {http://www.sciencedirect.com/science/article/pii/S1470160X02000055},\n month = {3},\n id = {6cfb406e-23d4-39ad-8c18-503cdcd07905},\n created = {2015-04-11T19:51:57.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.},\n bibtype = {article},\n author = {Hammond, T.R and Ellis, J.R},\n doi = {10.1016/S1470-160X(02)00005-5},\n journal = {Ecological Indicators},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2001\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2001')\"\n      onkeypress=\"toggleGroup('group_2001')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2001</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004534\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004534', event);\">\n    Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rieman,  B.; Peterson,  J., T.; Clayton,  J.; Howell,  P.; Thurow,  R.; Thompson,  W.;  and Lee,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Forest Ecology and Management</i>, 153(1-3): 43-62. 10 2001.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004534\"\n     onclick=\"log_download('rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004534', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0378-1127(01)00453-4\"\n     onclick=\"log_download('rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001', 'http://doi.org/10.1016/S0378-1127(01)00453-4', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rieman-peterson-clayton-howell-thurow-thompson-lee-evaluationofpotentialeffectsoffederallandmanagementalternativesontrendsofsalmonidsandtheirhabitatsintheinteriorcolumbiariverbasin-2001')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin},\n type = {article},\n year = {2001},\n keywords = {Aquatic habitat,Bayesian belief network,Columbia River basin,Fish,Salmon,Trout},\n pages = {43-62},\n volume = {153},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004534},\n month = {10},\n id = {30411cd0-977e-336b-92a0-7fd355045e17},\n created = {2015-04-11T17:55:09.000Z},\n accessed = {2015-03-24},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Aquatic species throughout the interior Columbia River basin are at risk. Evaluation of the potential effects of federal land management on aquatic ecosystems across this region is an important but challenging task. Issues include the size and complexity of the systems, uncertainty in important processes and existing states, flexibility and consistency in the analytical framework, and an ability to quantify results. We focused on salmonid fishes and their habitats as indicators of conditions in aquatic ecosystems and used Bayesian belief networks as a formal, quantitative framework to address the issues in our evaluation of land management alternatives proposed for the interior Columbia River basin. Because empirical information is limited at the scales relevant to our analysis, an ability to combine both empirical and more subjective information was key to the analysis. The representation of linkages through conditional probabilities made uncertainty explicit. We constructed two general networks. One represented the influence of landscape characteristics and existing and predicted management activities on aquatic habitats. A second represented the influence of habitat, existing biotic conditions, and for two anadromous species, ocean and migratory conditions, on the status of six widely distributed salmonid fishes. In the long term (100 years) all three land management alternatives were expected to produce positive changes in the status and distribution of the salmonids and their habitats. Trends were stronger for habitat than for the status of salmonids because of greater uncertainty in linking the fish and habitat networks and constraints outside spawning and rearing habitat on federal lands in the study area. Trends were stronger for resident salmonids than anadromous forms because of additional effects of the migratory corridor assumed for the latter. Alternative S2, which approached ecosystem restoration more conservatively, generally produced the strongest positive changes, and alternative S3, designed to promote more aggressive restoration, the weakest. Averaged across the basin, differences among the alternatives were small. Differences were greater at finer temporal and spatial scales. In the short term (10 years) alternative S3 was expected to lead to further degradation in some areas. By formalizing our understanding and assumptions in these networks, we provided a framework for exploring differences in the management alternatives that is more quantifiable, spatially explicit, and flexible than previous approaches.},\n bibtype = {article},\n author = {Rieman, Bruce and Peterson, James T and Clayton, James and Howell, Philip and Thurow, Russell and Thompson, William and Lee, Danny},\n doi = {10.1016/S0378-1127(01)00453-4},\n journal = {Forest Ecology and Management},\n number = {1-3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Aquatic species throughout the interior Columbia River basin are at risk. Evaluation of the potential effects of federal land management on aquatic ecosystems across this region is an important but challenging task. Issues include the size and complexity of the systems, uncertainty in important processes and existing states, flexibility and consistency in the analytical framework, and an ability to quantify results. We focused on salmonid fishes and their habitats as indicators of conditions in aquatic ecosystems and used Bayesian belief networks as a formal, quantitative framework to address the issues in our evaluation of land management alternatives proposed for the interior Columbia River basin. Because empirical information is limited at the scales relevant to our analysis, an ability to combine both empirical and more subjective information was key to the analysis. The representation of linkages through conditional probabilities made uncertainty explicit. We constructed two general networks. One represented the influence of landscape characteristics and existing and predicted management activities on aquatic habitats. A second represented the influence of habitat, existing biotic conditions, and for two anadromous species, ocean and migratory conditions, on the status of six widely distributed salmonid fishes. In the long term (100 years) all three land management alternatives were expected to produce positive changes in the status and distribution of the salmonids and their habitats. Trends were stronger for habitat than for the status of salmonids because of greater uncertainty in linking the fish and habitat networks and constraints outside spawning and rearing habitat on federal lands in the study area. Trends were stronger for resident salmonids than anadromous forms because of additional effects of the migratory corridor assumed for the latter. Alternative S2, which approached ecosystem restoration more conservatively, generally produced the strongest positive changes, and alternative S3, designed to promote more aggressive restoration, the weakest. Averaged across the basin, differences among the alternatives were small. Differences were greater at finer temporal and spatial scales. In the short term (10 years) alternative S3 was expected to lead to further degradation in some areas. By formalizing our understanding and assumptions in these networks, we provided a framework for exploring differences in the management alternatives that is more quantifiable, spatially explicit, and flexible than previous approaches.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004522', event);\">\n    Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Marcot,  B., G.; Holthausen,  R., S.; Raphael,  M., G.; Rowland,  M., M.;  and Wisdom,  M., J.\n</span>\n\n  \n\n</span>\n\n  <i>Forest Ecology and Management</i>, 153(1-3): 29-42. 10 2001.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"\n     onclick=\"log_download('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004522', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0378-1127(01)00452-2\"\n     onclick=\"log_download('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://doi.org/10.1016/S0378-1127(01)00452-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},\n type = {article},\n year = {2001},\n keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},\n pages = {29-42},\n volume = {153},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},\n month = {10},\n id = {2a076313-dfae-38fb-b4b2-d549d498e92e},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},\n bibtype = {article},\n author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},\n doi = {10.1016/S0378-1127(01)00452-2},\n journal = {Forest Ecology and Management},\n number = {1-3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1093019101000958\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001', 'http://www.sciencedirect.com/science/article/pii/S1093019101000958', event);\">\n    The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pal,  C.; Swayne,  D.;  and Frey,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Advances in Environmental Research</i>, 5(4): 435-444. 11 2001.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S1093019101000958\"\n     onclick=\"log_download('pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001', 'http://www.sciencedirect.com/science/article/pii/S1093019101000958', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S1093-0191(01)00095-8\"\n     onclick=\"log_download('pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001', 'http://doi.org/10.1016/S1093-0191(01)00095-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pal-swayne-frey-theautomatedextractionofenvironmentallyrelevantfeaturesfromdigitalimageryusingbayesianmultiresolutionanalysis-2001')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis},\n type = {article},\n year = {2001},\n keywords = {Bayesian networks,Computer vision,Ecosystem analysis,Hydrologic modeling,Image analysis,Image feature extraction,Image segmentation,Knowledge integration,Monitoring urban growth},\n pages = {435-444},\n volume = {5},\n websites = {http://www.sciencedirect.com/science/article/pii/S1093019101000958},\n month = {11},\n id = {40ab50eb-80b4-34d8-882d-a222c43f65d0},\n created = {2015-04-11T19:52:11.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {In this paper, we discuss the use of hierarchical tree-structured Bayesian networks for integrating knowledge concerning contextual relationships between environmentally relevant features extracted from digital imagery at multiple resolution scales. In our model, conditional probability distributions over continuous valued observations are parameterized using a mixture of multivariate Gaussian distributions. Separate classifiers for pixels and groups of pixels are used as sub-components of the overall model. The Bayesian formalism allows models to be composed in a systematic and statistically sound manner. We illustrate how this approach can be used to resolve ambiguity leading to classification errors and thus improve techniques for the classification of land use from aerial imagery. We present an example relevant to ecosystem analysis, the monitoring of urban growth and the automatic generation of input parameters for hydrologic models.},\n bibtype = {article},\n author = {Pal, Chris and Swayne, Dave and Frey, Brendan},\n doi = {10.1016/S1093-0191(01)00095-8},\n journal = {Advances in Environmental Research},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper, we discuss the use of hierarchical tree-structured Bayesian networks for integrating knowledge concerning contextual relationships between environmentally relevant features extracted from digital imagery at multiple resolution scales. In our model, conditional probability distributions over continuous valued observations are parameterized using a mixture of multivariate Gaussian distributions. Separate classifiers for pixels and groups of pixels are used as sub-components of the overall model. The Bayesian formalism allows models to be composed in a systematic and statistically sound manner. We illustrate how this approach can be used to resolve ambiguity leading to classification errors and thus improve techniques for the classification of land use from aerial imagery. We present an example relevant to ecosystem analysis, the monitoring of urban growth and the automatic generation of input parameters for hydrologic models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004522', event);\">\n    Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Marcot,  B., G.; Holthausen,  R., S.; Raphael,  M., G.; Rowland,  M., M.;  and Wisdom,  M., J.\n</span>\n\n  \n\n</span>\n\n  <i>Forest Ecology and Management</i>, 153(1-3): 29-42. 10 2001.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0378112701004522\"\n     onclick=\"log_download('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://www.sciencedirect.com/science/article/pii/S0378112701004522', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0378-1127(01)00452-2\"\n     onclick=\"log_download('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001', 'http://doi.org/10.1016/S0378-1127(01)00452-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('marcot-holthausen-raphael-rowland-wisdom-usingbayesianbeliefnetworkstoevaluatefishandwildlifepopulationviabilityunderlandmanagementalternativesfromanenvironmentalimpactstatement-2001')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement},\n type = {article},\n year = {2001},\n keywords = {Bayesian belief networks,Bayesian statistics,Columbia River,Fish modeling,Interior Columbia basin,Population viability,Wildlife modeling},\n pages = {29-42},\n volume = {153},\n websites = {http://www.sciencedirect.com/science/article/pii/S0378112701004522},\n month = {10},\n id = {2b9e25b4-1810-3167-ae7a-a2d6c0ba496a},\n created = {2015-04-12T19:47:10.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.},\n bibtype = {article},\n author = {Marcot, Bruce G and Holthausen, Richard S and Raphael, Martin G and Rowland, Mary M and Wisdom, Michael J},\n doi = {10.1016/S0378-1127(01)00452-2},\n journal = {Forest Ecology and Management},\n number = {1-3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We developed procedures for using Bayesian belief networks (BBNs) to model habitat and population viability of selected at-risk fish and wildlife species. The BBN models represent the ecological causal web of key environmental correlates (KECs) that most influence habitat capability, potential population response for each species, and influence of habitat planning alternatives. BBN models represent site-specific KECs, habitat capability at the subwatershed level, and pattern of habitat capability across all subwatersheds. BBNs use Dirichlet prior probability distributions and standard Bayesian updating of posterior probabilities. We derived estimates of prior and conditional probabilities from a mix of empirical data and expert judgment, mostly the latter. Sensitivity analyses identified planning decisions and KECs that most influence species outcomes, and can help prioritize monitoring activities. BBN models, however, substitute for neither field studies nor empirical, quantitative population viability analyses of population demography and genetics.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_1998\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_1998')\"\n      onkeypress=\"toggleGroup('group_1998')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>1998</span>\n      <span class=\"bibbase_group_count\">\n        \n        (1)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0004370298000101\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998', 'http://www.sciencedirect.com/science/article/pii/S0004370298000101', event);\">\n    A belief network approach to optimization and parameter estimation: application to resource and environmental management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Vans,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Artificial Intelligence</i>, 101(1-2): 135-163. 5 1998.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0004370298000101\"\n     onclick=\"log_download('vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998', 'http://www.sciencedirect.com/science/article/pii/S0004370298000101', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A belief network approach to optimization and parameter estimation: application to resource and environmental management [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0004-3702(98)00010-1\"\n     onclick=\"log_download('vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998', 'http://doi.org/10.1016/S0004-3702(98)00010-1', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vans-abeliefnetworkapproachtooptimizationandparameterestimationapplicationtoresourceandenvironmentalmanagement-1998')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A belief network approach to optimization and parameter estimation: application to resource and environmental management},\n type = {article},\n year = {1998},\n keywords = {Bayesian methods,Belief networks,Environmental policies,Hybrid models,Optimization,Parameter estimation,Probabilistic models,Resource management,Water quality},\n pages = {135-163},\n volume = {101},\n websites = {http://www.sciencedirect.com/science/article/pii/S0004370298000101},\n month = {5},\n id = {a8d856d9-f8bc-359d-8fb6-63d912a186ee},\n created = {2015-04-11T18:33:33.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {An approach to use Bayesian belief networks in optimization is presented, with an illustration on resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of that model. The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various policy options. Also multiobjective optimization is possible. The approach is illustrated with an example on cost-effective management of river water quality.},\n bibtype = {article},\n author = {Vans, Olli},\n doi = {10.1016/S0004-3702(98)00010-1},\n journal = {Artificial Intelligence},\n number = {1-2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  An approach to use Bayesian belief networks in optimization is presented, with an illustration on resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of that model. The divergence between prior and posterior probability distributions at the model components is used as an indication on the inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various policy options. Also multiobjective optimization is possible. The approach is illustrated with an example on cost-effective management of river water quality.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_1997\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_1997')\"\n      onkeypress=\"toggleGroup('group_1997')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>1997</span>\n      <span class=\"bibbase_group_count\">\n        \n        (2)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481529700008X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997', 'http://www.sciencedirect.com/science/article/pii/S136481529700008X', event);\">\n    Bayesian decision analysis for environmental and resource management.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Varis,  O.\n</span>\n\n  \n\n</span>\n\n  <i>Environmental Modelling & Software</i>, 12(2-3): 177-185. 1 1997.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S136481529700008X\"\n     onclick=\"log_download('varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997', 'http://www.sciencedirect.com/science/article/pii/S136481529700008X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Bayesian decision analysis for environmental and resource management [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S1364-8152(97)00008-X\"\n     onclick=\"log_download('varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997', 'http://doi.org/10.1016/S1364-8152(97)00008-X', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('varis-bayesiandecisionanalysisforenvironmentalandresourcemanagement-1997')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Bayesian decision analysis for environmental and resource management},\n type = {article},\n year = {1997},\n keywords = {Bayesian inference,belief networks,decision analysis,influence diagrams,risk,uncertainty,value of information},\n pages = {177-185},\n volume = {12},\n websites = {http://www.sciencedirect.com/science/article/pii/S136481529700008X},\n month = {1},\n id = {1fbcbc94-b930-34e8-afeb-2528dc5c3fac},\n created = {2015-04-11T18:56:32.000Z},\n accessed = {2015-03-03},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {During the last two decades, much of the theoretical and practical advances in Bayesian decision analysis have been closely linked to the adaptation of emerging new computational — usually Artificial Intelligence — techniques and to progress in computer software, respectively. This paper documents and discusses experience on the use of two recent network model approaches, influence diagrams and belief networks, and relates those approaches to decision trees. They both allow probabilistic, Bayesian studies with classical decision analytic concepts such as risk attitude analysis, value of information and control, multi-attribute analysis, and various structural analyses. The theory of influence diagrams dates back to the early 1980s, and a variety of commercial software are on market. Belief network is a more recent concept that is under process of finding its way to applications. Illustration on environmental and resource management is provided with examples on freshwater and fisheries studies.},\n bibtype = {article},\n author = {Varis, Olli},\n doi = {10.1016/S1364-8152(97)00008-X},\n journal = {Environmental Modelling &amp; Software},\n number = {2-3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  During the last two decades, much of the theoretical and practical advances in Bayesian decision analysis have been closely linked to the adaptation of emerging new computational — usually Artificial Intelligence — techniques and to progress in computer software, respectively. This paper documents and discusses experience on the use of two recent network model approaches, influence diagrams and belief networks, and relates those approaches to decision trees. They both allow probabilistic, Bayesian studies with classical decision analytic concepts such as risk attitude analysis, value of information and control, multi-attribute analysis, and various structural analyses. The theory of influence diagrams dates back to the early 1980s, and a variety of commercial software are on market. Belief network is a more recent concept that is under process of finding its way to applications. Illustration on environmental and resource management is provided with examples on freshwater and fisheries studies.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0168169997013227\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997', 'http://www.sciencedirect.com/science/article/pii/S0168169997013227', event);\">\n    Modelling uncertainty in agricultural image analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Onyango,  C., M.; Marchant,  J., A.;  and Zwiggelaar,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Electronics in Agriculture</i>, 17(3): 295-305. 6 1997.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/S0168169997013227\"\n     onclick=\"log_download('onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997', 'http://www.sciencedirect.com/science/article/pii/S0168169997013227', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling uncertainty in agricultural image analysis [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/S0168-1699(97)01322-7\"\n     onclick=\"log_download('onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997', 'http://doi.org/10.1016/S0168-1699(97)01322-7', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('onyango-marchant-zwiggelaar-modellinguncertaintyinagriculturalimageanalysis-1997')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling uncertainty in agricultural image analysis},\n type = {article},\n year = {1997},\n keywords = {Algorithm fusion,Bayesian networks,Image analysis,Uncertainty},\n pages = {295-305},\n volume = {17},\n websites = {http://www.sciencedirect.com/science/article/pii/S0168169997013227},\n month = {6},\n id = {112c3213-8659-3cee-b728-b0bb21b9bb65},\n created = {2015-04-12T17:48:22.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {No absolute certainty can be given for information derived for images. In most cases image analysis uses single algorithms, or multiple single algorithms&#x27; results which are combined in an ad hoc manner, to derive certain information (e.g. edges and textures) to segment images into various regions of interest. However, more robust methods of data fusion can be developed which are based on mathematical foundations of probability theory. One such method combines results from single algorithms using a Bayesian network. This should improve the confidence in the derived image segmentation and gives a direct measure of the probability of each region to be classified correctly. Specific agricultural examples using a Bayesian data fusion approach are given.},\n bibtype = {article},\n author = {Onyango, Christine M. and Marchant, John A. and Zwiggelaar, Reyer},\n doi = {10.1016/S0168-1699(97)01322-7},\n journal = {Computers and Electronics in Agriculture},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  No absolute certainty can be given for information derived for images. In most cases image analysis uses single algorithms, or multiple single algorithms' results which are combined in an ad hoc manner, to derive certain information (e.g. edges and textures) to segment images into various regions of interest. However, more robust methods of data fusion can be developed which are based on mathematical foundations of probability theory. One such method combines results from single algorithms using a Bayesian network. This should improve the confidence in the derived image segmentation and gives a direct measure of the probability of each region to be classified correctly. Specific agricultural examples using a Bayesian data fusion approach are given.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_1996\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_1996')\"\n      onkeypress=\"toggleGroup('group_1996')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>1996</span>\n      <span class=\"bibbase_group_count\">\n        \n        (2)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/0954181096000039\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996', 'http://www.sciencedirect.com/science/article/pii/0954181096000039', event);\">\n    Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chong,  H.;  and Walley,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Artificial Intelligence in Engineering</i>, 10(3): 265-273. 8 1996.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/0954181096000039\"\n     onclick=\"log_download('chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996', 'http://www.sciencedirect.com/science/article/pii/0954181096000039', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/0954-1810(96)00003-9\"\n     onclick=\"log_download('chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996', 'http://doi.org/10.1016/0954-1810(96)00003-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chong-walley-rulebasedversusprobabilisticapproachestothediagnosisoffaultsinwastewatertreatmentprocesses-1996')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes},\n type = {article},\n year = {1996},\n keywords = {Bayesian belief networks,causal belief networks,diagnosis,expert systems,rulebased systems,uncertainty,wastewater treatment},\n pages = {265-273},\n volume = {10},\n websites = {http://www.sciencedirect.com/science/article/pii/0954181096000039},\n month = {8},\n id = {ac924305-ac28-37c9-90aa-5e5f4444ce33},\n created = {2015-04-11T18:46:33.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {The need for computer-based diagnostic tools in wastewater management is outlined. Rule-based and probabilistic approaches to the development of diagnostic expert systems are critically reviewed, and it is demonstrated that the rule-based approach has serious limitations which make it unsuitable for diagnostic tasks under conditions of uncertainty. It is shown that Bayesian belief networks (BBNs), a probabilistic approach, has none of these limitations and is well-suited to diagnosis under uncertainty. The theory and application of BBNs are outlined and illustrated by a simple example based on a wastewater treatment plant. A brief case study is presented of the development of a full-scale BBN for the diagnosis of faults in a wastewater treatment plant. It is concluded that BBNs are far superior to rule-based systems in their ability to diagnose faults in complex systems like wastewater treatment processes, whose behaviour is inherently uncertain.},\n bibtype = {article},\n author = {Chong, H.G. and Walley, W.J.},\n doi = {10.1016/0954-1810(96)00003-9},\n journal = {Artificial Intelligence in Engineering},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The need for computer-based diagnostic tools in wastewater management is outlined. Rule-based and probabilistic approaches to the development of diagnostic expert systems are critically reviewed, and it is demonstrated that the rule-based approach has serious limitations which make it unsuitable for diagnostic tasks under conditions of uncertainty. It is shown that Bayesian belief networks (BBNs), a probabilistic approach, has none of these limitations and is well-suited to diagnosis under uncertainty. The theory and application of BBNs are outlined and illustrated by a simple example based on a wastewater treatment plant. A brief case study is presented of the development of a full-scale BBN for the diagnosis of faults in a wastewater treatment plant. It is concluded that BBNs are far superior to rule-based systems in their ability to diagnose faults in complex systems like wastewater treatment processes, whose behaviour is inherently uncertain.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/0169207095006648\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996', 'http://www.sciencedirect.com/science/article/pii/0169207095006648', event);\">\n    Hailfinder: A Bayesian system for forecasting severe weather.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Abramson,  B.; Brown,  J.; Edwards,  W.; Murphy,  A.;  and Winkler,  R., L.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Forecasting</i>, 12(1): 57-71. 3 1996.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.sciencedirect.com/science/article/pii/0169207095006648\"\n     onclick=\"log_download('abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996', 'http://www.sciencedirect.com/science/article/pii/0169207095006648', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Hailfinder: A Bayesian system for forecasting severe weather [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/0169-2070(95)00664-8\"\n     onclick=\"log_download('abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996', 'http://doi.org/10.1016/0169-2070(95)00664-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('abramson-brown-edwards-murphy-winkler-hailfinderabayesiansystemforforecastingsevereweather-1996')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Hailfinder: A Bayesian system for forecasting severe weather},\n type = {article},\n year = {1996},\n keywords = {Bayesian,Belief networks,Elicitation,Intelligent systems,Meteorology,System design,Weather forecasting},\n pages = {57-71},\n volume = {12},\n websites = {http://www.sciencedirect.com/science/article/pii/0169207095006648},\n month = {3},\n id = {edb592f0-50e3-39c0-98f3-18b2f3c8b066},\n created = {2015-04-11T19:07:35.000Z},\n accessed = {2015-04-11},\n file_attached = {false},\n profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},\n group_id = {71a29c65-85d2-3809-a3a1-fe4a94dc78d2},\n last_modified = {2017-03-14T14:27:45.955Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n private_publication = {false},\n abstract = {Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.},\n bibtype = {article},\n author = {Abramson, Bruce and Brown, John and Edwards, Ward and Murphy, Allan and Winkler, Robert L.},\n doi = {10.1016/0169-2070(95)00664-8},\n journal = {International Journal of Forecasting},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);