@article{ferreiraStochasticApproachOptimize2011,
  title = {A Stochastic Approach to Optimize {{Maritime}} Pine ({{Pinus}} Pinaster {{Ait}}.) Stand Management Scheduling under Fire Risk. {{An}} Application in {{Portugal}}},
  author = {Ferreira, L. and Constantino, M. and Borges, J. G.},
  date = {2011-01},
  journaltitle = {Annals of Operations Research},
  pages = {1--19},
  issn = {0254-5330},
  doi = {10.1007/s10479-011-0845-z},
  url = {https://doi.org/10.1007/s10479-011-0845-z},
  abstract = {The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-8712568,forest-fires,forest-management,forest-resources,local-scale,pinus-pinaster,portugal,stochastic-dynamic-programming}
}

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An Application in Portugal","author":[{"propositions":[],"lastnames":["Ferreira"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Constantino"],"firstnames":["M."],"suffixes":[]},{"propositions":[],"lastnames":["Borges"],"firstnames":["J.","G."],"suffixes":[]}],"date":"2011-01","journaltitle":"Annals of Operations Research","pages":"1–19","issn":"0254-5330","doi":"10.1007/s10479-011-0845-z","url":"https://doi.org/10.1007/s10479-011-0845-z","abstract":"The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk.","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-8712568,forest-fires,forest-management,forest-resources,local-scale,pinus-pinaster,portugal,stochastic-dynamic-programming","bibtex":"@article{ferreiraStochasticApproachOptimize2011,\n title = {A Stochastic Approach to Optimize {{Maritime}} Pine ({{Pinus}} Pinaster {{Ait}}.) Stand Management Scheduling under Fire Risk. {{An}} Application in {{Portugal}}},\n author = {Ferreira, L. and Constantino, M. and Borges, J. G.},\n date = {2011-01},\n journaltitle = {Annals of Operations Research},\n pages = {1--19},\n issn = {0254-5330},\n doi = {10.1007/s10479-011-0845-z},\n url = {https://doi.org/10.1007/s10479-011-0845-z},\n abstract = {The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk.},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-8712568,forest-fires,forest-management,forest-resources,local-scale,pinus-pinaster,portugal,stochastic-dynamic-programming}\n}\n\n","author_short":["Ferreira, L.","Constantino, M.","Borges, J. 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