Improving the Assessment and Reporting on Rare and Endangered Species through Species Distribution Models. Sousa-Silva, R., Alves, P., Honrado, J., & Lomba, A. Global Ecology and Conservation, 2:226–237, December, 2014. doi abstract bibtex Species distribution models (SDMs) are increasingly used to understand rare and endangered species distributions, as well as the environmental pressures affecting them. Detailed knowledge of their distribution is critical for reporting its conservation status, and SDMs are potential tools to provide the relevant information to conservation practitioners. In this study, we modeled the distribution of Veronica micrantha, a vulnerable plant whose conservation status has to be periodically assessed under Article 17 of the Habitats Directive. [] The objective was to highlight the potential of SDMs for the assessment of threatened species within the periodical report on their conservation status. We used a spatially explicit modeling approach, which predicts species distributions by spatially combining two SDMs: one fitted with climate data alone and the other fitted solely with landscape variables. A comparison between the modeled distribution and the range obtained by classical methods (minimum convex polygon and Range Tool) is also presented. Our results show that while data-based approaches only consider the species known distribution, model-based methods allow a more complete evaluation of species distributions and their dynamics, as well as of the underlying pressures. This will ultimately improve the accuracy and usefulness of assessments in the context of EU reporting obligations. [Excerpt:Conclusion] Overall, our results highlight the usefulness of SDMs to report on rare species, and illustrate how the tool applied to such reporting assessments may affect decisions about resource allocation for monitoring and conservation. We consider the statistical modeling of the potential distribution of target species a more adequate estimate of the available suitable habitat for the focal species and thus a useful tool to complement existing data. Also, as the effects of climate and land-use changes on species distributions become more noticeable, those effects should be considered in the next assessment and reporting periods. This further highlights the importance of this novel framework for future assessments of threatened species and habitat types in a global change context. As a result, the proposed approach might be of interest for scientists and managers dealing with rare and endangered species. [] [...]
@article{sousa-silvaImprovingAssessmentReporting2014,
title = {Improving the Assessment and Reporting on Rare and Endangered Species through Species Distribution Models},
author = {{Sousa-Silva}, Rita and Alves, Paulo and Honrado, Jo{\~a}o and Lomba, Angela},
year = {2014},
month = dec,
volume = {2},
pages = {226--237},
issn = {2351-9894},
doi = {10.1016/j.gecco.2014.09.011},
abstract = {Species distribution models (SDMs) are increasingly used to understand rare and endangered species distributions, as well as the environmental pressures affecting them. Detailed knowledge of their distribution is critical for reporting its conservation status, and SDMs are potential tools to provide the relevant information to conservation practitioners. In this study, we modeled the distribution of Veronica micrantha, a vulnerable plant whose conservation status has to be periodically assessed under Article 17 of the Habitats Directive.
[] The objective was to highlight the potential of SDMs for the assessment of threatened species within the periodical report on their conservation status. We used a spatially explicit modeling approach, which predicts species distributions by spatially combining two SDMs: one fitted with climate data alone and the other fitted solely with landscape variables. A comparison between the modeled distribution and the range obtained by classical methods (minimum convex polygon and Range Tool) is also presented. Our results show that while data-based approaches only consider the species known distribution, model-based methods allow a more complete evaluation of species distributions and their dynamics, as well as of the underlying pressures. This will ultimately improve the accuracy and usefulness of assessments in the context of EU reporting obligations.
[Excerpt:Conclusion]
Overall, our results highlight the usefulness of SDMs to report on rare species, and illustrate how the tool applied to such reporting assessments may affect decisions about resource allocation for monitoring and conservation. We consider the statistical modeling of the potential distribution of target species a more adequate estimate of the available suitable habitat for the focal species and thus a useful tool to complement existing data. Also, as the effects of climate and land-use changes on species distributions become more noticeable, those effects should be considered in the next assessment and reporting periods. This further highlights the importance of this novel framework for future assessments of threatened species and habitat types in a global change context. As a result, the proposed approach might be of interest for scientists and managers dealing with rare and endangered species.
[] [...]},
journal = {Global Ecology and Conservation},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14076785,~to-add-doi-URL,assessment,comparison,csmfa,endangered-species,integration-techniques,modelling,spain,spatial-pattern,species-distribution,veronica-micrantha},
lccn = {INRMM-MiD:c-14076785}
}
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Our results show that while data-based approaches only consider the species known distribution, model-based methods allow a more complete evaluation of species distributions and their dynamics, as well as of the underlying pressures. This will ultimately improve the accuracy and usefulness of assessments in the context of EU reporting obligations. [Excerpt:Conclusion] Overall, our results highlight the usefulness of SDMs to report on rare species, and illustrate how the tool applied to such reporting assessments may affect decisions about resource allocation for monitoring and conservation. We consider the statistical modeling of the potential distribution of target species a more adequate estimate of the available suitable habitat for the focal species and thus a useful tool to complement existing data. Also, as the effects of climate and land-use changes on species distributions become more noticeable, those effects should be considered in the next assessment and reporting periods. 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