A new stochastic dynamic tool to improve the accuracy of mortality

Detalhes bibliográficos
Autor(a) principal: Bastos, Rita
Data de Publicação: 2013
Outros Autores: Santos, Mário, Cabral, João Alexandre
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10348/4296
Resumo: Although generally considered environmentally friendly, wind power has been associated with extensive mortality of birds and bats. In this perspective, there is a need for reliable estimates of fatalities at wind farms, where the heterogeneity of the basic information, used among environmental assessment studies, is unlikely to support an accurate universal estimation method. We tested the applicability of the Stochastic Dynamic Methodology (StDM) to estimate bat fatalities, based on multifactorial cause–effect relationships (by integrating multi-model inference statistical analysis and dynamic modelling) between mortality estimates, detected fatalities and the selected key-components of the reality, such as the real number of bat mortalities simulated, the rate of carcasses removal, the searcher efficiency, the monitoring periodicity and the number of turbines for different realistic scenarios associated with particular wind farm conditions. Although some existing mortality estimators are considered accurate, the choice of a given universal formula for all mortality assessments, based on deterministic parameters and assumptions, may originate unsuspected errors. Therefore, we propose a flexible dynamic modelling framework, the StDM estimator, where the obtained algorithms are adaptable to the universe of application intended. The StDM estimator takes into account random, non-constant and scenario dependent parameters, providing bias-corrected estimates. The StDM estimator was applied for the European wind farm context and validated in the most cases tested, through the confrontation with independent data. Overall, this approach is considered a valuable tool to improve the quality of mortality estimates at onshore wind facilities, within the local, environmental and methodological gradients (including the cases where no mortality is detected), namely in the scope of environmental impact assessments and general ecological monitoring programmes.
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spelling A new stochastic dynamic tool to improve the accuracy of mortalityMortality estimatorsBat fatalitiesWind farmsStochastic dynamic modellingEnvironmental impact assessmentGeneral ecological monitoringAlthough generally considered environmentally friendly, wind power has been associated with extensive mortality of birds and bats. In this perspective, there is a need for reliable estimates of fatalities at wind farms, where the heterogeneity of the basic information, used among environmental assessment studies, is unlikely to support an accurate universal estimation method. We tested the applicability of the Stochastic Dynamic Methodology (StDM) to estimate bat fatalities, based on multifactorial cause–effect relationships (by integrating multi-model inference statistical analysis and dynamic modelling) between mortality estimates, detected fatalities and the selected key-components of the reality, such as the real number of bat mortalities simulated, the rate of carcasses removal, the searcher efficiency, the monitoring periodicity and the number of turbines for different realistic scenarios associated with particular wind farm conditions. Although some existing mortality estimators are considered accurate, the choice of a given universal formula for all mortality assessments, based on deterministic parameters and assumptions, may originate unsuspected errors. Therefore, we propose a flexible dynamic modelling framework, the StDM estimator, where the obtained algorithms are adaptable to the universe of application intended. The StDM estimator takes into account random, non-constant and scenario dependent parameters, providing bias-corrected estimates. The StDM estimator was applied for the European wind farm context and validated in the most cases tested, through the confrontation with independent data. Overall, this approach is considered a valuable tool to improve the quality of mortality estimates at onshore wind facilities, within the local, environmental and methodological gradients (including the cases where no mortality is detected), namely in the scope of environmental impact assessments and general ecological monitoring programmes.2015-03-17T14:00:16Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10348/4296engdoi: 10.1016/j.ecolind.2013.06.003metadata only accessinfo:eu-repo/semantics/openAccessBastos, RitaSantos, MárioCabral, João Alexandrereponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-02T12:56:14Zoai:repositorio.utad.pt:10348/4296Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:06:19.506821Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A new stochastic dynamic tool to improve the accuracy of mortality
title A new stochastic dynamic tool to improve the accuracy of mortality
spellingShingle A new stochastic dynamic tool to improve the accuracy of mortality
Bastos, Rita
Mortality estimators
Bat fatalities
Wind farms
Stochastic dynamic modelling
Environmental impact assessment
General ecological monitoring
title_short A new stochastic dynamic tool to improve the accuracy of mortality
title_full A new stochastic dynamic tool to improve the accuracy of mortality
title_fullStr A new stochastic dynamic tool to improve the accuracy of mortality
title_full_unstemmed A new stochastic dynamic tool to improve the accuracy of mortality
title_sort A new stochastic dynamic tool to improve the accuracy of mortality
author Bastos, Rita
author_facet Bastos, Rita
Santos, Mário
Cabral, João Alexandre
author_role author
author2 Santos, Mário
Cabral, João Alexandre
author2_role author
author
dc.contributor.author.fl_str_mv Bastos, Rita
Santos, Mário
Cabral, João Alexandre
dc.subject.por.fl_str_mv Mortality estimators
Bat fatalities
Wind farms
Stochastic dynamic modelling
Environmental impact assessment
General ecological monitoring
topic Mortality estimators
Bat fatalities
Wind farms
Stochastic dynamic modelling
Environmental impact assessment
General ecological monitoring
description Although generally considered environmentally friendly, wind power has been associated with extensive mortality of birds and bats. In this perspective, there is a need for reliable estimates of fatalities at wind farms, where the heterogeneity of the basic information, used among environmental assessment studies, is unlikely to support an accurate universal estimation method. We tested the applicability of the Stochastic Dynamic Methodology (StDM) to estimate bat fatalities, based on multifactorial cause–effect relationships (by integrating multi-model inference statistical analysis and dynamic modelling) between mortality estimates, detected fatalities and the selected key-components of the reality, such as the real number of bat mortalities simulated, the rate of carcasses removal, the searcher efficiency, the monitoring periodicity and the number of turbines for different realistic scenarios associated with particular wind farm conditions. Although some existing mortality estimators are considered accurate, the choice of a given universal formula for all mortality assessments, based on deterministic parameters and assumptions, may originate unsuspected errors. Therefore, we propose a flexible dynamic modelling framework, the StDM estimator, where the obtained algorithms are adaptable to the universe of application intended. The StDM estimator takes into account random, non-constant and scenario dependent parameters, providing bias-corrected estimates. The StDM estimator was applied for the European wind farm context and validated in the most cases tested, through the confrontation with independent data. Overall, this approach is considered a valuable tool to improve the quality of mortality estimates at onshore wind facilities, within the local, environmental and methodological gradients (including the cases where no mortality is detected), namely in the scope of environmental impact assessments and general ecological monitoring programmes.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01T00:00:00Z
2013
2015-03-17T14:00:16Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10348/4296
url http://hdl.handle.net/10348/4296
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv doi: 10.1016/j.ecolind.2013.06.003
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dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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