Meeting species persistence targets under climate change: a spatially-explicit conservation planning model
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/28006 https://doi.org/10.1111/ddi.12562 |
Resumo: | Aim Climate change threatens the effectiveness of existing protected areas, pivotal, yet static, instruments to promote the persistence of biodiversity. The identification of the areas more likely to be used by multiple species to track their most suitable changing climates is therefore an important step in conservation planning. Species persistence targets and budget limitation are two critical ingredients constraining target‐based conservation area selection. However, defining adequate persistence targets under budget constraints is far from intuitive. Location Unspecific. Methods We propose a two‐staged mixed‐integer linear programming model to determine optimized persistence targets for several species, for a given time horizon and climate change scenarios, under budgetary limitation. The first stage tunes pre‐established targets for each species with a bound on the size of the area to select. The second stage identifies a set of areas of minimum cost that allows the persistence levels optimized in the first stage to be achieved. We apply a heuristic to test whether small deviations from optimal persistence settings (i.e., targets for multiple species) do influence cost‐effectiveness of final solutions. Analyses were undertaken using a synthetic data set replicating changes of environmental suitability for several simulated species using several experimental designs. Results Our results showed that minor differences to the optimal persistence scores can result in large contraction of cost‐effectiveness in final solutions. Main conclusions Persistence targets should be carefully assessed case by case, and alternative species persistence settings should be considered, as they potentially result in important reductions of cost‐effectiveness. Our model along with the respective heuristic can be used as a tool to efficiently promote species persistence under climate change. |
id |
RCAP_f5a9e8db00bd0f65062387c4666d71d0 |
---|---|
oai_identifier_str |
oai:dspace.uevora.pt:10174/28006 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning modelBiogeography ConservationDecision Suopport ToolsMixed Integer ProgrammingReserve designRisk AnalysisSpatial optimizationAim Climate change threatens the effectiveness of existing protected areas, pivotal, yet static, instruments to promote the persistence of biodiversity. The identification of the areas more likely to be used by multiple species to track their most suitable changing climates is therefore an important step in conservation planning. Species persistence targets and budget limitation are two critical ingredients constraining target‐based conservation area selection. However, defining adequate persistence targets under budget constraints is far from intuitive. Location Unspecific. Methods We propose a two‐staged mixed‐integer linear programming model to determine optimized persistence targets for several species, for a given time horizon and climate change scenarios, under budgetary limitation. The first stage tunes pre‐established targets for each species with a bound on the size of the area to select. The second stage identifies a set of areas of minimum cost that allows the persistence levels optimized in the first stage to be achieved. We apply a heuristic to test whether small deviations from optimal persistence settings (i.e., targets for multiple species) do influence cost‐effectiveness of final solutions. Analyses were undertaken using a synthetic data set replicating changes of environmental suitability for several simulated species using several experimental designs. Results Our results showed that minor differences to the optimal persistence scores can result in large contraction of cost‐effectiveness in final solutions. Main conclusions Persistence targets should be carefully assessed case by case, and alternative species persistence settings should be considered, as they potentially result in important reductions of cost‐effectiveness. Our model along with the respective heuristic can be used as a tool to efficiently promote species persistence under climate change.Diversity and Distributions2020-08-10T14:39:51Z2020-08-102017-05-16T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/28006http://hdl.handle.net/10174/28006https://doi.org/10.1111/ddi.12562enghttps://onlinelibrary.wiley.com/doi/epdf/10.1111/ddi.12562alagador@uevora.ptnd221Alagador, DiogoCerdeira, Jorge O.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:23:54Zoai:dspace.uevora.pt:10174/28006Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:17:57.149500Repositório 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 |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
title |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
spellingShingle |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model Alagador, Diogo Biogeography Conservation Decision Suopport Tools Mixed Integer Programming Reserve design Risk Analysis Spatial optimization |
title_short |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
title_full |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
title_fullStr |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
title_full_unstemmed |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
title_sort |
Meeting species persistence targets under climate change: a spatially-explicit conservation planning model |
author |
Alagador, Diogo |
author_facet |
Alagador, Diogo Cerdeira, Jorge O. |
author_role |
author |
author2 |
Cerdeira, Jorge O. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Alagador, Diogo Cerdeira, Jorge O. |
dc.subject.por.fl_str_mv |
Biogeography Conservation Decision Suopport Tools Mixed Integer Programming Reserve design Risk Analysis Spatial optimization |
topic |
Biogeography Conservation Decision Suopport Tools Mixed Integer Programming Reserve design Risk Analysis Spatial optimization |
description |
Aim Climate change threatens the effectiveness of existing protected areas, pivotal, yet static, instruments to promote the persistence of biodiversity. The identification of the areas more likely to be used by multiple species to track their most suitable changing climates is therefore an important step in conservation planning. Species persistence targets and budget limitation are two critical ingredients constraining target‐based conservation area selection. However, defining adequate persistence targets under budget constraints is far from intuitive. Location Unspecific. Methods We propose a two‐staged mixed‐integer linear programming model to determine optimized persistence targets for several species, for a given time horizon and climate change scenarios, under budgetary limitation. The first stage tunes pre‐established targets for each species with a bound on the size of the area to select. The second stage identifies a set of areas of minimum cost that allows the persistence levels optimized in the first stage to be achieved. We apply a heuristic to test whether small deviations from optimal persistence settings (i.e., targets for multiple species) do influence cost‐effectiveness of final solutions. Analyses were undertaken using a synthetic data set replicating changes of environmental suitability for several simulated species using several experimental designs. Results Our results showed that minor differences to the optimal persistence scores can result in large contraction of cost‐effectiveness in final solutions. Main conclusions Persistence targets should be carefully assessed case by case, and alternative species persistence settings should be considered, as they potentially result in important reductions of cost‐effectiveness. Our model along with the respective heuristic can be used as a tool to efficiently promote species persistence under climate change. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-05-16T00:00:00Z 2020-08-10T14:39:51Z 2020-08-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/28006 http://hdl.handle.net/10174/28006 https://doi.org/10.1111/ddi.12562 |
url |
http://hdl.handle.net/10174/28006 https://doi.org/10.1111/ddi.12562 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://onlinelibrary.wiley.com/doi/epdf/10.1111/ddi.12562 alagador@uevora.pt nd 221 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Diversity and Distributions |
publisher.none.fl_str_mv |
Diversity and Distributions |
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 |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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 |
repository.mail.fl_str_mv |
|
_version_ |
1799136661727084544 |