A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.7717/peerj.13534 http://hdl.handle.net/11449/241275 |
Resumo: | Monitoring biodiversity change is key to effective conservation policy. While it is difficult to establish in situ biodiversity monitoring programs at broad geographical scales, remote sensing advances allow for near-real time Earth observations that may help with this goal. We combine periodical and freely available remote sensing information describing temperature and precipitation with curated biological information from several groups of animals and plants in the Brazilian Atlantic rainforest to design an indirect remote sensing framework that monitors potential loss and gain of biodiversity in near-real time. Using data from biological collections and information from repeated field inventories, we demonstrate that this framework has the potential to accurately predict trends of biodiversity change for both taxonomic and phylogenetic diversity. The framework identifies areas of potential diversity loss more accurately than areas of species gain, and performs best when applied to broadly distributed groups of animals and plants. |
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A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforestBiodiversityMonitoringPhylogenetic diversityPredictionRichnessMonitoring biodiversity change is key to effective conservation policy. While it is difficult to establish in situ biodiversity monitoring programs at broad geographical scales, remote sensing advances allow for near-real time Earth observations that may help with this goal. We combine periodical and freely available remote sensing information describing temperature and precipitation with curated biological information from several groups of animals and plants in the Brazilian Atlantic rainforest to design an indirect remote sensing framework that monitors potential loss and gain of biodiversity in near-real time. Using data from biological collections and information from repeated field inventories, we demonstrate that this framework has the potential to accurately predict trends of biodiversity change for both taxonomic and phylogenetic diversity. The framework identifies areas of potential diversity loss more accurately than areas of species gain, and performs best when applied to broadly distributed groups of animals and plants.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)National Science FoundationDepartment of Biology City College of New YorkPh.D Program in Biology City University of New York Graduate School and University CenterDepartment of Environmental Systems Science Institute of Integrative Biology Swiss Federal Institute of Technology ZurichInstituto de Geociências e Ciências Exatas Departamento de Geografia Ecosystem Dynamics Observatory Universidade Estadual Paulista, São PauloBiological and Environmental Sciences Faculty of Natural Sciences University of StirlingInstituto de Geociências e Ciências Exatas Departamento de Geografia Ecosystem Dynamics Observatory Universidade Estadual Paulista, São PauloFAPESP: 2013/50297-0National Science Foundation: DEB 1343578National Science Foundation: DEB-1343612City College of New YorkGraduate School and University CenterZurichUniversidade Estadual Paulista (UNESP)University of StirlingPaz, AndreaSilva, Thiago S. [UNESP]Carnaval, Ana C.2023-03-01T20:54:45Z2023-03-01T20:54:45Z2022-06-29info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.7717/peerj.13534PeerJ, v. 10.2167-8359http://hdl.handle.net/11449/24127510.7717/peerj.135342-s2.0-85133481662Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPeerJinfo:eu-repo/semantics/openAccess2023-03-01T20:54:45Zoai:repositorio.unesp.br:11449/241275Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:36:32.025624Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
title |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
spellingShingle |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest Paz, Andrea Biodiversity Monitoring Phylogenetic diversity Prediction Richness |
title_short |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
title_full |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
title_fullStr |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
title_full_unstemmed |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
title_sort |
A framework for near-real time monitoring of diversity patterns based on indirect remote sensing, with an application in the Brazilian Atlantic rainforest |
author |
Paz, Andrea |
author_facet |
Paz, Andrea Silva, Thiago S. [UNESP] Carnaval, Ana C. |
author_role |
author |
author2 |
Silva, Thiago S. [UNESP] Carnaval, Ana C. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
City College of New York Graduate School and University Center Zurich Universidade Estadual Paulista (UNESP) University of Stirling |
dc.contributor.author.fl_str_mv |
Paz, Andrea Silva, Thiago S. [UNESP] Carnaval, Ana C. |
dc.subject.por.fl_str_mv |
Biodiversity Monitoring Phylogenetic diversity Prediction Richness |
topic |
Biodiversity Monitoring Phylogenetic diversity Prediction Richness |
description |
Monitoring biodiversity change is key to effective conservation policy. While it is difficult to establish in situ biodiversity monitoring programs at broad geographical scales, remote sensing advances allow for near-real time Earth observations that may help with this goal. We combine periodical and freely available remote sensing information describing temperature and precipitation with curated biological information from several groups of animals and plants in the Brazilian Atlantic rainforest to design an indirect remote sensing framework that monitors potential loss and gain of biodiversity in near-real time. Using data from biological collections and information from repeated field inventories, we demonstrate that this framework has the potential to accurately predict trends of biodiversity change for both taxonomic and phylogenetic diversity. The framework identifies areas of potential diversity loss more accurately than areas of species gain, and performs best when applied to broadly distributed groups of animals and plants. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-06-29 2023-03-01T20:54:45Z 2023-03-01T20:54:45Z |
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://dx.doi.org/10.7717/peerj.13534 PeerJ, v. 10. 2167-8359 http://hdl.handle.net/11449/241275 10.7717/peerj.13534 2-s2.0-85133481662 |
url |
http://dx.doi.org/10.7717/peerj.13534 http://hdl.handle.net/11449/241275 |
identifier_str_mv |
PeerJ, v. 10. 2167-8359 10.7717/peerj.13534 2-s2.0-85133481662 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PeerJ |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129536014942208 |