Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal

Detalhes bibliográficos
Autor(a) principal: Alegria, Cristina
Data de Publicação: 2020
Outros Autores: Roque, Natália, Albuquerque, Teresa, Gerassis, Saki, Fernandez, Paulo, Ribeiro, Maria Margarida
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/20345
Resumo: Species ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The o cial land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ a orestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to di erentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future a orestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios
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spelling Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugalecological envelopesclimate change scenariosspecies distributionspecies productivitymachine learningSpecies ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The o cial land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ a orestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to di erentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future a orestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenariosMDPIRepositório da Universidade de LisboaAlegria, CristinaRoque, NatáliaAlbuquerque, TeresaGerassis, SakiFernandez, PauloRibeiro, Maria Margarida2020-09-17T14:36:43Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/20345engForests 2020, 11, 88010.3390/f11080880info: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:RCAAP2023-03-06T14:49:47Zoai:www.repository.utl.pt:10400.5/20345Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:05:06.846853Repositório 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 Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
title Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
spellingShingle Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
Alegria, Cristina
ecological envelopes
climate change scenarios
species distribution
species productivity
machine learning
title_short Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
title_full Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
title_fullStr Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
title_full_unstemmed Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
title_sort Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
author Alegria, Cristina
author_facet Alegria, Cristina
Roque, Natália
Albuquerque, Teresa
Gerassis, Saki
Fernandez, Paulo
Ribeiro, Maria Margarida
author_role author
author2 Roque, Natália
Albuquerque, Teresa
Gerassis, Saki
Fernandez, Paulo
Ribeiro, Maria Margarida
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Alegria, Cristina
Roque, Natália
Albuquerque, Teresa
Gerassis, Saki
Fernandez, Paulo
Ribeiro, Maria Margarida
dc.subject.por.fl_str_mv ecological envelopes
climate change scenarios
species distribution
species productivity
machine learning
topic ecological envelopes
climate change scenarios
species distribution
species productivity
machine learning
description Species ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The o cial land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ a orestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to di erentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future a orestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios
publishDate 2020
dc.date.none.fl_str_mv 2020-09-17T14:36:43Z
2020
2020-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/20345
url http://hdl.handle.net/10400.5/20345
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Forests 2020, 11, 880
10.3390/f11080880
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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
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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
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