Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2020 |
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/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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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 |
format |
article |
status_str |
publishedVersion |
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 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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 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 |
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1799131143258243072 |