Species ecological envelopes under climate change scenarios: a case study for the main two wood-production forest species in Portugal
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2020 |
| Outros Autores: | , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/10400.11/7241 |
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 scenarios.MDPIRepositório Científico do Instituto Politécnico de Castelo BrancoAlegria, C.M.M.Roque, NatáliaAlbuquerque, M.T.D.Gerassis Davite, SakiFernandez, PauloRibeiro, M.M.A.2020-09-08T15:02:33Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/7241eng1999-490710.3390/f11080880info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-26T14:06:44Zoai:repositorio.ipcb.pt:10400.11/7241Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T21:22:25.899063Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| 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, C.M.M. 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, C.M.M. |
| author_facet |
Alegria, C.M.M. Roque, Natália Albuquerque, M.T.D. Gerassis Davite, Saki Fernandez, Paulo Ribeiro, M.M.A. |
| author_role |
author |
| author2 |
Roque, Natália Albuquerque, M.T.D. Gerassis Davite, Saki Fernandez, Paulo Ribeiro, M.M.A. |
| author2_role |
author author author author author |
| dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico de Castelo Branco |
| dc.contributor.author.fl_str_mv |
Alegria, C.M.M. Roque, Natália Albuquerque, M.T.D. Gerassis Davite, Saki Fernandez, Paulo Ribeiro, M.M.A. |
| 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 |
2020-09-08T15:02:33Z 2020 2020-01-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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http://hdl.handle.net/10400.11/7241 |
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eng |
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eng |
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1999-4907 10.3390/f11080880 |
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openAccess |
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MDPI |
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MDPI |
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