Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L.
Autor(a) principal: | |
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Data de Publicação: | 2023 |
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/10400.5/29158 |
Resumo: | Climate change’s huge impact on Mediterranean species’ habitat suitability and spatial and temporal distribution in the coming decades is expected. The present work aimed to reconstruct rockrose (Cistus ladanifer L.) historical and future spatial distribution, a typically Mediterranean species with abundant occurrence in North Africa, Iberian Peninsula, and Southern France. The R ensemble modeling approach was made using the biomod2 package to assess changes in the spatial distribution of the species in the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and the Middle Holocene (MH), in the present, and in the future (for the years 2050 and 2070), considering two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The current species potential distribution was modeled using 2,833 occurrences, six bioclimatic variables, and four algorithms, Generalized Linear Model (GLM), MaxEnt, Multivariate Adaptive Regression Splines (MARS), and Artificial Neural Networks (ANN). Two global climate models (GCMs), CCSM4 and MRI-CGCM3, were used to forecast past and future suitability. The potential area of occurrence of the species is equal to 15.8 and 14.1% of the study area for current and LIG conditions, while it decreased to 3.8% in the LGM. The species’ presence diaminished more than half in the RCP 4.5 (to 6.8% in 2050 and 7% in 2070), and a too low figure (2.2%) in the worst-case scenario (RCP 8.5) for 2070. The results suggested that the current climatic conditions are the most suitable for the species’ occurrence and that future changes in environmental conditions may lead to the loss of suitable habitats, especially in the worst-case scenario. The information unfolded by this study will help to understand future predictable desertification in the Mediterranean region and to help policymakers to implement possible measures for biodiversity maintenance and desertification avoidance. |
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Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L.Rock rosespecies distribution modelingbiomod2ensemble modelingclimate changeClimate change’s huge impact on Mediterranean species’ habitat suitability and spatial and temporal distribution in the coming decades is expected. The present work aimed to reconstruct rockrose (Cistus ladanifer L.) historical and future spatial distribution, a typically Mediterranean species with abundant occurrence in North Africa, Iberian Peninsula, and Southern France. The R ensemble modeling approach was made using the biomod2 package to assess changes in the spatial distribution of the species in the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and the Middle Holocene (MH), in the present, and in the future (for the years 2050 and 2070), considering two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The current species potential distribution was modeled using 2,833 occurrences, six bioclimatic variables, and four algorithms, Generalized Linear Model (GLM), MaxEnt, Multivariate Adaptive Regression Splines (MARS), and Artificial Neural Networks (ANN). Two global climate models (GCMs), CCSM4 and MRI-CGCM3, were used to forecast past and future suitability. The potential area of occurrence of the species is equal to 15.8 and 14.1% of the study area for current and LIG conditions, while it decreased to 3.8% in the LGM. The species’ presence diaminished more than half in the RCP 4.5 (to 6.8% in 2050 and 7% in 2070), and a too low figure (2.2%) in the worst-case scenario (RCP 8.5) for 2070. The results suggested that the current climatic conditions are the most suitable for the species’ occurrence and that future changes in environmental conditions may lead to the loss of suitable habitats, especially in the worst-case scenario. The information unfolded by this study will help to understand future predictable desertification in the Mediterranean region and to help policymakers to implement possible measures for biodiversity maintenance and desertification avoidance.FrontiersRepositório da Universidade de LisboaAlmeida, Alice MariaRibeiro, Maria MargaridaFerreira, Miguel R.Roque, NatáliaQuintela-Sabarís, CelestinoFernandez, Paulo2023-10-30T15:44:16Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/29158engAlmeida AM, Ribeiro MM, Ferreira MR, Roque N, Quintela-Sabarís C and Fernandez P (2023) Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. Front. Ecol. Evol. 11:113622410.3389/fevo.2023.1136224info: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:RCAAP2023-11-05T01:31:48Zoai:www.repository.utl.pt:10400.5/29158Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:26:46.724542Repositório 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 |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
title |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
spellingShingle |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. Almeida, Alice Maria Rock rose species distribution modeling biomod2 ensemble modeling climate change |
title_short |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
title_full |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
title_fullStr |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
title_full_unstemmed |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
title_sort |
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
author |
Almeida, Alice Maria |
author_facet |
Almeida, Alice Maria Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
author_role |
author |
author2 |
Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Almeida, Alice Maria Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
dc.subject.por.fl_str_mv |
Rock rose species distribution modeling biomod2 ensemble modeling climate change |
topic |
Rock rose species distribution modeling biomod2 ensemble modeling climate change |
description |
Climate change’s huge impact on Mediterranean species’ habitat suitability and spatial and temporal distribution in the coming decades is expected. The present work aimed to reconstruct rockrose (Cistus ladanifer L.) historical and future spatial distribution, a typically Mediterranean species with abundant occurrence in North Africa, Iberian Peninsula, and Southern France. The R ensemble modeling approach was made using the biomod2 package to assess changes in the spatial distribution of the species in the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and the Middle Holocene (MH), in the present, and in the future (for the years 2050 and 2070), considering two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The current species potential distribution was modeled using 2,833 occurrences, six bioclimatic variables, and four algorithms, Generalized Linear Model (GLM), MaxEnt, Multivariate Adaptive Regression Splines (MARS), and Artificial Neural Networks (ANN). Two global climate models (GCMs), CCSM4 and MRI-CGCM3, were used to forecast past and future suitability. The potential area of occurrence of the species is equal to 15.8 and 14.1% of the study area for current and LIG conditions, while it decreased to 3.8% in the LGM. The species’ presence diaminished more than half in the RCP 4.5 (to 6.8% in 2050 and 7% in 2070), and a too low figure (2.2%) in the worst-case scenario (RCP 8.5) for 2070. The results suggested that the current climatic conditions are the most suitable for the species’ occurrence and that future changes in environmental conditions may lead to the loss of suitable habitats, especially in the worst-case scenario. The information unfolded by this study will help to understand future predictable desertification in the Mediterranean region and to help policymakers to implement possible measures for biodiversity maintenance and desertification avoidance. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-10-30T15:44:16Z 2023 2023-01-01T00:00:00Z |
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/10400.5/29158 |
url |
http://hdl.handle.net/10400.5/29158 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Almeida AM, Ribeiro MM, Ferreira MR, Roque N, Quintela-Sabarís C and Fernandez P (2023) Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. Front. Ecol. Evol. 11:1136224 10.3389/fevo.2023.1136224 |
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 |
Frontiers |
publisher.none.fl_str_mv |
Frontiers |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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