Publicação
Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L.
| 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. |
|---|---|
| Autores principais: | Almeida, Alice Maria |
| Outros Autores: | Ribeiro, Maria Margarida; Ferreira, Miguel R.; Roque, Natália; Quintela-Sabarís, Celestino; Fernandez, Paulo |
| Assunto: | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1866811150540210176 |
|---|---|
| author | Almeida, Alice Maria |
| author2 | Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
| author2_role | author author author author author |
| author_facet | Almeida, Alice Maria Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
| author_role | author |
| contributor_name_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Almeida, Alice Maria\"},{\"Person.name\":\"Ribeiro, Maria Margarida\",\"Person.identifier.orcid\":\"0000-0003-4684-1262\"},{\"Person.name\":\"Ferreira, Miguel R.\"},{\"Person.name\":\"Roque, Natália\"},{\"Person.name\":\"Quintela-Sabarís, Celestino\"},{\"Person.name\":\"Fernandez, Paulo\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Almeida, Alice Maria Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
| datacite.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-10-30T15:44:16Z |
| datacite.date.embargoed.fl_str_mv | 2023-10-30T15:44:16Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| datacite.titles.title.fl_str_mv | Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
| dc.contributor.none.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Almeida, Alice Maria Ribeiro, Maria Margarida Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
| dc.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-10-30T15:44:16Z |
| dc.date.embargoed.fl_str_mv | 2023-10-30T15:44:16Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/29158 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Frontiers |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| dc.title.fl_str_mv | Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L. |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| 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. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/edf590fd-e6a2-4289-a887-a5e3aef07553/download |
| funding.funder.alternateName_str_mv | FCT FCT FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | 6817 - DCRRNI ID 6817 - DCRRNI ID 6817 - DCRRNI ID |
| id | ul_f7afa7cbb3a6a4a1bb52d421cfbed7cf |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/29158 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/29158 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Almeida, Alice Maria Ribeiro, Maria Margarida Ribeiro, Maria Margarida https://www.ciencia-id.pt/AD12-4D32-7A48 AD12-4D32-7A48 http://orcid.org/0000-0003-4684-1262 0000-0003-4684-1262 Ferreira, Miguel R. Roque, Natália Quintela-Sabarís, Celestino Fernandez, Paulo |
| publishDate | 2023 |
| publisher.none.fl_str_mv | Frontiers |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engFrontierspt_PTClimate 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.application/pdfpt_PTBig data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L.Almeida, Alice MariaPersonalRibeiro, Maria MargaridaDSpacehttp://dspace.org/items/611828c6-e1cd-4fe3-9f82-cf6f076860a9DSpacehttp://dspace.org/items/611828c6-e1cd-4fe3-9f82-cf6f076860a9RibeiroMaria MargaridaCiência IDhttps://www.ciencia-id.ptAD12-4D32-7A48ORCIDhttp://orcid.org0000-0003-4684-1262Researcher IDhttps://www.researcherid.comM-4235-2013Scopus Author IDhttps://www.scopus.com7201715611Ferreira, Miguel R.Roque, NatáliaQuintela-Sabarís, CelestinoFernandez, PauloHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptDOIIsPartOf10.3389/fevo.2023.11362242023-10-30T15:44:16Z20232023-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/29158http://purl.org/coar/access_right/c_abf2open accessRock rosespecies distribution modelingbiomod2ensemble modelingclimate change2068181 bytesFundação para a Ciência e a TecnologiaForest Research Centre6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaResearch Center in Natural Resources, Environment and Society6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaMediterranean Institute for Agriculture, Environment and Development6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal article2023http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/edf590fd-e6a2-4289-a887-a5e3aef07553/downloadFrontiers in Ecology and Evolution11Article number 1136224 |
| 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 |
| status | SINGLETON |
| subject.fl_str_mv | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| title | 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_short | 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. |
| topic | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| topic_facet | Rock rose species distribution modeling biomod2 ensemble modeling climate change |
| url | http://hdl.handle.net/10400.5/29158 |
| visible | 1 |