Modelling highly biodiverse areas in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | https://doi.org/10.1038/s41598-019-42881-9 http://hdl.handle.net/1843/52292 https://orcid.org/0000-0003-4877-5414 https://orcid.org/0000-0003-4640-0942 https://orcid.org/0000-0002-9504-5441 https://orcid.org/0000-0002-7887-2461 https://orcid.org/0000-0002-3628-6405 https://orcid.org/0000-0001-5122-0247 https://orcid.org/0000-0002-6491-806X https://orcid.org/0000-0002-7703-946X https://orcid.org/0000-0002-0010-346X https://orcid.org/0000-0001-9957-5506 https://orcid.org/0000-0002-1511-5324 https://orcid.org/0000-0002-4539-4336 https://orcid.org/0000-0003-4561-5634 |
Resumo: | Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties. |
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2023-04-19T20:55:35Z2023-04-19T20:55:35Z2019-04-23911https://doi.org/10.1038/s41598-019-42881-920452322http://hdl.handle.net/1843/52292https://orcid.org/0000-0003-4877-5414https://orcid.org/0000-0003-4640-0942https://orcid.org/0000-0002-9504-5441https://orcid.org/0000-0002-7887-2461https://orcid.org/0000-0002-3628-6405https://orcid.org/0000-0001-5122-0247https://orcid.org/0000-0002-6491-806Xhttps://orcid.org/0000-0002-7703-946Xhttps://orcid.org/0000-0002-0010-346Xhttps://orcid.org/0000-0001-9957-5506https://orcid.org/0000-0002-1511-5324https://orcid.org/0000-0002-4539-4336https://orcid.org/0000-0003-4561-5634Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.engUniversidade Federal de Minas GeraisUFMGBrasilICB - DEPARTAMENTO DE BOTÂNICAICB - DEPARTAMENTO DE ZOOLOGIAIGC - DEPARTAMENTO DE CARTOGRAFIAScientific ReportsEcologiaBiodiversidade - ConservaçãoSpatially explicitSDMConservation prioritiesModelling highly biodiverse areas in Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://www.nature.com/articles/s41598-019-42881-9#rightslinkUbirajara OliveiraJoão Aguiar Nogueira BatistaJoão Paulo Peixoto Pena BarbosaJoão Renato StehmannJohn S. AscherMarcelo F. VasconcelosPaulo de MarcoPeter Löwenberg-netoViviane Gianluppi FerroBritaldo Silveira Soares FilhoAdalberto J. SantosAdriano Pereira PagliaAntonio D. BrescovitClaudio J. B. de CarvalhoDaniel Paiva SilvaDaniella T. RezendeFelipe Sá Fortes Leiteapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/52292/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALmodellinghighlybiodiverse.pdfmodellinghighlybiodiverse.pdfapplication/pdf4609214https://repositorio.ufmg.br/bitstream/1843/52292/2/modellinghighlybiodiverse.pdf317d945ac88fd33954b50849fc28ca53MD521843/522922023-04-19 17:55:35.845oai:repositorio.ufmg.br:1843/52292TElDRU7vv71BIERFIERJU1RSSUJVSe+/ve+/vU8gTu+/vU8tRVhDTFVTSVZBIERPIFJFUE9TSVTvv71SSU8gSU5TVElUVUNJT05BTCBEQSBVRk1HCiAKCkNvbSBhIGFwcmVzZW50Ye+/ve+/vW8gZGVzdGEgbGljZW7vv71hLCB2b2Pvv70gKG8gYXV0b3IgKGVzKSBvdSBvIHRpdHVsYXIgZG9zIGRpcmVpdG9zIGRlIGF1dG9yKSBjb25jZWRlIGFvIFJlcG9zaXTvv71yaW8gSW5zdGl0dWNpb25hbCBkYSBVRk1HIChSSS1VRk1HKSBvIGRpcmVpdG8gbu+/vW8gZXhjbHVzaXZvIGUgaXJyZXZvZ++/vXZlbCBkZSByZXByb2R1emlyIGUvb3UgZGlzdHJpYnVpciBhIHN1YSBwdWJsaWNh77+977+9byAoaW5jbHVpbmRvIG8gcmVzdW1vKSBwb3IgdG9kbyBvIG11bmRvIG5vIGZvcm1hdG8gaW1wcmVzc28gZSBlbGV0cu+/vW5pY28gZSBlbSBxdWFscXVlciBtZWlvLCBpbmNsdWluZG8gb3MgZm9ybWF0b3Mg77+9dWRpbyBvdSB277+9ZGVvLgoKVm9j77+9IGRlY2xhcmEgcXVlIGNvbmhlY2UgYSBwb2zvv710aWNhIGRlIGNvcHlyaWdodCBkYSBlZGl0b3JhIGRvIHNldSBkb2N1bWVudG8gZSBxdWUgY29uaGVjZSBlIGFjZWl0YSBhcyBEaXJldHJpemVzIGRvIFJJLVVGTUcuCgpWb2Pvv70gY29uY29yZGEgcXVlIG8gUmVwb3NpdO+/vXJpbyBJbnN0aXR1Y2lvbmFsIGRhIFVGTUcgcG9kZSwgc2VtIGFsdGVyYXIgbyBjb250Ze+/vWRvLCB0cmFuc3BvciBhIHN1YSBwdWJsaWNh77+977+9byBwYXJhIHF1YWxxdWVyIG1laW8gb3UgZm9ybWF0byBwYXJhIGZpbnMgZGUgcHJlc2VydmHvv73vv71vLgoKVm9j77+9IHRhbWLvv71tIGNvbmNvcmRhIHF1ZSBvIFJlcG9zaXTvv71yaW8gSW5zdGl0dWNpb25hbCBkYSBVRk1HIHBvZGUgbWFudGVyIG1haXMgZGUgdW1hIGPvv71waWEgZGUgc3VhIHB1YmxpY2Hvv73vv71vIHBhcmEgZmlucyBkZSBzZWd1cmFu77+9YSwgYmFjay11cCBlIHByZXNlcnZh77+977+9by4KClZvY++/vSBkZWNsYXJhIHF1ZSBhIHN1YSBwdWJsaWNh77+977+9byDvv70gb3JpZ2luYWwgZSBxdWUgdm9j77+9IHRlbSBvIHBvZGVyIGRlIGNvbmNlZGVyIG9zIGRpcmVpdG9zIGNvbnRpZG9zIG5lc3RhIGxpY2Vu77+9YS4gVm9j77+9IHRhbWLvv71tIGRlY2xhcmEgcXVlIG8gZGVw77+9c2l0byBkZSBzdWEgcHVibGljYe+/ve+/vW8gbu+/vW8sIHF1ZSBzZWphIGRlIHNldSBjb25oZWNpbWVudG8sIGluZnJpbmdlIGRpcmVpdG9zIGF1dG9yYWlzIGRlIG5pbmd177+9bS4KCkNhc28gYSBzdWEgcHVibGljYe+/ve+/vW8gY29udGVuaGEgbWF0ZXJpYWwgcXVlIHZvY++/vSBu77+9byBwb3NzdWkgYSB0aXR1bGFyaWRhZGUgZG9zIGRpcmVpdG9zIGF1dG9yYWlzLCB2b2Pvv70gZGVjbGFyYSBxdWUgb2J0ZXZlIGEgcGVybWlzc++/vW8gaXJyZXN0cml0YSBkbyBkZXRlbnRvciBkb3MgZGlyZWl0b3MgYXV0b3JhaXMgcGFyYSBjb25jZWRlciBhbyBSZXBvc2l077+9cmlvIEluc3RpdHVjaW9uYWwgZGEgVUZNRyBvcyBkaXJlaXRvcyBhcHJlc2VudGFkb3MgbmVzdGEgbGljZW7vv71hLCBlIHF1ZSBlc3NlIG1hdGVyaWFsIGRlIHByb3ByaWVkYWRlIGRlIHRlcmNlaXJvcyBlc3Tvv70gY2xhcmFtZW50ZSBpZGVudGlmaWNhZG8gZSByZWNvbmhlY2lkbyBubyB0ZXh0byBvdSBubyBjb250Ze+/vWRvIGRhIHB1YmxpY2Hvv73vv71vIG9yYSBkZXBvc2l0YWRhLgoKQ0FTTyBBIFBVQkxJQ0Hvv73vv71PIE9SQSBERVBPU0lUQURBIFRFTkhBIFNJRE8gUkVTVUxUQURPIERFIFVNIFBBVFJPQ++/vU5JTyBPVSBBUE9JTyBERSBVTUEgQUfvv71OQ0lBIERFIEZPTUVOVE8gT1UgT1VUUk8gT1JHQU5JU01PLCBWT0Pvv70gREVDTEFSQSBRVUUgUkVTUEVJVE9VIFRPRE9TIEUgUVVBSVNRVUVSIERJUkVJVE9TIERFIFJFVklT77+9TyBDT01PIFRBTULvv71NIEFTIERFTUFJUyBPQlJJR0Hvv73vv71FUyBFWElHSURBUyBQT1IgQ09OVFJBVE8gT1UgQUNPUkRPLgoKTyBSZXBvc2l077+9cmlvIEluc3RpdHVjaW9uYWwgZGEgVUZNRyBzZSBjb21wcm9tZXRlIGEgaWRlbnRpZmljYXIgY2xhcmFtZW50ZSBvIHNldSBub21lKHMpIG91IG8ocykgbm9tZXMocykgZG8ocykgZGV0ZW50b3IoZXMpIGRvcyBkaXJlaXRvcyBhdXRvcmFpcyBkYSBwdWJsaWNh77+977+9bywgZSBu77+9byBmYXLvv70gcXVhbHF1ZXIgYWx0ZXJh77+977+9bywgYWzvv71tIGRhcXVlbGFzIGNvbmNlZGlkYXMgcG9yIGVzdGEgbGljZW7vv71hLgo=Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-04-19T20:55:35Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
Modelling highly biodiverse areas in Brazil |
title |
Modelling highly biodiverse areas in Brazil |
spellingShingle |
Modelling highly biodiverse areas in Brazil Ubirajara Oliveira Spatially explicit SDM Conservation priorities Ecologia Biodiversidade - Conservação |
title_short |
Modelling highly biodiverse areas in Brazil |
title_full |
Modelling highly biodiverse areas in Brazil |
title_fullStr |
Modelling highly biodiverse areas in Brazil |
title_full_unstemmed |
Modelling highly biodiverse areas in Brazil |
title_sort |
Modelling highly biodiverse areas in Brazil |
author |
Ubirajara Oliveira |
author_facet |
Ubirajara Oliveira João Aguiar Nogueira Batista João Paulo Peixoto Pena Barbosa João Renato Stehmann John S. Ascher Marcelo F. Vasconcelos Paulo de Marco Peter Löwenberg-neto Viviane Gianluppi Ferro Britaldo Silveira Soares Filho Adalberto J. Santos Adriano Pereira Paglia Antonio D. Brescovit Claudio J. B. de Carvalho Daniel Paiva Silva Daniella T. Rezende Felipe Sá Fortes Leite |
author_role |
author |
author2 |
João Aguiar Nogueira Batista João Paulo Peixoto Pena Barbosa João Renato Stehmann John S. Ascher Marcelo F. Vasconcelos Paulo de Marco Peter Löwenberg-neto Viviane Gianluppi Ferro Britaldo Silveira Soares Filho Adalberto J. Santos Adriano Pereira Paglia Antonio D. Brescovit Claudio J. B. de Carvalho Daniel Paiva Silva Daniella T. Rezende Felipe Sá Fortes Leite |
author2_role |
author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Ubirajara Oliveira João Aguiar Nogueira Batista João Paulo Peixoto Pena Barbosa João Renato Stehmann John S. Ascher Marcelo F. Vasconcelos Paulo de Marco Peter Löwenberg-neto Viviane Gianluppi Ferro Britaldo Silveira Soares Filho Adalberto J. Santos Adriano Pereira Paglia Antonio D. Brescovit Claudio J. B. de Carvalho Daniel Paiva Silva Daniella T. Rezende Felipe Sá Fortes Leite |
dc.subject.por.fl_str_mv |
Spatially explicit SDM Conservation priorities |
topic |
Spatially explicit SDM Conservation priorities Ecologia Biodiversidade - Conservação |
dc.subject.other.pt_BR.fl_str_mv |
Ecologia Biodiversidade - Conservação |
description |
Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-04-23 |
dc.date.accessioned.fl_str_mv |
2023-04-19T20:55:35Z |
dc.date.available.fl_str_mv |
2023-04-19T20:55:35Z |
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/1843/52292 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.1038/s41598-019-42881-9 |
dc.identifier.issn.pt_BR.fl_str_mv |
20452322 |
dc.identifier.orcid.pt_BR.fl_str_mv |
https://orcid.org/0000-0003-4877-5414 https://orcid.org/0000-0003-4640-0942 https://orcid.org/0000-0002-9504-5441 https://orcid.org/0000-0002-7887-2461 https://orcid.org/0000-0002-3628-6405 https://orcid.org/0000-0001-5122-0247 https://orcid.org/0000-0002-6491-806X https://orcid.org/0000-0002-7703-946X https://orcid.org/0000-0002-0010-346X https://orcid.org/0000-0001-9957-5506 https://orcid.org/0000-0002-1511-5324 https://orcid.org/0000-0002-4539-4336 https://orcid.org/0000-0003-4561-5634 |
url |
https://doi.org/10.1038/s41598-019-42881-9 http://hdl.handle.net/1843/52292 https://orcid.org/0000-0003-4877-5414 https://orcid.org/0000-0003-4640-0942 https://orcid.org/0000-0002-9504-5441 https://orcid.org/0000-0002-7887-2461 https://orcid.org/0000-0002-3628-6405 https://orcid.org/0000-0001-5122-0247 https://orcid.org/0000-0002-6491-806X https://orcid.org/0000-0002-7703-946X https://orcid.org/0000-0002-0010-346X https://orcid.org/0000-0001-9957-5506 https://orcid.org/0000-0002-1511-5324 https://orcid.org/0000-0002-4539-4336 https://orcid.org/0000-0003-4561-5634 |
identifier_str_mv |
20452322 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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Scientific Reports |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Universidade Federal de Minas Gerais |
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UFMG |
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Brasil |
dc.publisher.department.fl_str_mv |
ICB - DEPARTAMENTO DE BOTÂNICA ICB - DEPARTAMENTO DE ZOOLOGIA IGC - DEPARTAMENTO DE CARTOGRAFIA |
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Universidade Federal de Minas Gerais |
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reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
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