Modelling highly biodiverse areas in Brazil

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dc.creatorUbirajara Oliveira
dc.creatorJoão Aguiar Nogueira Batista
dc.creatorJoão Paulo Peixoto Pena Barbosa
dc.creatorJoão Renato Stehmann
dc.creatorJohn S. Ascher
dc.creatorMarcelo F. Vasconcelos
dc.creatorPaulo de Marco
dc.creatorPeter Löwenberg-neto
dc.creatorViviane Gianluppi Ferro
dc.creatorBritaldo Silveira Soares Filho
dc.creatorAdalberto J. Santos
dc.creatorAdriano Pereira Paglia
dc.creatorAntonio D. Brescovit
dc.creatorClaudio J. B. de Carvalho
dc.creatorDaniel Paiva Silva
dc.creatorDaniella T. Rezende
dc.creatorFelipe Sá Fortes Leite
dc.date.accessioned2023-04-19T20:55:35Z
dc.date.accessioned2025-09-09T01:30:56Z
dc.date.available2023-04-19T20:55:35Z
dc.date.issued2019-04-23
dc.format.mimetypepdf
dc.identifier.doihttps://doi.org/10.1038/s41598-019-42881-9
dc.identifier.issn20452322
dc.identifier.urihttps://hdl.handle.net/1843/52292
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofScientific Reports
dc.rightsAcesso Aberto
dc.subjectEcologia
dc.subjectBiodiversidade - Conservação
dc.subject.otherSpatially explicit
dc.subject.otherSDM
dc.subject.otherConservation priorities
dc.titleModelling highly biodiverse areas in Brazil
dc.typeArtigo de periódico
local.citation.issue1
local.citation.spage1
local.citation.volume9
local.description.resumoTraditional 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.
local.identifier.orcidhttps://orcid.org/0000-0003-4877-5414
local.identifier.orcidhttps://orcid.org/0000-0003-4640-0942
local.identifier.orcidhttps://orcid.org/0000-0002-9504-5441
local.identifier.orcidhttps://orcid.org/0000-0002-7887-2461
local.identifier.orcidhttps://orcid.org/0000-0002-3628-6405
local.identifier.orcidhttps://orcid.org/0000-0001-5122-0247
local.identifier.orcidhttps://orcid.org/0000-0002-6491-806X
local.identifier.orcidhttps://orcid.org/0000-0002-7703-946X
local.identifier.orcidhttps://orcid.org/0000-0002-0010-346X
local.identifier.orcidhttps://orcid.org/0000-0001-9957-5506
local.identifier.orcidhttps://orcid.org/0000-0002-1511-5324
local.identifier.orcidhttps://orcid.org/0000-0002-4539-4336
local.identifier.orcidhttps://orcid.org/0000-0003-4561-5634
local.publisher.countryBrasil
local.publisher.departmentICB - DEPARTAMENTO DE BOTÂNICA
local.publisher.departmentICB - DEPARTAMENTO DE ZOOLOGIA
local.publisher.departmentIGC - DEPARTAMENTO DE CARTOGRAFIA
local.publisher.initialsUFMG
local.url.externahttps://www.nature.com/articles/s41598-019-42881-9#rightslink

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