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Brazilian marine biogeography: a multi-taxa approach for outlining sectorization

dc.contributor.authorCord, Isadora
dc.contributor.authorNunes, Lucas T.
dc.contributor.authorBarroso, Cristiane X.
dc.contributor.authorFreire, Andrea S.
dc.contributor.authorGadig, Otto B. F. [UNESP]
dc.contributor.authorGomes, Paula B.
dc.contributor.authorGurgel, Carlos F. D.
dc.contributor.authorLindner, Alberto
dc.contributor.authorMantelatto, Fernando L.
dc.contributor.authorTargino, Alessandra K. G.
dc.contributor.authorFloeter, Sergio R.
dc.contributor.institutionUniversidade Federal de Santa Catarina (UFSC)
dc.contributor.institutionUniversidade Federal Do Ceará
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Federal Rural de Pernambuco
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2023-03-01T20:34:29Z
dc.date.available2023-03-01T20:34:29Z
dc.date.issued2022-05-01
dc.description.abstractSpecies distribution patterns in the Brazilian Marine Province (BMP) are extensively debated, nevertheless no study used a multi-taxa approach to investigate possible biotic distinctions and the role of environmental factors in determining biogeographical patterns in this province. Here, we compiled the largest distributional multi-taxa dataset in the southern Atlantic (2412 reef species) to address the following: (1) similarities among areas accounting for species composition and environmental characteristics; (2) the absolute species richness of nine taxonomic groups among geographical bins; and (3) how species biogeographical patterns are explained by the environmental similarities. We hypothesized sub-provinces’ limits will be strongly correlated to environmental delimitations, being sea surface temperature a central component influencing biotic subdivision on the BMP. We found eight different geographical bins considering the environmental factors, while five considering species distributions. We also observed a latitudinal gradient of species richness for most taxa, some presenting a “mid-domain” shape pattern. Beta diversity among sub-provinces was low, and the nestedness component more important, indicating high connectivity along the BMP. Using a db-RDA, we demonstrated that environmental variables explained 64% of species clustering patterns, with sea surface temperature, water turbidity and current velocity explaining the biotic clustering of the Brazilian northeastern coast. Sub-provinces North and Abrolhos Bank were the most distinct areas regarding environmental and biotic data. Our study highlights the importance of using a multi-taxa approach to understand the relationship between biogeographical patterns, as well as its response to environmental and historical factors.en
dc.description.affiliationLaboratório de Biogeografia e Macroecologia Marinha Departamento de Ecologia e Zoologia Universidade Federal de Santa Catarina, Santa Catarina
dc.description.affiliationLaboratório de Invertebrados Marinhos do Ceará Departamento de Biologia Universidade Federal Do Ceará, Ceará
dc.description.affiliationLaboratório de Crustáceos e Plâncton Departamento de Ecologia e Zoologia Universidade Federal de Santa Catarina, Santa Catarina
dc.description.affiliationLaboratório de Pesquisa em Elasmobrânquios Instituto de Biociências Universidade Estadual Paulista “Júlio de Mesquita Filho”, São Vicente
dc.description.affiliationLaboratório de Ecologia e Conservação de Ecossistemas Marinhos Universidade Federal Rural de Pernambuco, Pernambuco
dc.description.affiliationLaboratório de Ficologia Departamento de Botânica Universidade Federal de Santa Catarina, Santa Catarina
dc.description.affiliationLaboratório de Biodiversidade Marinha Departamento de Ecologia e Zoologia Universidade Federal de Santa Catarina, Santa Catarina
dc.description.affiliationLaboratório de Bioecologia e Sistemática de Crustáceos (LBSC) Departamento de Biologia Faculdade de Filosofia Ciências e Letras de Ribeirão Preto (FFCLRP) Universidade de São Paulo (USP), São Paulo
dc.description.affiliationUnespLaboratório de Pesquisa em Elasmobrânquios Instituto de Biociências Universidade Estadual Paulista “Júlio de Mesquita Filho”, São Vicente
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdCAPES: 001
dc.description.sponsorshipIdCNPq: 307340/2019-8
dc.identifierhttp://dx.doi.org/10.1007/s00227-022-04045-8
dc.identifier.citationMarine Biology, v. 169, n. 5, 2022.
dc.identifier.doi10.1007/s00227-022-04045-8
dc.identifier.issn1432-1793
dc.identifier.issn0025-3162
dc.identifier.scopus2-s2.0-85128101300
dc.identifier.urihttp://hdl.handle.net/11449/240828
dc.language.isoeng
dc.relation.ispartofMarine Biology
dc.sourceScopus
dc.subjectEcological filters
dc.subjectLatitudinal gradients
dc.subjectMarine biogeography
dc.subjectReef environments
dc.subjectSpecies distributions
dc.titleBrazilian marine biogeography: a multi-taxa approach for outlining sectorizationen
dc.typeArtigo
unesp.author.orcid0000-0002-4220-8112[1]
unesp.author.orcid0000-0001-9543-4589[2]
unesp.author.orcid0000-0001-9933-9394[3]
unesp.author.orcid0000-0001-6280-7254[4]
unesp.author.orcid0000-0002-8109-5085[5]
unesp.author.orcid0000-0002-1555-1484[6]
unesp.author.orcid0000-0002-7321-6115[7]
unesp.author.orcid0000-0003-3288-0885[8]
unesp.author.orcid0000-0002-8497-187X[9]
unesp.author.orcid0000-0001-7117-2852[10]
unesp.author.orcid0000-0002-3201-6504[11]
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências, São Vicentept
unesp.departmentCiências Biológicas - IBCLPpt

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