Use este identificador para citar o ir al link de este elemento: http://hdl.handle.net/1843/52292
Tipo: Artigo de Periódico
Título: Modelling highly biodiverse areas in Brazil
Autor(es): 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
Resumen: 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.
Asunto: Ecologia
Biodiversidade - Conservação
Idioma: eng
País: Brasil
Editor: Universidade Federal de Minas Gerais
Sigla da Institución: UFMG
Departamento: ICB - DEPARTAMENTO DE BOTÂNICA
ICB - DEPARTAMENTO DE ZOOLOGIA
IGC - DEPARTAMENTO DE CARTOGRAFIA
Tipo de acceso: Acesso Aberto
Identificador DOI: https://doi.org/10.1038/s41598-019-42881-9
URI: http://hdl.handle.net/1843/52292
Fecha del documento: 23-abr-2019
metadata.dc.url.externa: https://www.nature.com/articles/s41598-019-42881-9#rightslink
metadata.dc.relation.ispartof: Scientific Reports
Aparece en las colecciones:Artigo de Periódico

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