Atualização de Documento

XIX SBSR

Formulário de atualização

O sistema de atualização, para eventuais correções, estará ativo até 30/11/2019.

Contato: bibdigital@inpe.br


Nome do Campo		Valor do Campo
Tipo de Referência		Artigo em Evento (Conference Proceedings)
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	Não esqueça de clicar na opção "+" para informar os dados dos co-autores, se tiver.		v
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Resumo	(*)(?)	Potential distribution models, when allowing the occurrence mapping of species, can be a powerful tool for conservation of natural resources programs. The objective of this study is to evaluate the performance of many modeling algorithms utilizing distribution data of the Wunderlichia azulenzis species. The species is listed in the Ministry of Environment''s National list of endangered species of flora in the Caatinga biome. Two groups of algorithms, classified according to two types of entry data (presence and absence), were evaluated using the Area Under the Curve - AUC. From the registered occurrences for the species on database Global Biodiversity Information Facility GBIF, and utilizing six temperature and precipitation variables selected from the Worldclim project, species distribution maps were created. Six different algorithms were used to create the distribution maps of the species. The Mahalanobis Distance (0,978) and the Random Forest (0,0993) algorithms presented the greatest AUC values among its respective groups, while the Bioclim (0,931) and General Linear Model - GLM (0,807) algorithms presented the lowest values. The algorithms that are a part of the group of models that use only presence registers (Bioclim, Domain and Mahalanobis Distance) were considered efficient.
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e-Mail (login)		banon