Data/hora: 09/06/2024 04:04:33

Provedor de dados: 	5	
País: 	France	
Título: 	Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study	
Autores: 	Meynard, Christine N.; Kaplan, David; Leroy, Boris.	
Data: 	2019-09	
Ano: 	2019	
Palavras-chave: 	ENM; Observation errors; Outliers; Prevalence; Probabilistic approach; Sample bias; Simulations; Species distribution models; Virtual ecology; Virtual species.	
Resumo: 	Liu et al. (2018) used a virtual species approach to test the effects of outliers on species distribution models. In their simulations, they applied a threshold value over the simulated suitabilities to generate the species distributions, suggesting that using a probabilistic simulation approach would have been more complex and yield the same results. Here, we argue that using a probabilistic approach is not necessarily more complex and may significantly change results. Although the threshold approach may be justified under limited circumstances, the probabilistic approach has multiple advantages. First, it is in line with ecological theory, which largely assumes non‐threshold responses. Second, it is more general, as it includes the threshold as a limiting case. Third, it allows a better separation of the relevant intervening factors that influence model performance. Therefore, we argue that the probabilistic simulation approach should be used as a general standard in virtual species studies.	
Tipo: 	Text	
Idioma: 	Inglês	
Identificador: 	https://archimer.ifremer.fr/doc/00501/61309/64868.pdf

DOI:10.1111/jbi.13626

https://archimer.ifremer.fr/doc/00501/61309/	
Editor: 	Wiley	
Formato: 	application/pdf	
Fonte: 	Journal Of Biogeography (0305-0270) (Wiley), 2019-09 , Vol. 46 , N. 9 , P. 2141-2144	
Fonte: 	info:eu-repo/semantics/openAccess

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