Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study

Type Article
Date 2019-09
Language English
Author(s) Meynard Christine N.1, Kaplan David2, Leroy Boris3
Affiliation(s) 1 : CBGP, INRA, CIRAD, Montpellier SupAgro Univ Montpellier Montpellier, France
2 : IRD MARBEC (Univ. Montpellier, CNRS, Ifremer, IRD) Sète, France
3 : Unité Biologie des organismes et écosystèmes aquatiques (BOREA), Muséum National d'Histoire Naturelle, Sorbonne Université, Université de Caen Normandie, Université des Antilles, CNRS, IRD Paris ,France
Source Journal Of Biogeography (0305-0270) (Wiley), 2019-09 , Vol. 46 , N. 9 , P. 2141-2144
DOI 10.1111/jbi.13626
WOS© Times Cited 3
Keyword(s) ENM, observation errors, outliers, prevalence, probabilistic approach, sample bias, simulations, species distribution models, virtual ecology, virtual species

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.

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