Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Journal Articles Journal of Biogeography Year : 2019

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

Abstract

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.

Dates and versions

hal-02439732 , version 1 (14-01-2020)

Identifiers

Cite

Christine N. Meynard, David M. Kaplan, Boris Leroy. Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study. Journal of Biogeography, 2019, 46 (9), pp.2141--2144. ⟨10.1111/jbi.13626⟩. ⟨hal-02439732⟩
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