Outlier detection methods are still effective even using virtual species created with the probabilistic approach

0Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Liu et al. (Journal of Biogeography, 2018, 45:164–176) presented an approach to detect outliers in species distribution data by developing virtual species created using the threshold approach. Meynard et al. (Journal of biogeography, 2019, 46:2141–2144) raised concerns about this approach stating that ‘using a probabilistic approach … may significantly change results’. Here we provide a new series of simulations using the two approaches and demonstrate that the outlier detection approach based on pseudo species distribution models was still effective when using the probabilistic approach, although the detection rate was lower than when using the threshold approach.

Cite

CITATION STYLE

APA

Liu, C., White, M., & Newell, G. (2020, September 1). Outlier detection methods are still effective even using virtual species created with the probabilistic approach. Journal of Biogeography. Blackwell Publishing Ltd. https://doi.org/10.1111/jbi.13872

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free