More complex distribution models or more representative data

TLDR: In this article, the results of the best comparative study of different modeling techniques, which used pseudo-absence data selected at random, were analyzed and it was shown that good model predictions depend most critically on better biological data.

Abstract: Distribution models for species are increasingly used to summarize species’ geography in conservation analyses. These models use increasingly sophisticated modeling techniques, but often lack detailed examination of the quality of the biological occurrence data on which they are based. I analyze the results of the best comparative study of the performance of different modeling techniques, which used pseudo-absence data selected at random. I provide an example of variation in model accuracy depending on the type of absence information used, showing that good model predictions depend most critically on better biological data.