Species distribution models (SDMs) based on occurrence and environmental data are used extensively to model species’ niches and predict e.g. the spread of invasive species or responses to changing climates. Such models can only perform as well as the data that feeds them, and are thus vulnerable to biases in the underlying data.
This study considers IUCN-derived expert-based range maps as an alternative source of species distribution information, and evaluate the modelling performance of such data compared to models using empirical occurrence data. Although using the range maps as a base for SDM involves sampling pseudo-occurrences, the researcher finds that while comparing the predicted distributions of 85 species based on either GBIF-mediated occurrences or on expert-based range maps, the two approaches produce similar results.
The author concludes by arguing that expert-based maps may be used for SDM when true occurrence data is limited or known to be biased.