Minimum required number of specimen records to develop accurate species distribution models

Species Distribution Models (SDMs) are widely used to predict the occurrence of species. Because SDMs generally use presence-only data, validation of the predicted distribution and assessing model accuracy is challenging. Model performance depends on both sample size and species’ prevalence, being the fraction of the study area occupied by the species. Here, we present a novel method using simulated species to identify the minimum number of records required to generate accurate SDMs for taxa of different pre-defined prevalence classes. We quantified model performance as a function of sample size and prevalence and found model performance to increase with increasing sample size under constant prevalence, and to decrease with increasing prevalence under constant sample size. The Area Under the Curve (AUC) is commonly used as a measure of model performance. However, when applied to presence-only data it is prevalence-dependent and hence not an accurate performance index. Testing the AUC of...