How to evaluate community predictions without thresholding?

Stacked species distribution models (S-SDM) provide a tool to make spatial predictions about communities by first modelling individual species and then stacking the modelled predictions to form assemblages. The evaluation of the predictive performance is usually based on a comparison of the observed and predicted community properties (e.g., species richness, composition). However, the most available and widely used evaluation metrics require the thresholding of single species’ predicted probabilities of occurrence to obtain binary outcomes (i.e., presence/absence). This binarisation can introduce unnecessary bias and error. Herein, we present and demonstrate the use of several groups of new or rarely used evaluation approaches and metrics for both species richness and community composition that do not require thresholding but instead directly compare the predicted probabilities of occurrences of species to the presence/absence observations in the assemblages. Community AUC, whic...