Virtual species distribution models: Using simulated data to evaluate aspects of model performance

Species distribution models (SDMs) have become a dominant paradigm for quantifying species-environment relationships, and both the models and their outcomes have seen widespread use in conservation studies, particularly in the context of climate change research. With the growing interest in SDMs, extensive comparative studies have been undertaken. However, few generalizations and recommendations have resulted from these empirical studies, largely due to the confounding effects of differences in and interactions among the statistical methods, species traits, data characteristics, and accuracy metrics considered. This progress report addresses virtual species distribution models': the use of spatially explicit simulated data to represent a true' species distribution in order to evaluate aspects of model conceptualization and implementation. Simulating a true' species distribution, or a virtual species distribution, and systematically testing how these aspects affect SDMs, can provide an important baseline and generate new insights into how these issues affect model outcomes.