Continuous predictors of species distributions support categorically stronger inference than ordinal and nominal classes: An example with urban bats

Abstract

Understanding of how species distributions are driven by landscape-level processes has been obscured by null or inconsistent findings from poorly designed studies. We explore how differences in the way potential drivers of species distributions are defined can influence their perceived effects. Specifically, we evaluate how much statistical power is lost when continuous variables are discretised, and how the use of qualitatively defined nominal variables impacts biological interpretation of results. We fitted generalized linear models to dependent variables relating to bat distribution (species richness, diversity, relative abundance of functional groups and individual species) obtained from..