Five (or so) challenges for species distribution modelling

TLDR

Species distribution modelling is central to biogeography, yet conceptual ambiguities and biotic and algorithmic uncertainties persist, requiring further investigation to increase confidence in model results. The study aims to identify and discuss five high‑priority areas of enquiry for species distribution modelling. The authors identify and discuss these five areas—clarification of the niche concept, improved sampling designs, better parameterization, refined model selection and predictor contribution, and enhanced model evaluation. These challenges are deemed critical for advancing the science of species distribution modelling.

Abstract

Abstract Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in model results. We identify and discuss five areas of enquiry that are of high importance for species distribution modelling: (1) clarification of the niche concept; (2) improved designs for sampling data for building models; (3) improved parameterization; (4) improved model selection and predictor contribution; and (5) improved model evaluation. The challenges discussed in this essay do not preclude the need for developments of other areas of research in this field. However, they are critical for allowing the science of species distribution modelling to move forward.