Modelling Species’ Distributions
Species distribution models have become a commonplace exercise over the last 10 years, however, analyses vary due to different traditions, aims of applications and statistical backgrounds. In this chapter, I lay out what I consider to be the most crucial steps in a species distribution analysis: data pre-processing and visualisation, dimensional reduction (including collinearity), model formulation, model simplification, model type, assessment of model performance (incl. spatial autocorrelation) and model interpretation. For each step, the most relevant considerations are discussed, mainly illustrated with Generalised Linear Models and Boosted Regression Trees as the two most contrasting methods. In the second section, I draw attention to the three most challenging problems in species distribution modelling: identifying (and incorporating into the model) the factors that limit a species range; separating the fundamental, realised and potential niche; and niche evolution.
KeywordsExplanatory Variable Spatial Autocorrelation Biotic Interaction Omission Error Niche Model
Over the years, many colleagues helped develop the above recipe. I am particularly grateful to Boris Schröder, Björn Reineking and Jane Elith, as well as the many participants of statistical workshops on this topic. I am also grateful to Fred Jopp, Hauke Reuter and Dietmar Kraft for improving a previous version. Funding by the Helmholtz Association is acknowledged (VH-NG-247).