Environmental Engineering Reference
In-Depth Information
Chapter 13
Modelling Species' Distributions
Carsten F. Dormann
Abstract Species distribution models have become a commonplace exercise over
the last 10 years, however, analyses vary due to different traditions, aims of applica-
tions 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 visua-
lisation, dimensional reduction (including collinearity), model formulation, model
simplification, model type, assessment of model performance (incl. spatial autocor-
relation) and model interpretation. For each step, the most relevant considerations are
discussed, mainly illustrated with Generalised Linear Models and Boosted Regres-
sion 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.
13.1
Introduction
As more species types undergo rapid human-induced extinction, understanding why
species occur where they do is becoming a highly relevant, pressing and potentially
life-saving topic. Conservation actions, such as establishing protected site networks,
adapting land use, providing stepping-stone habitats all require an idea of how the
target species will respond. Furthermore, using organisms as a “bioassay technique”,
i.e. indicators of environmental trends (such as climate change, air pollution, over-
fishing), demands an intimate knowledge of the organism's niche. Species distribution
modelling (SDM) attempts to identify the probable causes of species whereabouts.
We seek to delineate the realized niche of an organismbased on its current distribution
with respect to the environment (for definitions and concepts see Guisan and Thuiller
2005; Kearney 2006; Sober´n 2007; Elith and Leathwick 2009b).
