Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions

Authors

  • Damaris Zurell,

    Corresponding author
    1. Institute of Earth and Environmental Sciences, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam, Germany
    2. Institute for Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, D-14469 Potsdam, Germany
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  • Jane Elith,

    1. School of Botany, University of Melbourne, Parkville, Vic. 3010, Australia
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  • Boris Schröder

    1. Institute of Earth and Environmental Sciences, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam, Germany
    2. Landscape Ecology, Technische Universität München, Emil-Ramann-Straße 6, D-85354 Freising, Germany
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Damaris Zurell, Institute for Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, D-14469 Potsdam, Germany.
E-mail: damaris.zurell@uni-potsdam.de

Abstract

Data limitations can lead to unrealistic fits of predictive species distribution models (SDMs) and spurious extrapolation to novel environments. Here, we want to draw attention to novel combinations of environmental predictors that are within the sampled range of individual predictors but are nevertheless outside the sample space. These tend to be overlooked when visualizing model behaviour. They may be a cause of differing model transferability and environmental change predictions between methods, a problem described in some studies but generally not well understood. We here use a simple simulated data example to illustrate the problem and provide new and complementary visualization techniques to explore model behaviour and predictions to novel environments. We then apply these in a more complex real-world example. Our results underscore the necessity of scrutinizing model fits, ecological theory and environmental novelty.

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