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

Predicting to new environments: tools for visualizing model behaviour and impacts on mapped... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diversity and Distributions Wiley

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

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Publisher
Wiley
Copyright
© 2012 Blackwell Publishing Ltd
ISSN
1366-9516
eISSN
1472-4642
DOI
10.1111/j.1472-4642.2012.00887.x
Publisher site
See Article on Publisher Site

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.

Journal

Diversity and DistributionsWiley

Published: Jun 1, 2012

References

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