The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 6 of 25
Back to Result List

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

  • 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.

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Damaris ZurellORCiDGND, Jane Elith, Boris Schröder-EsselbachORCiDGND
DOI:https://doi.org/10.1111/j.1472-4642.2012.00887.x
ISSN:1366-9516
Title of parent work (English):Diversity & distributions : a journal of biological invasions and biodiversity
Publisher:Wiley-Blackwell
Place of publishing:Hoboken
Publication type:Other
Language:English
Year of first publication:2012
Publication year:2012
Release date:2017/03/26
Tag:Environmental niche; extrapolation; inflated response curves; novel environment; sampling space; species distribution models
Volume:18
Issue:6
Number of pages:7
First page:628
Last Page:634
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
Peer review:Referiert
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.