The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions
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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Cites
The art of modelling range-shifting species: The art of modelling range-shifting species
Elith, J., Kearney, M., & Phillips, S. (2010) · Methods in Ecology and Evolution · doi:10.1111/j.2041-210x.2010.00036.x · Cited by 2,813
Self-citationNovel climates, no‐analog communities, and ecological surprises
Williams, J. W., & Jackson, S. T. (2007) · Frontiers in Ecology and the Environment · doi:10.1890/070037 · Cited by 1,736
Cited by
Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure
Roberts, D. R., Bahn, V., Ciuti, S., Boyce, M. S., Elith, J., Guillera‐Arroita, G., Hauenstein, S., Lahoz‐Monfort, J. J., Schröder, B., Thuiller, W., et al. (2017) · Ecography · doi:10.1111/ecog.02881 · Cited by 3,689
Self-citationMultiple Dimensions of Climate Change and Their Implications for Biodiversity
Garcia, R. A., Cabeza, M., Rahbek, C., & Araújo, M. B. (2014) · Science · doi:10.1126/science.1247579 · Cited by 765
What do we gain from simplicity versus complexity in species distribution models?
Merow, C., Smith, M. J., Edwards, T. C., Guisan, A., McMahon, S. M., Normand, S., Thuiller, W., Wüest, R. O., Zimmermann, N. E., & Elith, J. (2014) · Ecography · doi:10.1111/ecog.00845 · Cited by 683
Self-citationA checklist for maximizing reproducibility of ecological niche models
Feng, X., Park, D. S., Walker, C., Peterson, A. T., Merow, C., & Papeş, M. (2019) · Nature Ecology & Evolution · doi:10.1038/s41559-019-0972-5 · Cited by 323
Mainali, K. P., Warren, D. L., Dhileepan, K., McConnachie, A., Strathie, L., Hassan, G., Karki, D., Shrestha, B. B., & Parmesan, C. (2015) · Global Change Biology · doi:10.1111/gcb.13038 · Cited by 314
Metadata
- Authors
- Zurell, D., Elith, J., & Schröder, B.
- Venue
- Diversity and Distributions
- Publisher
- Wiley
- Published
- 2012-02-11
- Volume
- 18
- Issue
- 6
- Pages
- 628-634
- ISSN
- 0967-9952 (ISSN-L)
- 1366-9516
- 1472-4642
- OpenAlex
- W1500255874
- Cited by
- 181
- References
- 2
- FWCI
- 6.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zurell, D., Elith, J., & Schröder, B. (2012). Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions. Diversity and Distributions. https://doi.org/10.1111/j.1472-4642.2012.00887.x
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