A cautionary note on the use of hypervolume kernel density estimators in ecological niche modelling |
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| Authors: | Huijie Qiao Luis E Escobar Erin E Saupe Liqiang Ji Jorge Soberón |
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| Institution: | 1. Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China;2. Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, USA;3. Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St Paul, MN, USA;4. Department of Geology and Geophysics, Yale University, New Haven, CT, USA;5. Biodiversity Institute and Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KN, USA |
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| Abstract: | Blonder et al. ( 2014 , Global Ecology and Biogeography, 23, 595–609) introduced a new multivariate kernel density estimation (KDE) method to infer Hutchinsonian hypervolumes in the modelling of ecological niches. The authors argued that their KDE method matches or outperforms several methods for estimating hypervolume geometries and for conducting species distribution modelling. Further clarification, however, is appropriate with respect to the assumptions and limitations of KDE as a method for species distribution modelling. Using virtual species and controlled environmental scenarios, we show that KDE both under‐ and overestimates niche volumes depending on the dimensionality of the dataset and the number of occurrence records considered. We suggest that KDE may be a viable approach when dealing with large sample sizes, limited sampling bias and only a few environmental dimensions. |
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| Keywords: | Ecological space Hutchinsonian hypervolumes minimum volume ellipsoid multivariate kernel density estimation niche virtual species |
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