Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

作者：Jennifer D. McCabe, John Clare, Tricia A. Miller, Todd E. Katzner, Jeff Cooper, Scott G. Somershoe, David Hanni, Christine A. Kelly, Robert Craig Sargent, Eric C. Soehren, Carrie Threadgill, Mercedes Maddox, Jonathan Stober, Mark S. Martell, Thomas Salo, Andrew J. Berry, Michael Lanzone, Melissa A. Braham, Christopher J. W. McClure · 发表于：Ecography · 年份：2021 · DOI：10.1111/ecog.06058 · 被引用次数：30 · 研究领域：Species Distribution and Climate Change、Wildlife Ecology and Conservation、Ecology and Vegetation Dynamics Studies

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual‐ and population‐level inference with flexible non‐linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k ‐fold cross‐validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of indi...