Elina Takola
Individuals of the same species often differ consistently in their use of resources, their responses to environmental gradients, and their movement decisions. Between-individual variation across niche axes has been shown to have important ecological consequences. However, practical frameworks that translate modern tracking data and space-use patterns into operational, comparable measures of individual specialization in habitat use remain limited. The individualized niche concept has inherited the plasticity of the ecological niche concept, and its quantification is considered a laborious task. Here, a workflow that estimates realized and potential individualized niches from movement data using mixed-effects resource selection functions and niche multidimensional hypervolumes is presented. The workflow combines random-intercept and random-slope resource selection functions with relative selection probabilities and ecological niche indices. The outputs of resource selection functions are used to create a kernel density-estimated hypervolume, and individualized niches are quantified using niche breadth and pairwise niche overlap indices. In addition, repeatability estimates are used to capture consistent among-individual differences and allow direct comparisons between realized and potential niche components. The workflow is implemented exclusively in the programming language R. A case study using publicly available northern lapwing ( Vanellus vanellus ) tracking data illustrates how the workflow can integrate multiple environmental variables, including earthworm abundance, human presence, pesticides, management, soil variables, and vegetation, to characterize individualized niches. The proposed workflow is transferable across taxa of mobile organisms and can facilitate the study of niche specialization and population-level heterogeneity across scales.