Extending utility of hierarchical models to multi-scale habitat selection

Aim: Characterizing animal habitat selection is central to ecology and conservation, and understanding selection across multiple spatial scales is a particular priority for research. However, the ability of selection models to capture multi-scale response has been limited by the dual analytical hurdles of cross-scale collinearity and overlapping landscapes. The aim of this study was to overcome these limitations using a novel, spatially hierarchical approach. Location: North America's northern Great Plains (U.S.A. and Canada). Methods: We developed a novel adaptation of the occupancy modelling framework that integrates animal response conditionally across scales. We then compared outcomes to those from a traditional multi-scale model. We illustrated our approach using the breeding distribution of two North American grassland songbirds of conservation concern, Sprague's Pipit Anthus spragueii and Chestnut-collared Longspur Calcarius ornatus. Results: Our model successfully captured bird response to local habitat within a broader landscape context, even when habitat associations occurred in opposite directions across scale. Probabilities of occupancy were more strongly affected by local conditions when landscape context was favourable than when it was unfavourable. The traditional multi-scale approach extended problems of scale into spatial predictions by over-estimating occurrence where conditions were locally favourable but regionally unsuitable. Main conclusions: The spatially hierarchical approach provides an integrated model of habitat selection across scales by allowing broader landscape context to shape local response to conditions. For grassland songbirds, our application enabled targeting that could enhance the expected benefits of conservation when compared to the traditional approach.