Habitat selection patterns are density dependent under the ideal free distribution.

Abstract

Despite being widely used, habitat selection models are rarely reliable and informative when applied across different ecosystems or over time. One possible explanation is that habitat selection is context‐dependent due to variation in consumer density and/or resource availability. The goal of this paper is to provide a general theoretical perspective on the contributory mechanisms of consumer and resource density‐dependent habitat selection, as well as on our capacity to account for their effects.Towards this goal we revisit the ideal free distribution (IFD), where consumers are assumed to be omniscient, equally competitive and freely moving, and are hence expected to instantaneously distribute themselves across a heterogeneous landscape such that fitness is equalised across the population. Although these assumptions are clearly unrealistic to some degree, the simplicity of the structure in IFD provides a useful theoretical vantage point to help clarify our understanding of more complex spatial processes. Of equal importance, IFD assumptions are compatible with the assumptions underlying common habitat selection models.Here we show how a fitness‐maximising space use model, based on IFD, gives rise to resource and consumer density‐dependent shifts in consumer distribution, providing a mechanistic explanation for the context‐dependent outcomes often reported in habitat selection analysis. Our model suggests that adaptive shifts in consumer distribution patterns would be expected to lead to nonlinear and often non‐monotonic patterns of habitat selection.These results indicate that even under the simplest of assumptions about adaptive organismal behaviour, habitat selection strength should critically depend on system‐wide characteristics. Clarifying the impact of adaptive behavioural responses may be pivotal in making meaningful ecological inferences about observed patterns of habitat selection and allow reliable transferability of habitat selection predictions across time and space.