title: Quantifying the effect of habitat availability on species distributions.
abstract: 1. If animals moved randomly in space, the use of different habitats would be proportional to their availability. Hence, deviations from proportionality between use and availability are considered the tell-tale sign of preference. This principle forms the basis for most habitat selection and species distribution models fitted to use-availability or count data (e.g. MaxEnt and Resource Selection Functions). 2. Yet, once an essential habitat type is sufficiently abundant to meet an individual's needs, increased availability of this habitat type may lead to a decrease in the use/availability ratio. Accordingly, habitat selection functions may estimate negative coefficients when habitats are superabundant, incorrectly suggesting an apparent avoidance. Furthermore, not accounting for the effects of availability on habitat use may lead to poor predictions, particularly when applied to habitats that differ considerably from those for which data have been collected. 3. Using simulations, we show that habitat use varies non-linearly with habitat availability, even when individuals follow simple movement rules to acquire food and avoid risk. The results show that the impact of availability strongly depends on the type of habitat (e.g. whether it is essential or substitutable) and how it interacts with the distribution and availability of other habitats. 4. We demonstrate the utility of a variety of existing and new methods that enable the influence of habitat availability to be explicitly estimated. Models that allow for non-linear effects (using b-spline smoothers) and interactions between environmental covariates defining habitats and measures of their availability were best able to capture simulated patterns of habitat use across a range of environments. 5. An appealing aspect of some of the methods we discuss is that the relative influence of availability is not defined a priori, but directly estimated by the model. This feature is likely to improve model prediction, hint at the mechanism of habitat selection, and may signpost habitats that are critical for the organism's fitness.
authors.affiliation: IMARES Wageningen UR, PO Box 167, 1790AD, Den Burg, The Netherlands; Department of Aquatic Ecology and Water quality Management, Wageningen UR, PO Box 47, 6700AA, Wageningen, the Netherlands.
authors.forename: Geert
authors.initials: G
authors.lastname: Aarts
authors.forename: John
authors.initials: J
authors.lastname: Fieberg
authors.forename: Sophie
authors.initials: S
authors.lastname: Brasseur
authors.forename: Jason
authors.initials: J
authors.lastname: Matthiopoulos
mesh_terms: D000818:Animals; D002755:Choice Behavior; D003198:Computer Simulation; D004463:Ecology / Q000379:methods*; D017753:Ecosystem; D008954:Models, Biological
keywords: climate change; conservation; discrete choice models; foraging; generalized additive model; generalized functional response; generalized linear mixed effect model; inhomogeneous Poisson point process; integrated nested Laplace approximation; sampling design; spline smoother