WHAT CAN HABITAT PREFERENCE MODELS TELL US? TESTS USING A VIRTUAL TROUT POPULATION

Habitat selection (“preference”) models are widely used to manage fish and wildlife. Their use assumes that (1) habitat with high animal densities (highly selected habitat) is high quality habitat, and low densities indicate low quality habitat; and (2) animal populations respond positively to the availability of highly selected habitat. These assumptions are increasingly questioned but very difficult to test. We evaluated these assumptions in an individual-based model (IBM) of stream trout that reproduces many natural complexities and habitat selection behaviors. Trout in the IBM select habitat to maximize their potential fitness, a function of growth potential (including food competition) and mortality risks. We know each habitat cell's intrinsic habitat quality, the fitness potential a trout in the cell would experience in the absence of competition. There was no strong relation between fitness potential and the density of fish in the IBM; cells where fitness potential was high but density low were com...

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