Formulation of habitat suitability models for stream fish guilds: Do thestandard methods work?

摘要

Habitat suitability index (HSI) models for seven fish guilds in two segments of the upper Roanoke River drainage, Virginia, were formulated for the summer seasons of 1989 and 1990. We considered five habitat variables as potential limiting factors: depth, average and demersal velocities, average substratum size, and percent cover. These physical variables were modeled both separately and as composite HSI indices. Composite models were built from linear regression equations (both simple and multiple) in which the observed guild density in quadrats was regressed against physical microhabitat variables or individual suitability indices (SIs = predicted fish densities). There were five major findings. First, habitat variables were used independently by most fish guilds, as statistical interactions were weak and inconsistent for regression models predicting guild densities from physical variables. That is, fish-microhabitat relations for target habitat variables were typically unaffected by the condition (value) of other habitat variables. Although polynomial (curvilinear) terms were stronger than interaction terms, linear terms accounted for most of the variation in guild densities among quadrats. Second, the predictive power of these complex physical models for guild densities was matched by that of multiplying the SIs for individual microhabitat variables together. Third, this product (joint-suitability-factor) approach was superior to other methods of developing composite HSIs from individual SIs because it was consistently accurate across fish guilds (owing to the lack of strong statistical interactions) and was a simpler regression model (involving only one slope coefficient). Fourth, observed guild densities for each river segment were well correlated with those predicted by the product equation with SI data from the other river segment, thus cross-validating our HSI models in the upper Roanoke River drainage. Fifth, maximum guild densities for habitat variables that were stratified into a few or several categories provided useful indices of the limiting factors for fish guilds because higher densities indicated greater habitat specialization. Across all guilds, depth was consistently the most important factor in habitat selection. In sum, our results suggest that fish-habitat statistical interactions are not strong enough to invalidate the product equation traditionally used by fish researchers to build composite HSI models, at least when SI data are aggregated by habitat use guild.