Is it possible to predict habitat use by spawning salmonids?: A test using California golden trout (Oncorhynchus mykiss aguabonita)

It is widely believed that stream salmonids select spawning sites based on water depth, water velocity, and substrate size. Attempts to predict spawning locations using these habitat features have met with little success, however. In this study, we used nonparametric logistic regression to determine what habitat features were associated with the locations chosen by spawning California golden trout (Oncorhynchus mykiss aguabonita). From this nonparametric model, we developed a parametric model that incorporated the habitat features most strongly associated with spawning sites and used this model to calculate the probability of use by spawning golden trout for specific stream locations. The overall nonparametric model was highly significant and explained 62% of the variation in spawning location. Four of the eight habitat variables, substrate size, water depth, water velocity, and stream width, had highly significant effects and alone explained 59% of the variation in spawning location. The results of a cross-validation procedure indicated that the parametric model generally provided a good fit to the data. These results indicate that location-specific probabilities of use were predictable based on easily measured habitat characteristics and that nonparametric regression, an approach still rarely used in ecological studies, may have considerable utility in the development of fish-habitat models. Given the escalating pace at which fish habitats are being altered, such models are increasingly important in predicting the effects of these alterations on populations.