Estimating diel, depth-specific foraging opportunities with a visual encounter rate model for pelagic piscivores

Abstract

We developed a visual foraging model for piscivores that predicts search volume as a function of light and turbidity. We combined this model with diel hydroacoustic measurements of depth-specific prey fish densities during summer stratification in Lake Tahoe, Lake Washington, and Strawberry Reservoir to examine differences in diel, depth-specific visual encounter rates of prey. These study sites were selected to represent gradients of increasing limnetic prey fish density and declining transparency. The model predicted over a 30-fold difference in maximum depth-specific diel encounter rates among the three lakes. Lake Washington, which was characterized by intermediate transparency and moderate limnetic prey density, had the highest predicted prey encounter rates. The pattern of prey encounter rates among the three lakes was similar to the proportional contribution of limnetic prey fishes observed in the diet of piscivores from these waters. This approach may be used to construct temporally and spatially explicit trophic interaction models for examining mechanisms underlying predator and prey distributions or to predict the response of existing or introduced predators to changing environmental conditions, prey abundance, or distribution.