A New Mechanistic Model of Drift Feeding Based on Cognitive Limits on Visual Information Processing

Recent reviews have shown that mechanistic models of drift-feeding behavior are useful, in many theoretical and management contexts, for understanding energy intake as a function of physiological capabilities and environmental conditions. However, these models have had limited predictive success, and clear evidence now contradicts some of their foundational assumptions. To clarify conflicts between drift-feeding models and data, and to identify new metrics for evaluating such models in the future, we reviewed empirical tests of past models and other studies of the spatial behavior or diet composition of drift feeders. We then developed a new mechanistic model in which the primary characteristics of drift-feeding behavior follow from universal cognitive constraints on the rate at which animals can process visual information. This new drift-feeding model treats prey detection as a random (Poisson) process, which permits a more realistic depiction of prey detection locations and probabilities. It also incorporates signal detection theory to describe tradeoffs between search speed (a function of water velocity) and accuracy in discriminating prey from inedible debris. This model replicates and exceeds the qualitative successes of past models without using their falsified assumptions. We are currently testing it with laboratory and field data using three Alaskan drift-feeding salmonids.