Lagging Partial Preferences for Cryptic Prey: A Signal Detection Analysis of Great Tit Foraging

Most prey species are cryptic or mimetic, and as a result, they provide variable sensory cues to predators that are only statistically correlated with resource quality. We develop an analogy between foraging for cryptic prey and basic signal detection problems. An optimization model based on this analogy predicts partial preferences for cryptic prey, with the probability of attack varying between 0 and 1 as a function of the relative frequency of prey. Experiments with great tits show that they respond to unpredictable changes in prey relative frequency by adjusting their probabilities of attack in the predicted directions, but the responses lag behind. In our experiments, the birds' behavior is most appropriate to long-term average conditions (over a span of hours, extending into the preceding day. Problems associated with assessing changing resource distributions are discussed.