title: Mimicry among Unequally Defended Prey Should Be Mutualistic When Predators Sample Optimally.
abstract: Understanding the conditions under which moderately defended prey evolve to resemble better-defended prey and whether this mimicry is parasitic (quasi-Batesian) or mutualistic (Müllerian) is central to our understanding of warning signals. Models of predator learning generally predict quasi-Batesian relationships. However, predators' attack decisions are based not only on learning alone but also on the potential future rewards. We identify the optimal sampling strategy of predators capable of classifying prey into different profitability categories and contrast the implications of these rules for mimicry evolution with a classical Pavlovian model based on conditioning. In both cases, the presence of moderately unprofitable mimics causes an increase in overall consumption. However, in the case of the optimal sampling strategy, this increase in consumption is typically outweighed by the increase in overall density of prey sharing the model appearance (a dilution effect), causing a decrease in mortality. It suggests that if predators forage efficiently to maximize their long-term payoff, genuine quasi-Batesian mimicry should be rare, which may explain the scarcity of evidence for it in nature. Nevertheless, we show that when moderately defended mimics are profitable to attack by hungry predators, then they can be parasitic on their models, just as classical Batesian mimics are.
authors.forename: Thomas G
authors.initials: TG
authors.lastname: Aubier
authors.forename: Mathieu
authors.initials: M
authors.lastname: Joron
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Sherratt
mesh_terms: D000818:Animals; D005075:Biological Evolution; D000067558:Biological Mimicry; D007858:Learning; D008954:Models, Biological; D011235:Predatory Behavior; D013559:Symbiosis
keywords: Bayesian inference; Müllerian mimicry; Pavlovian conditioning; dynamic programming; optimal foraging; quasi-Batesian mimicry