Learning and memory in mimicry: II. Do we understand the mimicry spectrum?

摘要

The evolution of mimicry is driven by the behaviour of predators. However, there has been little systematic testing of the sensitivity of evolutionary predictions to variations in assumptions about predator learning and forgetting. To test how robust mimicry theory is to such behavioural modifications we combined sets of rules describing ways in which learning and forgetting might operate in vertebrate predators into 29 computer predator behaviour systems. These systems were applied in simulations of simplified natural mimicry situations, particularly investigating the nature of density-dependence and the benefits and losses conferred by mimicry across a spectrum of palatabilities. The classical Batesian-Muellerian spectrum was generated only by two of our 29 predator behaviour systems. Both of these 'classical predators' had extreme asymptotes of learning and fixed rate, time dependent forgetting. All edible mimics were treated by them as Batesian in that they parasitized their model's protection and had positive monotonic effects of density on model-mimic attack rates. All defended mimics were treated as Muellerian (Mullerian) in that their presence benefited their Model's protection, and showed negative monotonic density effects on attack rates. With the remaining 27 systems Batesian or Muellerian relationships extended beyond their conventional edibility boundaries. In some cases, Muellerian mimicry extended into the edible region of the 'palatability spectrum' (we term this quasi-Muellerian mimicry), and in others Batesian mimicry extended into the 'unpalatable', defended half of the spectrum (quasi-Batesian mimicry). Although most of the 29 behaviour systems included at least some regions of true Batesian and Muellerian mimicries, if forgetting was triggered by avoidance events (as suggested by J.E. Huheey) rather than by the passage of time then the mimicry spectrum excluded Mullerian mimicry altogether, and was composed of Batesian and quasi-Batesian mimicries. In addition the classical prediction of monotonic density-dependent predation was shown not to be robust against variations in the forgetting algorithm. Time based forgetting which is retarded by observations of prey, or which varies its rate according to the degree of pleasantness or unpleasantness of a prey generates non-monotonic results. Ar low mimic densities there is a positive effect on attack rates and at higher densities a negative effect. Overall, the mode of forgetting has a more significant effect on mimetic relationships than the rate of learning. It seems to matter little whether learning and forgetting are switched or gradual functions. Predictions about mimetic evolution are therefore sensitive to assumptions about predator behaviour! though more so to variations in forgetting than learning rate. Based on findings from animal psychology and mimetic populations, Mle are able to rule out a number of predator behaviour systems. We suggest that the most credible of our 29 predators are those which generate results which incorporate Batesian, quasi-Batesian and Muellerian mimicries across the 'palatability spectrum'. (C) 1999 The Linnean Society of London.