Predator-induced plasticity in web-building behaviour

Animals are frequently faced with trade-offs created by the fact that both resource acquisition and risk of mortality increase with activity, for example, with foraging speed or time spent foraging. We develop models predicting adaptive responses for both foraging speed and proportion of time active when individual growth rate and mortality risk are functions of these variables. Using the criterion that animals should minimize the ratio of mortality to growth rates, we show that, when both growth and mortality rates are linear with activity levels, the latter should be either maximal or minimal depending on resource level. If growth rate is a decelerating function of activity, then speed or time active should decrease with increases in resources, handling time, or the effect of activity on mortality rate. By contrast, if mortality rate unrelated to activity increases, then activity rate also should increase. We also develop predictions for cases in which time horizon is critical using a dynamic programming framework. The general patterns of predicted activity responses are similar to the time-invariant analytical solutions, but foraging speed is reduced relative to the analytical solutions when time remaining is long or when accumulated reserves are high. This effect is ameliorated when accumulated reserves (size) increase resource capture efficiency or reduce mortality risk. If resources decline with time (e.g., because of competition) optimal foraging speeds are also higher than predicted by the analytical solutions. We discuss the relation of our predictions to previous models and the available empirical evidence. The majority of available data appear to be consistent with our models, and in some cases quantitative comparisons are quite close. Finally, we discuss the implications of our results for ontogenetic changes in behavior and for population- and community-level phenomena, particularly the role of activity responses in competitive interactions and indirect effects and patterns of coexistence among competitors.

Animal communication systems have evolved so that individuals can make decisions based upon the behaviour, physiology or morphology of others. Receiving mechanisms probably evolve to increase the efficiency and reliability of information reception whereas signals probably evolve to increase the efficiency of communication and reliability of manipulation of the receiving individual to the benefit of the emitter. The minimum requirement for clear reception suggests that any study of the evolution and design of communication systems must consider the factors that affect the quality of the received and processed signal. Critical information is needed about how the signal is generated and emitted, how it fares during transmission through air, water or substrate, how it is received and processed by the receiver's sensory and cognitive systems, and the factors which affect the fitness consequences of alternative ways of reacting to the information contained in the signal. These should allow predictions about the kinds and forms of signals used by animals signalling under known conditions. Phylogenetic history, and the geological time a clade spends in different signalling environments, will also affect signal evolution, and hence the success of predictions about signal design. We need to use methods of many different biological fields to understand the design and evolution of signals and signalling systems.