Individual adaptations in stochastic environments

Summary

Many natural populations undergo radical and unpredictable fluctuations, associated with stochastic environmental conditions. Under such circumstances, fitness of a genotype (or ‘strategy’) is defined as the geometric mean of the intergenerational genotypic population growth ratel(t). Unfortunately, this population-level criterion has proved difficult to apply at the level of individual organisms.

After developing a formula for the variance ofl as the sum of developmental and environmental variance, we discuss several models of individual adaptations, involving clutch size, progeny size and number, and foraging behaviour under risk of predation, based on the geometric-mean fitness concept. We then show how the method of dynamic programming can be extended to deal with facultative behaviour in stochastic environments. Finally we discuss the concept of an evolutionarily stable strategy in a stochastic environment.

Our analysis suggests several novel interpretations of field and laboratory observations. Under the geometric mean criterion behaviour may be determined primarily by the worst likely environment; behaviour may appear suboptimal if observed only under normal or average conditions. For example,except under extreme environmental conditions, avian clutches larger than those that are observed might result in increased fecundity, with little if any cost of reproduction in terms of parental survival; however, in unusually bad years such large clutches might be disastrous, in terms of parental survival. This consideration may help explain some recently reported experimental clutch-size manipulation results. Similarly, our analysis indicates that the known phenomenon of seasonal reduction in seed size may constitute a double bet-hedging strategy, determined by parental mortality risk and future seed survival probability. We also discuss circumstances in which phenotypic polymorphism is an adaptation to environmental uncertainty. Thus almost any individual life history or behavioural adaptation may be affected by environmental stochasticity.