Evolutionary bet-hedging in the real world: empirical evidence and challenges revealed by plants

Abstract

Understanding the adaptations that allow species to live in temporally variable environments is essential for predicting how they may respond to future environmental change. Variation at the intergenerational scale can allow the evolution of bet-hedging strategies: a novel genotype may be favoured over an alternative with higher arithmetic mean fitness if the new genotype experiences a sufficiently large reduction in temporal fitness variation; the successful genotype is said to have traded off its mean and variance in fitness in order to 'hedge its evolutionary bets'. We review the evidence for bet-hedging in a range of simple plant systems that have proved particularly tractable for studying bet-hedging under natural conditions. We begin by outlining the essential theory, reiterating the important distinction between conservative and diversified bet-hedging strategies. We then examine the theory and empirical evidence for the canonical example of bet-hedging: diversification via dormant seeds in annual plants. We discuss the complications that arise when moving beyond this simple case to consider more complex life-history traits, such as flowering size in semelparous perennial plants. Finally, we outline a framework for accommodating these complications, emphasizing the central role that model-based approaches can play.

Figure 1.

Mean germination fraction of 10 species of desert annuals versus variation in per capita reproductive success. Codes indicate species names; see Venable (2007) for codes and a detailed description of the study.

Figure 2.

The fitness landscape for flowering strategies in C. vulgaris in the context of different types of environmental variation, obtained by eliminating stochastic elements from a model containing all observed sources of fluctuations (see text). Stochastic recruitment reduces the fitness of plants adopting a small-flowering strategy more than any other form of stochasticity, because small-flowering plants all flower at approximately the same age, and therefore this strategy will be least buffered against year to year fluctuations in recruitment. By contrast, stochastic variation in survival affects the fitness of small-flowering plants very little, since flowering early leaves them unexposed to many years of fluctuations. For large-flowering plants, stochastic recruitment and stochastic survival have very similar effects. See Childs et al. (2004) for a detailed description of the models. Dashed line, stochastic survival only; thin solid line, constant model; thick solid black line, fully stochastic model; dashed–dotted line, stochastic recruitment only.