Evolutionary bet-hedging reconsidered: What is the mean–variance trade-off of fitness?

Abstract

In traditional theories, bet-hedging in evolutionary biology is defined as a trade-off between the within-generation arithmetic mean fitness (AMF) of a genotype and between-generation variance (BGV) in AMF across generations. The rationale of this definition is that a bet-hedger genotype suppresses the BGV to increase between-generation geometric mean fitness (GMF; an index of long-term sustainability), which in turn entails costs in terms of AMF. However, too strict interpretation of this definition causes confusion among empirical researchers. For example, in empirical studies comparing a putative bet-hedger (e.g., producing a generalist phenotype or mixture of various phenotypes) and non-bet-hedger control (e.g., producing only a specialist phenotype), reviewers sometimes request that a necessary condition of bet-hedging is that the bet-hedger candidate shows a smaller arithmetic mean of AMFs obtained from multiple generations and larger GMF than the control. However, the cost of bet-hedging is incurred at the potential genotypic level and thus the decrease of AMF mean is not necessarily observed at the phenotypic level (especially if bet-hedger individuals have good conditions). Moreover, contrary to previous arguments, the “fine-grained” environments would promote bet-hedging because even monomorphic specialist genotypes increase GMF if their population size is sufficiently large. Computer simulations support these views. I try to shift the definition of bet-hedging from the trade-off-based one to the GMF-based one: bet-hedging is any strategy to increase the between-generational GMF to avoid extinction of its controlling genotype against unpredictable environmental fluctuation. Under this new light, bet-hedging will be a universal law of biology.