Phenotypic diversity as an adaptation to environmental uncertainty

  • Donaldson-Matasci M
  • Lachmann M
  • Bergstrom C
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Question: What is the general quantitative relationship between adaptive phenotypic diversity, or bet-hedging, and the environmental uncertainty that selects for it? Mathematical methods: Building on the fitness set approach introduced by Levins, we develop a graphical heuristic for determining the optimal amount of diversity in a fluctuating environment. We use as our optimality criterion the expected long-term growth rate of a lineage. Key insights: Each of the phenotypes in a polyphenic population may be seen as investing a certain proportion of its reproductive effort in each of the possible environments. A bet-hedging lineage that produces the phenotypes in just the right proportions - so that the overall reproductive investment in each environment matches the environmental frequencies - grows faster on average than other lineages. How much faster it grows than the resident population, and thus the strength of selection towards the optimal bet-hedging strategy, depends on how far the residents are from the optimal investment profile. Predictions: A rigorous empirical demonstration that bet-hedging is adaptive requires a comparison of the degree of phenotypic diversification in similar populations subject to varying levels of environmental uncertainty. We confirm that bet-hedging should be observed only within a certain range of environmental variation; when the environment is more predictable than this, a phenotypic generalist would do better. We furthermore provide a simple method to calculate this range, based on the shape of the fitness trade-offs. Within this range, we predict a linear relationship between the frequency of phenotypes and the frequency of environments, independent of the shape of the trade-offs.

Author-supplied keywords

  • Bet hedging
  • Fluctuating environment
  • Generalist
  • Life history
  • Plasticity
  • Polyphenism
  • Trade-off
  • specialist

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  • M.C. Donaldson-Matasci

  • Michael Lachmann

  • C.T. Bergstrom

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