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PMID: 28565011 Published · ppublish English Journal Article

THE EVOLUTIONARILY STABLE PHENOTYPE DISTRIBUTION IN A RANDOM ENVIRONMENT.

Evolution; international journal of organic evolution ·Vol. 49 ·No. 2 ·1995-04-00 ·Pages 337-350

Sasaki A, Ellner S

Abstract

In an unpredictably changing environment, phenotypic variability may evolve as a "bet-hedging" strategy. We examine here two models for evolutionarily stable phenotype distributions resulting from stabilizing selection with a randomly fluctuating optimum. Both models include overlapping generations, either survival of adults or a dormant propagule pool. In the first model (mixed-strategies model) we assume that individuals can produce offspring with a distribution of phenotypes, in which case, the evolutionarily stable population always consists of a single genotype. We show that there is a unique evolutionarily stable strategy (ESS) distribution that does not depend on the amount of generational overlap, and that the ESS distribution generically is discrete rather than continuous; that is, there are distinct classes of offspring rather than a continuous distribution of offspring phenotypes. If the probability of extreme fluctuations in the optimum is sufficiently small, then the ESS distribution is monomorphic: a single type fitted to the mean environment. At higher levels of variability, the ESS distribution is polymorphic, and we find stability conditions for dimorphic distributions. For an exponential or similarly broad-tailed distribution of the optimum phenotype, the ESS consists of an infinite number of distinct phenotypes. In the second model we assume that an individual produces offspring with a single, genetically determined phenotype (pure-strategies model). The ESS population then contains multiple genotypes when the environmental variance is sufficiently high. However the phenotype distributions are similar to those in the mixed-strategies model: discrete, with an increasing number of distinct phenotypes as the environmental variance increases.

Keywords
Bet-hedging evolutionarily stable strategy (ESS) genetic polymorphism phenotypic variation random environment
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Sasaki Akira
Department of Biology, Faculty of Science, Kyushu University, Fukuoka 812, Japan.
Ellner Stephen
Biomathematics Program, Department of Statistics, North Carolina State University, Raleigh, NC, 27695-820.
Article Info
Journal
Evolution; international journal of organic evolution
Abbr.
Evolution
ISSN
1558-5646
Published
1995-04-00
Pages
337-350
Language
English
Region
United States
NLM ID
0373224
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