Evol Ecol Res 4: 275-292 (2002)     Full PDF if your library subscribes.

A genetic algorithm approach to study the evolution of female preference based on male age

Christopher W. Beck,1* Beth Shapiro,2 Semil Choksi2 and Daniel E.L. Promislow2

1Department of Biology, Emory University, 1510 Clifton Road, Atlanta, GA 30322 and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA

Author to whom all correspondence should be addressed.
e-mail: cbeck@biology.emory.edu


In many species, females prefer to mate with older males, possibly because older males are of higher genetic quality than younger males. However, the relationship between age and genetic quality may differ among populations depending on rates of age-dependent mortality. Therefore, we examined the evolution of female preference in populations with different age structures arising from differences in rates of age-dependent and age-independent mortality. To determine the shape of optimal female preference functions for males in each of 10 ages, we used a genetic algorithm approach. This approach allowed female preference for each male age to evolve independently. At moderate levels of mortality, females showed a bias in favour of the oldest males. At higher mortality rates, however, females showed the greatest preference for intermediate age males and, at very low mortality rates, females showed little bias overall. We also examined whether costs of choice influenced equilibrium preference functions. As opportunity costs increased, females were less likely to discriminate against young males and age structure became less important in determining preference function. Our results demonstrate that demographic patterns and costs of choice can influence female preference for young versus old males. In addition, the existence of female preference can alter the underlying demographic structure in a population.

Keywords: age effects, genetic algorithm, mate choice, senescence, sexual selection.

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        © 2002 Christopher W. Beck. All EER articles are copyrighted by their authors. All authors endorse, permit and license Evolutionary Ecology Ltd. to grant its subscribing institutions/libraries the copying privileges specified below without additional consideration or payment to them or to Evolutionary Ecology, Ltd. These endorsements, in writing, are on file in the office of Evolutionary Ecology, Ltd. Consult authors for permission to use any portion of their work in derivative works, compilations or to distribute their work in any commercial manner.

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