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Title: Modelling the evolution and consequences of mate choice
Author: Tazzyman, S. J.
ISNI:       0000 0004 2728 8876
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2010
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This thesis considers the evolution and the consequences of mate choice across a variety of taxa, using game theoretic, population genetic, and quantitative genetic modelling techniques. Part I is about the evolution of mate choice. In chapter 2, a population genetic model shows that mate choice is even beneficial in self-fertilising species such as Saccharomyces yeast. In chapter 3, a game theoretic model shows that female choice will be strongly dependent upon whether the benefits are fixed, so that females receive the same fitness boost from a mating with a given male regardless of how many matings that male has, or dilutable, where the more females a male mates with, the lower the expected benefit to each. This leads to the prediction that mating skew should be higher in species in which the benefits of mate choice are hypothesised to be due to good genes. Part II is about the consequences of mate choice. The theoretical prediction from chapter 3 is borne out by a literature review of studies of wild populations of birds in chapter 4. In chapter 5, a quantitative genetic model about poison-dart frogs suggests that sexual selection can speed up the effect of random genetic drift. This may be of more general importance, further widening the evolutionary impact of sexual selection. Finally, in chapter 6, a game theoretic model of sperm competition shows that pre-copulatory mate choice can also have evolutionary effects upon post-copulatory behaviour, affecting the optimal ejaculate expenditure of males. Overall, mate choice is shown to be an important evolutionary force, with wide-ranging ramifications across diverse taxa, and eects so varied as to include the evolution of sex, the genetic variation in species, speciation, and post-copulatory behaviour, amongst others. These effects can be effectively explored using mathematical modelling.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available