The evolution of social behaviour has been studied using different frameworks based on game theory and quantitative genetics. While both approaches provide a conceptually clear explanation of evolution of social behaviour, both have been limited in their applicability to empirical systems, mainly due to difficulties in measuring model parameters. Here, I develop a new quantitative genetics approach to the study of the evolution of social behaviours based on indirect genetic effects (IGEs), which parameters can be readily determined by empirical studies. IGEs describe effects of an individual's genotype on phenotypes of social partners, which may indirectly affect their fitness. Unlike traditional quantitative genetics assuming a non-genetical, non-heritable environment, IGE models assume that part of the environment is social, provided by parents and other interacting partners, thus has a genetic basic and can be heritable. In this study I explore the effects of IGEs on the magnitude and range of phenotypic values in a focal individual. I show that social interactions may not only cause indirect genetic effects but can also modify direct genetic effects. I demonstrate that interactions can substantially alter group mean phenotype and variance. This may lead to scenarios in which between group phenotypic variation is much higher than within group variation despite similar underlying genetic properties of different groups. Further, I analyse how IGEs influence levels of selection and predictions about evolutionary trajectories. I show that IGEs can create selection pressure at the group level, leading to evolution of behaviours that would not evolve otherwise. Moreover, I demonstrate that IGEs may lead to differences in the direction of evolutionary response between genotypes and phenotypes. Building on these results, I show that IGE models can be translated to and are fully compatible with traditional kin and multilevel selection models. I express costs and benefits in IGE parameters and determine the conditions under which social interactions lead to the evolution of cooperative or harmful behaviours. Therefore, the model I propose combines the conceptual clarity of kin and multilevel selection models with the applicability of IGE models, which parameters can be empirically determined, facilitating the testing of model predictions. Finally, I show that the use of IGE models is strongly limited by the underlying assumption of linearity. I prove that the modelling of interaction dynamics leads to steady state solutions found by IGE models only under limited conditions. In this light, I discuss the relevance of results published previously and propose a solution of how this problem can be addressed.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:647374 |
| Date | January 2014 |
| Creators | Trubenova, Barbora |
| Contributors | Preziosi, Richard; Hager, Reinmar |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.research.manchester.ac.uk/portal/en/theses/indirect-genetic-effects-and-the-evolution-of-cooperation(cac253c8-500d-4f5e-91ff-878f6ead4c0e).html |
Page generated in 0.0019 seconds