Models of Altruism by Phenotypic Similarity Restricted; Files Only
Bavik, Linnea (Fall 2024)
Abstract
Natural selection favors genes that increase the number of replicas they generate in subsequent generations and genes for altruism are ultimately no different. One well-supported mechanism by which altruists can preferentially distribute the benefits of altruism towards their replicas is called phenotypic similarity, in which individuals use the correlations between phenotypes and overall genetic distance to infer relatedness at the altruism locus. In this thesis I explore altruism by phenotypic similarity in the context of a mechanistic model in which individuals compare phenotypes and only donate to those that are “sufficiently similar” to themselves, where the criterion for this decision is an evolving parameter called their “threshold”. In part one, we find that altruists who compare information from a large number of quantitative phenotypes against their threshold are able to evade the evolution of cheater mutants and sustain altruism even in strongly selected regimes. In part two, we model context dependence by allowing individuals to plastically adjust their similarity threshold criterion dependent on the average phenotypic distance observed between themselves and their partners. We find that despite the presence of sensing noise, context dependence is heavily favored in our simulations and the threshold plastic altruists evolve is close to the empirically optimal value for increasing the strategy’s frequency. In part three, we investigate how much population information is necessary for context-dependent strategies to remain advantageous, and find that the advantage of context dependence persists even when thresholds are formed with phenotype information from very few partners.
Table of Contents
1. Introduction 1
2. 50 shades of greenbeard: Robust evolution of altruism based on similarity of complex phenotypes 7
3. Selection favors context-dependent bias in altruism 29
4. Altruism by online learning retains plasticity advantage 50
5. Discussion 64
Appendix A. Chapter 2 Supplemental Information 69
Appendix B. Chapter 3 Supplemental Information 90
Bibliography 93
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