Individuals across the tree of life make costly contributions to resources that benefit the group as a whole. However, such ‘public goods’ come with a problem; a selfish individual could refrain from contributing to public goods, instead leeching off the contributions of others. How does cooperation stay stable in the face of such exploitation? This problem of the maintenance of cooperation is commonly understood through the ‘tragedy of the commons’, with resolutions to the problem largely focused on avoiding the individuals who can undermine cooperation – cheaters. In this thesis, I counter the perspective of cooperation being most vulnerable to ‘cheater’ individuals who contribute nothing, aiming instead to highlight the problem caused by the strategic (i.e. conditional and quantitative) behaviour of all individuals. To this end, I use the model organism of the social amoeba D. discoideum as an empirical system to test new models of strategic behaviour, and back an argument for the importance of conditional and quantitative contributions in the evolution of cooperation in public goods. I develop a theoretical framework of the public goods game, and empirically test its utility to predict social behaviour in simple and complex social groups, finding a close match between model predictions and empirical data (Chapters 1-2). Further, I demonstrate the important consequences of strategic contributions for how we think about conflict in public goods (Chapter 3) and how genetic self-recognition (in D. discoideum and beyond) can occur through the ‘greenbeard’ effect, which has previously been considered highly unlikely to occur in nature (Chapter 4). My work in this thesis combines theory and data to demonstrate that cooperation and conflict can be misunderstood by a binary ‘cooperate’ vs ‘cheat’ perspective, and are instead better understood through the more complex idea of conditional and quantitative strategies of all individuals shaping the patterns of cooperation and conflict we see in nature.
|Date of Award||20 Nov 2019|
|Supervisor||Jason Wolf (Supervisor) & Daniel Henk (Supervisor)|