Predicting relative abundance using evolutionary game theory

Questions: Can game theoretic models of competition-driven co-evolution help us to understand patterns of species abundance within a community? Can we use these models to predict the presence and abundance of species in a ‘real’ biological community where species are represented by their ecologically important strategies? Mathematical methods: We use an evolutionary game approach to model the assembly of biological communities. We examine several modifications of the Lotka-Volterra competition model using Vincent and Brown’s approach with Darwinian dynamics. Key assumptions: We define an ecological community as a group of species that obey the same rules of ecological engagement and that compete in a local area for the same or similar resources. We also assume that strategies can influence the outcome of the ‘ecological engagement’ in the manner of an evolutionary game and that species are defined by their population’s mean strategy. New strategies are allowed to arise via evolutionary dynamics. Predictions: Unimodal carrying capacity functions produce relative abundance distributions with many common species and few rare species. Polymodal carrying capacity functions produce relative abundance distributions with few common species and many rare species. Polymodal carrying capacity functions that contain one high peak lead to strong dominance for one species. Increasing the competitive asymmetries leads to changes in rank order of species. In addition, we use our modelling approach to predict community structure of Geospiza finches on Isla Wolf of the Galapagos Islands. We predict the evolutionary co-existence of only two beak strategies and that the relative abundance of the larger-beaked strategy should be about 30% that of the smaller-beaked strategy.

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