Game Theoretical Approaches to Infer Fitness from Traits

Abstract

Abstract Evolutionary game theory becomes a useful (and some would argue, necessary) tool when strategy success depends on what other individuals in the community are doing. The evolutionarily stable strategy (ESS) resists an invader with a different strategy that is introduced at low density. That is, the ESS is a peak on a fitness landscape, where alternative strategies have lower fitness and are therefore unsuccessful at invading from low densities. In evolutionary game theory, there are players, strategies, and payoffs. Players are individual organisms, strategies are heritable phenotypes (traits), and the payoff is fitness expressed as the per capita growth rate of a strategy in a given abiotic and biotic environment. Once the demographic parameters of a population model become functions of the focal individual’s trait, the traits in the community, the densities of those that possess those traits, and the environmental conditions, then the population model becomes a game theoretic model. Tall species are adapted to productive sites because the consequences of not keeping up with their neighbors is deep shade and eventual death. Plants produce more leaves, stems, and roots than what is optimal for the most efficient harvesting of required resources for growth because excess tissue production provides a competitive advantage by pre-empting the resources before others obtain them. A combination of empirical approaches and game theoretical approaches is the most promising pathway toward the maturation of plant strategy theory.