Eco-Evolutionary Interactions and their Dynamics

Most of the experimental and theoretical studies of eco-evolutionary dynamics are based on biological interactions between various agents from either the same species or from different species. If we look at the whole picture, individuals take part in diverse interactions simultaneously, and they adopt varied roles or strategies in each interaction. To study the evolutionary dynamics of a population, it is therefore crucial to capture the combined effects of all the interactions that an individual is a part of. To that aim, in the first part of my thesis, I construct a mathematical framework residing in evolutionary game theory that allows to account for multiple interactions. In infinite populations, I find that the composition of a population in which individuals are involved in combined games shows different dynamical trajectories and different equilibrium points as compared to a population in which individuals only take part in single games considered in isolation. For finite populations, I derive an expression for calculating the fixation probability of a strategy, which is an important stochastic property and here too, I find that combining even a neutral game with another game could change the dynamics. In the second part, I use the framework developed in the first part to study the dynamics in the numbers of male and female individuals in a population when jointly considering several life-history traits. Life-history traits may have sex-specific differences. Using evolutionary game theory and population dynamics, I show that sex-specific differences in parental investment, ornamentation, and immune response give rise to skewed adult sex ratios. My results fit with empirical observations from a wide range of taxa. In the previous study, the sex-specific differences in certain life-history traits were a given parameter. But how did these sex-specific differences in various life-history traits emerge in the first place? The last part of this thesis presents the evolution of sexual dimorphism in immunity in relation to parental investment. Experimental results show that an increase in parental investment may give rise to better immune responses. I use a state-dependent dynamic optimization method, where parental investment and immunocompetence are considered to be two different traits of an individual. Every individual has a certain amount of energy reserves at a certain time. I study the trade-off between allocating reserves to parental effort and to immunity in such a way that they maximize an individual’s fitness. Through this study, I show that for most species systems, it is optimal to invest more in immunocompetence when the time spent in parental investment is longer. Thus, this thesis uses population dynamics, evolutionary game theory, and state-dependent dynamic optimization modeling in order to advance our understanding of eco- evolutionary consequences of multiple interlinked interactions between individuals or traits within individuals.


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