Simulating Eco-evolutionary Processes in an Obligate Pollination Model with a Genetic Algorithm

Abstract

Pollination interactions are common, and their maintenance is critical for many food crops upon which human populations depend. Pollination is a mutualism interaction; together with predation and competition, mutualism makes up the triumvirate of fundamental interactions that control population dynamics. Here we examine pollination interactions (nectar reward for gamete transport service) using a simple heuristic model similar to the Lotka-Volterra models that have underpinned our understanding of predation and competition so effectively since the 1920s. We use a genetic algorithm to simulate the eco-evolutionary interactions of the plant and pollinator populations and examine the distributions of the parameter values and zero isoclines to infer the relative ubiquity of the various eco-evolutionary outcomes possible in the model. Our results suggest that trade-offs between costs and benefits for the pollinator may be a key component of obligate pollination systems in achieving adaptive success creating and stably occupying mutualist niches.