Understanding how both the differences and similarities among species contribute to community patterns is a central goal of community ecology. Recently, there have been strong efforts to understand how rapid evolution and ecological dynamics can feedback on each other. In certain scenarios, evolutionary processes within communities have been demonstrated to facilitate the emergence of ecological equivalence. Most investigations into the emergence of ecological equivalence, however, focus solely on competitive interactions. In food webs, species face both competitive interactions and consumer-resource interactions. Here, we investigate the relationship between the trait convergence and the rate of trait evolution using a stochastic, individual-based simulation of a quantitative genetic eco-evolutionary model of food web communities. In particular, we are interested in how the forces of competition and omnivory jointly affect trait convergence.
Results/Conclusions
Our simulation results allow direct comparison between scenarios with no evolution to communities with variable rates of evolution. By tracking both the changes in population densities and trait values through time, we are able to quantify both convergence of traits and patterns of population persistence. Overall, we find that there is more trait convergence in communities with higher rates of evolution. In species pairs that persist in the communities, we found that, on average, the difference between trait values decreases significantly with the rate of evolution. Further, we discuss the relationship between the mutational generation of trait variation, and the ecological interactions, and how this mutational variance may facilitate the evolution of ecological equivalence. Finally, we touch on how the evolution of ecological equivalence in our model relates to community stability. Together, our results provide a glimpse of how the variable interaction types in diverse communities can present unique combinations of selection pressures, and point toward the importance of considering the complexities arising from the broader community context when studying trait evolution.