Towards enhanced realism in models of biodiversity evolution
Human activities are increasingly affecting ecosystems and the services that they provide. Mathematical modeling helps to understand and predict the dynamics of ecosystems and the evolution of biodiversity. Many of the commonly used models descend from traditional predator-prey models, in which interactions with other species are represented as a weighted sum over species abundances. While these models are used to study the evolutionary emergence and maintenance of ecosystems, it remains unknown how the simplified representation of interaction intensities as weighted sums affects the results. The aim of this project is to investigate how this assumption influences the ecological and evolutionary dynamics in models of biodiversity evolution. I will approach this aim from two complementary directions: i) by investigating analytically how the weighted-sum assumption affects key properties of the dynamics for a general class of models; and ii) by investigating numerically how this assumption influences the dynamics in one or more prominent models of biodiversity evolution. The former approach promises to give insights that allow us to assess the plausibility of any given model, while the latter will reveal how the weighted sum assumption affects biodiversity evolution in specific models.