Welcome

I am a mathematical biologist interested in the evolution of ecosystem structure and patterns of species abundance and diversity. I am currently postdoctoral researcher in Annette Ostling's Lab in the department of Ecology and Evolutionary Biology at the University of Michigan, and I am currently visiting at Tulane University's Center for Computational Science. I also have ongoing collaborations with the Pacific Ecoinformatics and Computational Ecology Lab in Berkeley, CA. I study the dynamics and evolution of competition and predator-prey relationships using networks, differential and difference equations, stochastic models, and evolutionary game theory.

Community abundance patterns

Can species abundance patterns reveal underlying niche structure that differs from neutrality? Neutral dynamics are based on demographic stochasticity and immigration and niche dynamics are generated by trait differences that affect fitnesses of competing populations. We use a stochastic competition model to investigate differences that arise in species abundance distributions between niche and neutral communities. 

Collaborators: Annette Ostling, Gyuri Barabas, Rafael D'Andrea, and Trevor Bedford

Food web evolution

Food webs are complex networks of who eats whom in an ecosystem. By modeling the dynamics of these systems and the evolution of these structures through time, we can explore the impacts of speciation and adaptation on the properties of food webs. I am interested in how species survival depends on the ecosystem context in which one arises, and how it in turn, affects the species already present. By combining evolution with ecological dynamics, we can study stability and resilience of food webs in a more realistic setting.

Collaborator: Neo Martinez

Evolution of competition

Evolution can change the expected outcome of competition. When species are able to adapt quickly in the presence of competitors, two competing species may be able to coexist stably, when otherwise one would be expected to competitively exclude the other. This scenario requires certain conditions on the speed of evolution and the competition coefficients.  We use evolutionary game theory to model this and other changes that may arise in competitive systems due to evolution. These models are inspired by and compare favorably to scenarios that have arisen in competition experiments with Tribolium flour beetles.

This is my dissertation work, advised by Jim Cushing and Tom Vincent in collaboration with Bob Costantino at the University of Arizona.