I am interested in the patterns of diversity exhibited by ecological communities and the biological processes that shape them. In particular, I have studied how coevolution mediates the response of mutualistic networks to climate change, the transition from mutualism to parasitism mediated by phenotypic evolution and have developed model-based statistical methods to measure coevolution in the wild. My work also contributes to the synthesis of theoretical evolutionary ecology by relating population genetics, quantitative genetics and population dynamics via measure-valued branching processes and stochastic partial differential equations.
Current Position & Trajectory
I am a second-year postdoctoral researcher at Michigan State University in The Bradburd Lab. My current research applies mathematical and computational approaches to elucidate the genomic signature of host-parasite coevolution in continuous-space. My long-term goal is to start a lab with two primary objectives. The first is to integrate mathematical approaches to genetics, coevolution, community ecology and eventually ecosystem ecology for theoretical explorations of the causes and consequences of genetic and ecological patterns across spatial, temporal and taxonomic scales. The second is the development of statistical methods to infer ecological and evolutionary processes and to forecast future states of populations, communities and ecosystems.
I defended my PhD June 30, 2020. My dissertation contributes to a coevolutionary theory of community ecology with a focus on plant-pollinator networks. Using Diffusion Limits of Measure-Valued Branching Processes (e.g., super-Brownian motion), I introduced an approach to derive the stochastic dynamics of populations and quantitative traits from biological first principles (Week et. al. 2021). Using this framework, I have investigated the evolutionary dissolution of mutualisms experiencing coevolutionary arms races (Week & Nuismer 2021) and have developed a Maximum Likelihood method to infer the strength of coevolution between pairs of species using spatially structured phenotypic data (Week & Nuismer 2019). My defense was recorded and can be viewed here. Interactive slides are available here.