Quantitative models allow us to apply the logic and rationality of math and computer science to understand if our view of how ecological systems work is a reasonable one. We are broadly interested in the development and testing of ecological models. Current work focuses on species-area relationships, community dynamics, and metabolic ecology.
Zero-sum dynamics: Zero-sum dynamic models attempt to predict the influence of resource constraints, or other limiting factors, on ecological systems. In collaboration with the Ernest Lab we are interested in using these models to understand the dynamics of ecological systems.
Species-time-area relationships: STARs are an ecological pattern describing the combined influence of spatial and temporal scales on species richness. We are interested in statistical/empirical models for characterizing these relationships and in the application of mechanistic models to understanding this scale dependence.
Maximum entropy models: Ecologists have recently begun utilizing the maximum entropy framework from statistical physics to attempt to understand macroecological patterns. Entropy maximization determines the most likely form of a pattern given a small number of limiting constraints. We are interested in testing and expanding these approaches to understand macroecological patterns and processes.