Our research synergistically combines theoretical and empirical work to get a deeper understanding of the interactions between ecology and evolution in (mostly) insect and plant systems over different time scales. The common currency of ecology and evolution are birth and death processes. They determine the population growth rate (ecological entity) which is considered an indicator of fitness (evolutionary entity) because it determines gene transmission to future generations. Specifically, we quantify ecological drivers of population dynamics, which are key components of evolutionary landscapes. This knowledge is crucial for predicting immediate population consequences of environmental change such as global climate change as well as for guiding population management. Over longer evolutionary time scales we are interested in assessing what phenotypic traits (life history and behavioral traits) should be associated with a particular evolutionary landscape. One successful approach to this problem is the development of optimization models that assume that natural selection selects for genotypes that maximize their fitness.
The majority of our work spans three broad areas of inquiry.
(1) Plant and insect community dynamics: We use a combination of empirical work and mathematical modeling to understand the effect of anthropogenic activities on plant populations and resulting cascading effects on arthropod community dynamics.
(2) Optimal decisions in behavior and life history: We use mathematical models predicting the effect of biotic and abiotic drivers on the evolution of specific phenotypes.
(3) Applied Ecology: We use a range of mathematical approaches to aid population management.