My 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, I 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 and introductions of novel species as well as for designing effective population management strategies. Over longer evolutionary time scales I am 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.
My work spans three broad areas of inquiry.
(1) Insect and plant demography: I use stage structured population models to identify key factors shaping population dynamics. Since environmental drivers can vary in space and time I also explore how spatio-temporal dynamics influence life-history evolution and species persistence.
(2) Optimal decisions in behavior and life history: I use mathematical models predicting ultimate causes for the evolution of specific phenotypes.
(3) Population management: I use a range of mathematical approaches to evaluate management strategies.