Research Projects

Circuit theory in ecology, evolution, and conservation
	My NCEAS project involves developing and testing models of landscape connectivity using algorithms borrowed from electronic circuit theory. The algorithms can be used to efficiently predict gene flow in heterogeneous landscapes, and also show promise in predicting animal movement and mortality patterns during dispersal. The models should help researchers and managers predict ecological and evolutionary consequences of landscape change, and identify important habitats for conservation.
More: Using Circuit Theory to Design Connected Landscapes Circuit theory software
Modeling animal population responses to land use and climate change
	At the EPA's Western Ecology Division, I used a dynamic population model to investigate animal responses to landscape and climate change.  I combined output from land use, climate change, and tree growth models with a spatially-explicit and individually-based animal population model to predict trajectories of songbird populations in the Oregon Cascades under alternative future scenarios.
Using DNA to map dispersal barriers and investigate population history
	For my dissertation research at Northern Arizona University, I investigated effects of landscape composition and pattern on genetic connectivity between subpopulations of pumas (Puma concolor) in the southwestern USA.  Pumas in this region are patchily distributed, with a high degree of habitat heterogeneity providing for a wide range of connective habitat configurations between subpopulations.  This unique arrangement of habitats allowed for the development and testing of models of habitat quality, landscape connectivity, and gene flow using genetic data.