|Assistant Professor of Environmetrics
(519) 661-2111 x 88205
Ecological systems are complicated -- that is an understatement. Dynamics in an ecosystem result from the combined effects of processes at the individual, population, and community levels that are each affected by many factors, both internal and external. Studying these systems is further complicated by the fact that direct observations of individuals are often impossible or impractical, so that sophisticated methods are needed to extract information about the system from the data that is collected.
I am jointly appointed between the Department of Statistical and Actuarial Science and the Department of Biology, and my research focuses on developing novel statistical methods for the analysis of data from ecological studies and on working with biologists and wildlife scientists to implement these methods in their own research. In particular, I am interested in hierarchical models for ecological data that are fit in a Bayesian framework using advanced Markov chain Monte Carlo Sampling techniques. My primary area of application is in the analysis of data from mark-recapture studies of wild animal populations to study the basic biology of these animals and to understand the effects of human impacts including habitat disturbance and climate change. Specific projects I have worked on include:
I have also worked recently on complex models to identify factors affecting variability in individual behaviours, like parenting behaviour in songbirds and aggressive behaviours in hermit crabs (Bridger, 2015), and on new methods to study changes in a predators preferences for different prey (Roualdes et al., in preparation).