My research interests have tended to focus on 4 major themes:

  • the response of populations and ecological communities to environmental change, and the evolutionary and ecological consequences of these responses
  • the relationship of increasing habitat fragmentation on population dynamics, particularly in terms of linking empirical and theoretical work on the dynamics of subdivided populations
  • the development and application of novel and robust analytical and modeling techniques
  • can we use these approaches to better characterize and quantify the uncertainty in natural systems, and use this information to make more informed management and conservation decisions

The following is a very brief summary of some of the more major research initiatives I was involved with (past tense -- these days, I do more teaching than research). More specific details on those projects, and other things I've worked on at various times, can be gleaned by looking at my publications.

disease modelling

phone I was a collaborator on a large NSF-funded project exploring the disease ecology and dynamics of Mycoplasma infection in the common house finch. This study involved a combination of lab, field (including captive birds) and 'conceptual' (mathematical and statistical) research. The primary objective was to provide as complete an understanding of the hierarchy of factors contributing to variation in the prevalence of Mycoplasma in finch populations at a variety of spatial and temporal scales. Many neat results. I eventually jumped ship when the project 'went molecular'. Not my bag...

population modelling & estimation

phone An overarching theme for a lot of my work was based on the premise that meaningful testing of evolutionary and ecological theory is ultimately limited by our ability to robustly estimate various parameters using empircal data, and deriving 'reasonable' models for complex system. At various times I have been involved in a number of areas of research on areas of mark-recapture estimation, matrix modelling, and some newer areas of the application of Bayesian inference to estimate 'difficult' parameters. Since its impossible to keep up with the smart folks on the 'development' side of things, I now spend most of my efforts in this area explaining the 'new stuff' to the 'less smart folks' (like me).

adaptive resource managment

phone Management of any dynamic system is complicated by the presence of one or more sources of uncertainty (observation uncertainty, structural uncertainty, imperfect control...). Making optimal decisions under uncertainty, while simultaneously taking steps to reduce it, is the basis for ARM. I was part of a large collaborative group that focussed on one or more components of the general ARM framework. Work in this area was and remains intermitent, since its hard to get funded (funding for most science being unrelated to interest or utility...).