research

My research interests 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'm involved with. More specific details on these projects, and other things I'm working on, can be gleaned by looking at my publications.

disease modelling

phone I am a collaborator on a large NSF-funded project exploring the disease ecology and dynamics of Mycoplasma infection in the common house finch. This study involves a combination of lab, field (including captive birds) and 'conceptual' (mathematical and statistical) research. Our main focus to date has been 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.

population modelling & estimation

phone An overarching theme for a lot of my work is based on the premise that robust 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. I am 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.

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 am part of a large collaborative group that is tackling one or more components of the general ARM framework.