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
- 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
- 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.
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
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
adaptive resource managment
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.