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
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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...
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population modelling & estimation
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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).
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adaptive resource managment
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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 is tackling one or more components of the general ARM framework. Work in this area was and remains intermitent,
since its
hard to get funded (funcding for most science being unrelated to interest or utility...).
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