Research Interests                                                        Evan P. Economo

Biodiversity dynamics in structured landscapes:  I'm interested in the consequences of complex landscape structure for biodiversity dynamics.  I'm particularly interested in developing theory which merges ecological processes such as metapopulation dynamics with evolutionary processes such as genetic differentiation and speciation.  This provides a framework for understanding biodiversity patterns as an outcome of biological processes operating on a hierarchy of space and time scales.  Recently I have been focused on using network theory to represent spatial metacommunity structure, and build biodiversity models such as neutral theory onto this framework (Economo & Keitt, 2008). Ant ecology, evolution, and biogeography:   Ants are among the most fascinating organisms on the planet, and I am interested in all aspects of their biology.  With my collaborator, Eli Sarnat, I have been leading a comprehensive ant biodiversity inventory in the Fijian archipelago.  The initial stages of this project are to describe the diversity of ants in Fiji, develop a broad geographic dataset from communities across the archipelago.  We will to use this data to understand how local ecological controls on diversity, such as environmental gradients, human disturbance, and invasion of exotics, interact with evolutionary processes such as speciation and niche evolution, in determining the structure of ant communities.  These insular ecosystems are embedded in a vast network of communities, the greater Pacific islands metacommunity, which have the potential to be a model system for testing ideas in biodiversity theory. www.fijiants.org                                                                                      For the Fiji antweb page, see:

www.antweb.org/fiji.jsp

Scaling of ecological and evolutionary processes:  Scaling approaches seek to understand how biological processes change across scales of space and time, and with the basic dimensions of life; the body sizes and temperatures of organisms.   My research in this area uses metabolic theory to build models on the population and ecosystem scales.  This approach was applied to a global dataset of whole ecosystem energy dissipation, as measured by CO2 exchange.  Interestingly, the whole ecosystem temperature dependence of energy dissipation was governed by the same mathematical functions as individual organisms, but the parameters changed across geographic space in such a way that the effect of temperature was moderated (Enquist et al. 2003).  More recent work integrates life history theory with metabolic theory in order to predict population level rates of energy flow, biomass production, and trophic efficiency (Economo et al. 2005).

 

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