COS 65-2
Empirical tests of within- and across-species energetics in a diverse plant community: An information entropy approach

Wednesday, August 12, 2015: 8:20 AM
323, Baltimore Convention Center
Erica A. Newman, Energy and Resources Group, University of California, Berkeley, Berkeley, CA
Mark Wilber, Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, Santa Barbara, CA
Natalie Lowell, School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA
Mary Ellen Harte, Rocky Mountain Biological Laboratory, Crested Butte, CO
John Harte, Energy and Resources Group, University of California, Berkeley, CA
Background/Question/Methods

Many fundamental properties of ecological systems and interactions are tied to body size and a related metric, the metabolic rate distribution, both within and across species. A previously proposed maximum entropy theory of ecology (METE) predicts numerous interrelated macroecological patterns, including spatial distributions of individuals within species, abundance distributions across species, species area relationships, and distributions of metabolic rates of all individuals within a community. Extensive tests of METE’s macroecological predictions generally support the theory, but two related predictions have not, until now, been evaluated against full community census data: the distribution of metabolic rates of individuals within species as a function of the abundance of the species and the distribution of average individual metabolic rates across species.

Results/Conclusions

We test the metabolic predictions of METE for herbaceous plants in a subalpine meadow and show that while this theory realistically predicts the distribution of individual metabolic rates across the entire community, the within- and across-species predictions generally fail. We also test the energy-equivalence type prediction that arises as a consequence of the prediction for the distribution of average individual metabolic rates across species. We suggest several possible explanations for the empirical deviations from theory, and distinguish between the expected deviations caused by ecological disturbance and those deviations that might be corrected within the theory.