Wednesday, August 4, 2010 - 8:40 AM

COS 49-3: New methods in characterizing functional diversity and tests from a grassland biodiversity experiment

Chris M. Clark, US EPA, National Center for Environmental Assessment, Dan F.B. Flynn, Columbia University, Brad J. Butterfield, Arizona State University, and Peter B. Reich, University of Minnesota.

Background/Question/Methods

The concept of functional diversity sits at the intersection of two fields of ecological research, one which examines how community assembly processes (e.g. competition versus habitat filtering) generate functional diversity, and the other which examines the impacts of functional diversity, once generated, on ecosystem processes. Because of this, accurate representations of functional diversity are of paramount importance to the conclusions drawn from a wide variety of research. Several metrics have been developed over the past decade to quantify trait-based functional diversity, however, few incorporate the notion that more abundant species are likely to have a disproportionate effect on ecosystem function (Grime’s “mass ratio hypothesis”). Here we advance two leading functional diversity metrics (the functional dendrogram [FD] and the convex hull volume [CHV]) to incorporate species abundances. We use data from a long-term grassland experiment in Minnesota, USA, to test whether the functional diversity of key traits within the community (specific leaf area, leaf N, root mass fraction) predicts aboveground biomass and light interception.

Results/Conclusions

We found that aboveground biomass was best predicted by abundance-weighted FD. Furthermore, abundance-weighted diversity metrics always outperformed their unweighted counterparts, dendrogram-based diversity metrics always outperformed hulls, and traditional measures of functional diversity (i.e. species richness, functional group richness) performed poorly by comparison. In contrast, for light interception by the plant canopy, traditional measures of functional diversity were superior, and other diversity metrics performed poorly by comparison. Our results suggest that abundance-adjustments greatly enhance predictability for biomass-based ecosystem functions, and that the multi-dimensional distances among all species within a community (i.e. FD) is a better predictor of function than the volume of trait-space circumscribed by extreme species (i.e. CHV). However, each additional species appeared to “fill in” canopies in a way that was roughly independent of trait values explored here, suggesting that canopy architecture more than mass drives light interception. Our research advances functional diversity indices and suggests new directions for research linking biodiversity and ecosystem function.