COS 152-8 - The ecology of differences: Integrating trait and evolutionary distances

Thursday, August 9, 2012: 4:00 PM
F151, Oregon Convention Center
Marc W. Cadotte, Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada, Steven C. Walker, Department of Mathematics & Statistics, McMaster University, Hamilton, ON, Canada and Cécile H. Albert, Biology, McGill University, Montreal, QC, Canada
Background/Question/Methods

Community ecology has gone through a paradigm shift. Classic work sought to explain patterns of diversity in terms of the numbers and distribution of species. Responding to calls to protect biodiversity in the 1990’s, research used this species approach to determine the potential consequences of diversity change and extinction. Biodiversity has always been defined as the variation in life at all levels, from genomes to ecosystems, and ecologists are increasingly measuring biodiversity in a multitude of different ways to account for similarities and differences among species. Two rapidly expanding ways to quantify species differences are to use phylogenetic or trait-based distances. Both approaches have limitations, prompting the need to consider both sources of information, yet there has been little integration. We will present a new method to integrate distance-based approaches that quantifies species differences by both phylogenetic distances and quantitative traits. This approach incorporates the contribution of both unmeasured traits that evolve through time and convergence and divergence of measured traits, in a weighted metric. By accounting for trait and phylogenetic contributions to ecological patterns, we can reassess basic ecological hypotheses.

Results/Conclusions

We examine two phenomena that distance-based measures are employed. 1) The explanation of causes of ecological patterns. Here we show that patterns of community assembly are explained by both trait distances and evolutionary divergences, allowing for a more comprehensive explanation of how species assemble across environmental gradients; 2) The consequences of diversity. Here we re-analyze experiments that manipulate diversity and measure ecosystem function and show that optimal explanatory power results from a combination of traits and phylogeny. By accounting for trait divergence and convergence, we can better explain ecological phenomena that depend on unique niche and function contributions.