Using Traits-based Approaches to Understand the Dynamics of Biodiversity and Productivity
Date and time:
Thursday, February 10, 2011 - 4:30pm
Predicting changes in community composition and ecosystem function in a rapidly changing world is a major research challenge in ecology and evolution. I will discuss a proposed theoretical framework for addressing this challenge comprised of three elements: an underlying trait distribution (e.g., frequency distribution of photosynthetic rate across individuals and species in a community), a performance filter defining the fitness of traits in different environments, and a dynamic projection of the performance filter along some environmental gradient. This framework allows changes in the trait distribution and associated modifications to community composition or ecosystem function to be predicted across time or space. I will discuss analytical results using dynamical systems models within this framework that incorporate 1) migration from a global pool 2) an island model of migration and 3) correlations among traits and environmental drivers. These results help illustrate the underlying assumptions of traits-based models in the ecological literature and describe some biologically counter-intuitive results where lack of optimization (due to correlation) results in a faster evolutionary/ecological response in the trait distribution to environmental changes. Along with this analytical approach, I will also present an application of this framework to predicting species composition changes at Konza prairie using Bayesian hierarchical modeling, which helps to illustrate the difficulties in applying traits-based approaches to empirical data.