Mechanisms of convergence and divergence: understanding the variability of plant community responses to multiple resource manipulations

Introduction and Goals Ecologists have been tasked with predicting how communities will respond to altered environmental conditions in the face of global change. This task, however, is complicated by the inherent complexity of many ecological systems. Indeed, within a system the species composition of experimental replicates does not always respond to resource manipulations in similar ways; instead replicates can diverge to form distinct alternative community types. An understanding of the processes leading to such divergence is currently lacking. We are requesting LTER funding to form a working group to address the following questions: 1) what mechanisms lead to plant community convergence/divergence in response to resource manipulations; 2) do these same patterns hold for plant traits, i.e., do traits converge or diverge in response to resource manipulations; and 3) what are the consequences of community convergence/divergence for ecosystem stability? In order to address these questions we propose to first build a conceptual framework and then to test our proposed hypotheses by analyzing resource manipulation experiments from the LTER network. The products of our working group will include at least two publications. First, we aim to publish our conceptual model as either an Ecology Letters Ideas & Perspective or Ecology Forum piece. Although we are proposing to work with only terrestrial plant community ecologists, we expect our framework to be applicable to most ecological systems. Second, we expect the results of the test of our hypothesis with LTER datasets to be suitable for journals such as PNAS or Ecology Letters. In addition to fostering new collaboration, our working group includes two graduate students and two early career postdoctoral researchers, for whom participation in a working group is a valuable experience.
Principal Investigator: 
Meghan Avolio
Competition Date: 
2012, October
Award Date: 
2012, November
Award Year: 
2013
Award Amount: 
$13,744