COS 100-8
Testing competition through macro-ecological community data

Thursday, August 13, 2015: 10:30 AM
320, Baltimore Convention Center
Jose A. Capitan, CEAB, Consejo Superior de Investigaciones Cientificas, Blanes, Spain
Sara Cuenda, Economía Cuantitativa, Universidad Autónoma de Madrid, Madrid, Spain
Alejandro Ordonez, Department of Bioscience – Ecoinformatics and Biodiversity, Aarhus University, Aarhus, Denmark
David Alonso, Center for Advanced Studies (CEAB-CSIC), Spanish Council for Scientific Research, Blanes, Spain

Although many processes drive the assembly of ecological communities, competitive interactions are among the best studied. Classical coexistence theory implies that similar species will be displaced through competitive exclusion unless adaptation to different niches takes place. This paradigm has been recently challenged by contemporary coexistence theory [Chesson, 2000; Mayfield and Levine, 2010], which leads to opposing similarity patterns when competition is driven by either species niche differences or competitive ability differences. Accordingly, the empirical evidence for this hypothesis is mixed, and there are a variety of communities and habitats displaying contrasting patterns of competition and species similarity [HilleRisLambers et al., 2012].
Here we report results on the first large-scale study designed to test competition and its relationship with species similarity using plant community data across all the eco-regions found in Europe. Based on a stochastic model of competitive interactions, we have tested model predictions against empirical data. We have used available plant traits to measure, as empirical proxies for competition, either niche differences (using species functional distances in the trait space) or competitive ability differences (as signed trait differences). Competitive interactions have been analyzed separately according to herbaceous and woody growth forms.


First, we tested competition signatures by studying coexistence probability measured as the number of species in local communities relative to metacommunity richness. Regardless of the way competition is quantified (either as niche or competitive ability differences), we do not reject the model for neither herbaceous nor woody interactions. Second, we have conducted randomizations to test species clustering at the local level [Webb et al., 2002]. The model predicts trait over-dispersion or clustering if competition is measured by niche or competitive ability differences, respectively. Although these trends are rejected for woody data when competition is measured by signed trait differences, most herbaceous local communities are compatible with theoretical predictions in the case that competition is quantified by signed trait differences. 
In this contribution we propose a model-based method to elucidate whether competition is a relevant driver of community assembly. Our results support current evidence against the hypothesis that competition can lead to over-dispersion in real species assemblages [Mayfield and Levine, 2010], and, to our knowledge, this is the first study finding a signature of competition at large geographical scales.