Cyrille Violle1, Anne Bonis2, Manuel Plantegenest3, Christophe Cudennec3, Christian Damgaard4, Benoît Marion2, Didier Le Coeur3, and Jan-Bernard Bouzillé2. (1) University of Arizona, (2) University of Rennes, (3) INRA-Agrocampus Rennes, (4) University of Aarhus
Background/Question/Methods Predicting species coexistence remains a major challenge of ecologists, despite recent fruitful theoretical studies. Plant functional traits could both explain abiotic and biotic filtering processes of species diversity and should therefore constitute relevant tools to understand and predict species assemblages. Trait-based approaches for understanding biodiversity patterns remain to be empirically tested however, since species interactions were not explicitly taken into account by the few existing studies despite their huge importance in structuring plant communities. A promising method to understand environmental filtering processes is to analyse changes in community-aggregated traits along a given gradient. Here we coupled this method with species distribution modelling to predict species number within plant communities from plant traits through quantifying the main abiotic and biotic mechanisms shaping species coexistence. Local plant communities were sampled in a 4-ha flood meadow, characterized by microtopographic variations in elevation and consequently by a large flooding gradient extending from no flooding to several months of flooding.
Results/Conclusions We successfully predicted species distribution and species diversity within local plant assemblages located along the flooding gradient, from plant traits, specific leaf area and plant height, significantly linked to abiotic and competitive filtering processes respectively. Diversity-disturbance pattern sustained the Intermediate-Disturbance Hypothesis and was explained by plant response to abiotic constraints only. At the community scale, species interactions were the most important driving factor for biodiversity by reducing the dimension of the realized community -species number per se-. Our results give strong empirical evidence and a promising quantification of biodiversity filtering by both abiotic and competitive forces at local scales. More broadly, such trait-community approach provides new insights into the underlying mechanisms of species coexistence and biodiversity patterns.
