Functional trait-based approaches have seen rapid development in community ecology and biogeography in recent years, as they promise to offer a better mechanistic and predictive understanding of community structure. However, several key challenges remain. First, while many studies have explored connections between functional traits and abiotic gradients, far fewer have directly tested the common assumption that functional trait differences influence interspecific interactions. Second, empirical studies often ignore intraspecific trait variation within communities, even though intraspecific variation has been known to have substantial impacts on community dynamics. Here we present an experiment designed to assess the role of functional trait differences in predicting the outcome of interspecific species interactions among a suite of California vernal pool annual plants. Eight species were grown in pairwise combinations in two levels of inundation in a greenhouse and functional traits were measured on all individuals. Nested models predicting focal plant performance were fit to the data. For seven of the eight species in the experiment, the best model included a functional trait difference term that was consistent with a competitive hierarchy, indicating that focal species tended to do better when they had larger leaf size, lower specific leaf area, and greater investment in lateral canopy spread than their neighbors. Models that included individually measured trait values generally performed better than models using species trait averages. We tested if the same trait measurements predicted tolerance of inundation (a feature of vernal pool habitats), and species depth distributions from extensive field surveys, though we did not find strong relationships. Our results suggest that functional traits can be used to make inferences about the outcome of interspecific interactions, and that greater predictive power can come from considering intraspecific variation in functional traits, particularly in low diversity communities.