Studies of trait-based plant community dynamics typically rely on null model analyses of functional trait and plot-level composition data from a single growing season. The inclusion of community-level temporal dynamics, however, is vital in investigations of community dynamics as the type and strength of biotic and abiotic filters shaping the structure of plant communities may change through time. Oscillations between filter types may help explain the conflicting findings of previous single-year studies and provide a more accurate picture of how plant communities form and persist. Here, we use multivariate and univariate approaches to determine functional overlap in a long-term herbivore exclusion experiment in Ontario, Canada. We found that functional overlap changed across time without direction, differed between individual traits, was sensitive to herbivory, and differed between pollination systems. Our findings highlight the importance of using long-term data in trait-based community dynamics studies.
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