Abstract

AbstractQuestionPlant community dynamics are influenced by microvariations of the environment and of processes acting at fine spatio‐temporal scales like plant–plant interactions, local dispersal and phenology. However, descriptions and understanding of diversity changes both within year and over short distances are still required. We used a dynamic metacommunity framework to answer the following question: what is the relative influence of environmental filtering, dispersal limitation and ecological drift on fine‐scale grassland community dynamics under different disturbance regimes?LocationData were collected in a long‐term experiment located in the Massif Central, France (45°43′23″ N, 03°1′21″ E, 880 m a.s.l.).MethodsWe monitored fine‐scale spatio‐temporal community changes in small plots (i.e. local communities) distributed within six grassland paddocks (i.e. metacommunities) subject to two treatments (mown or grazed). We simultaneously monitored three key environmental variables: light, nitrogen and water, to assess how environmental heterogeneity impacts species compositional changes. We then inferred the metacommunity drivers of these changes in taxonomic and functional composition using a path analysis.ResultsManaged grasslands are dynamic within a year, and spatially heterogeneous within a paddock, with spatial and temporal β diversities totalling more than half of the taxonomic diversity. Mowing events caused sudden decreases of total vegetation cover resulting in taxonomical and functional changes. In grazed paddocks, community changes were mainly spatial due to spatially heterogeneous light‐structured filtering conditions. In both treatments, environmental heterogeneity only partially explained community changes that were also greatly impacted by dispersal limitation, but not ecological drift.ConclusionsOur study demonstrates that the fine‐scale analysis of community spatio‐temporal changes allows disentangling the relative importance of environmental filtering, dispersal limitation and ecological drift in community dynamics. Applying this approach to communities experiencing other kinds of disturbance regimes may allow gaining a general understanding of plant community assembly processes.

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