Community size and disturbance history jointly explain the interplay between stochastic and deterministic community variation in benthic invertebrates

Community ecology has so far struggled to integrate both deterministic and stochastic processes into a global model of community variation. To address this issue, we aimed to characterise the ecological conditions that determine the relative importance of deterministic and stochastic community variation in benthic macroinvertebrates. We sampled macroinvertebrate and algal periphyton communities, and microhabitat conditions at monthly intervals over a five year period in two sampling sites in the regulated Durance River and one site in the Asse River (a natural tributary of the Durance). The relative importance of stochastic and deterministic processes was estimated over time as functional and taxonomic spatial β‐deviation (i.e. β‐diversity obs − mean β‐diversity nul l /SD β‐diversity nul l ) for each sampling date and site. We additionally quantified deterministic variation as the trait–environment relationship and predicted a positive correlation with β‐deviation metrics. We found evidence of overdispersal in both functional and taxonomic β‐diversities compared to null expectations. Spatial β‐deviation was highly variable over temporal scales and was jointly explained by invertebrate community size, disturbance (i.e. flooding), periphyton diversity and to a lesser extent, microhabitat diversity. The key factor that explained β‐deviation was recent river discharge (< 90 days), which had a strong negative effect on community size but was also directly associated with higher β‐deviation, likely related to recolonization processes post‐flood. Lastly, we found that when β‐deviation was high, the hydraulic trait–environment relationship was stronger. This indicates that spatial heterogeneity in hydraulic conditions was the main driver of deterministic variation in invertebrate community structure. This study demonstrates that the importance of stochastic processes can vary greatly over short (~ months) and long (~ years) temporal windows with significant consequences for trait–environment relationships. Our study provides an example of how stochastic community variation can be modelled to better interpret deterministic patterns of community structure in natural communities.