Understanding how natural disturbance regimes drive biodiversity patterns is a major research challenge. Disturbances disrupt local communities by increasing population mortality and alter dispersal between communities. Yet, how species’ ecological strategies and disturbance regimes intertwine to shape the structure of metacommunities across space and time remains poorly understood. Drying river networks (DRNs) exemplify ecosystems structured by natural disturbances: drying events disrupt both local habitat within reaches and connectivity among flowing sections. Drying-wetting cycles thus alter two major mechanisms shaping metacommunity diversity: ecological drift and dispersal dynamics. In this study, we present a mechanistic metacommunity model that simulates species’ ability to withstand drying in place (resistance strategy) and to recolonize communities after rewetting (resilience strategy). Coupling this model with realistic hydrological models, we simulated community dynamics in four European DRNs encompassing variable flow intermittence regimes. Our aim was to investigate the relative importance of flow intermittence, network connectivity and species’ ecological strategies in shaping spatio-temporal biodiversity patterns. We show that higher connectivity increases reach-level α-diversity and decreases reach-level temporal β-diversity, whereas flow intermittence has the opposite effects. At the metacommunity scale, more intermittent DRNs exhibited low mean α-diversity and high spatial β-diversity, while DRNs with downstream drying exhibited high temporal β-diversity. Finally, we show that high levels of species drying resistance and dispersal counteract the effect of flow intermittence, leading to high mean α-diversity and low spatial and temporal β-diversities at the metacommunity scale. In contrast, maximal dispersal distance had complex, non-linear effects on spatial and temporal β-diversities, because dispersal amplifies both community stochasticity and biotic homogenisation. Altogether, our work emphasises how stochastic recolonisation of disturbed communities and biotic homogenisation interact with species resilience and resistance strategies to shape the spatio-temporal structure of biodiversity.

Inferring assembly processes from empirical community diversity patterns has always been a major goal in Ecology. Many empirical studies rely on the "filtering framework", which characterizes community assembly as a sequence of abiotic and biotic filters. The success of the ecological filtering framework lies in its theoretical foundation, linking environmental filtering to niche theory, and competitive interactions to coexistence theory. Empirical studies have provided evidence of environmental filtering in a wide range of environments. However, while competitive interactions are omnipresent, few applications of the filtering framework found significant evidence of competition in real-life settings. Consequently, the framework has been criticised for being overly simplistic. We argue that this unbalanced picture is likely due to specific conceptual challenges. First, many traits are commonly used in empirical work without a clear distinction between traits that capture species responses' to the environment vs. traits that capture the competitive interactions between species, and without consideration of how these two sets of traits may co-vary. Second, it neglects that environmental filter and competition can produce the same traits patterns. Third, the spatial scale at which the community is observed strongly impacts the resulting patterns. Here, we explore these three conceptual challenges and test how trait patterns vary depending on different assembly processes, traits and scales vary. Using a theoretical simulation model, we demonstrate that the trait patterns resulting from environmental filtering and competition respond differently to variations in traits' correlation structure and observation scales. We then identify the actual conditions in which it is possible to distinguish signals of distinct assembly processes from patterns, given the correlation and relevance of traits and the inherent constraints of the observational scale.

Our understanding of how biotic interactions influence animal community assembly is largely restricted to local systems due to the difficulty of obtaining ecologically meaningful assemblage data across large spatial extents. We used a unique dataset of thousands of spatio-phenologically high-resolution assemblages across three distinct European regions together with a functional diversity approach to understand community assembly of dragonflies and damselflies (Odonata), a group characterized by a pronounced competitive reproductive biology. We found that dragonfly, but not damselfly, assemblages were consistently overdispersed in the morphological traits driving inter-specific reproductive encounters, which supports the role of competition. As predicted by ecological theory, support for competition varied spatially and seasonally as a result of changes in temperature stress and niche packing. Our study provides uniquely consistent and general evidence for the role of competition in animal community assembly, and illustrates mechanistically how spatio-temporal diversity patterns arise from variation in assembly processes.