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Global loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts. 

The relationship between biodiversity and stability, or its inverse, temporal variability, is multidimensional and complex. Temporal variability in aggregate properties, like total biomass or abundance, is typically lower in communities with higher species diversity (i.e., the diversity–stability relationship [DSR]). At broader spatial extents, regional‐scale aggregate variability is also lower with higher regional diversity (in plant systems) and with lower spatial synchrony. However, focusing exclusively on aggregate properties of communities may overlook potentially destabilizing compositional shifts. It is not yet clear how diversity is related to different components of variability across spatial scales, nor whether regional DSRs emerge across a broad range of organisms and ecosystem types. To test these questions, we compiled a large collection of long‐term metacommunity data spanning a wide range of taxonomic groups (e.g., birds, fish, plants, invertebrates) and ecosystem types (e.g., deserts, forests, oceans). We applied a newly developed quantitative framework for jointly analyzing aggregate and compositional variability across scales. We quantified DSRs for composition and aggregate variability in local communities and metacommunities. At the local scale, more diverse communities were less variable, but this effect was stronger for aggregate than compositional properties. We found no stabilizing effect of γ‐diversity on metacommunity variability, but β‐diversity played a strong role in reducing compositional spatial synchrony, which reduced regional variability. Spatial synchrony differed among taxa, suggesting differences in stabilization by spatial processes. However, metacommunity variability was more strongly driven by local variability than by spatial synchrony. Across a broader range of taxa, our results suggest that high γ‐diversity does not consistently stabilize aggregate properties at regional scales without sufficient spatial β‐diversity to reduce spatial synchrony.