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Climate change is increasing the frequency of large-scale, extreme environmental events and flattening environmental gradients. Whether such changes will cause spatially synchronous, large-scale population declines depends on mechanisms that limit metapopulation synchrony, thereby promoting rescue effects and stability. Using long-term data and empirical dynamic models, we quantified spatial heterogeneity in density dependence, spatial heterogeneity in environmental responses, and environmental gradients to assess their role in inhibiting synchrony across 36 marine fish and invertebrate species. Overall, spatial heterogeneity in population dynamics was as important as environmental drivers in explaining population variation. This heterogeneity leads to weak synchrony in the California Current Ecosystem, where populations exhibit diverse responses to shared, large-scale environmental change. In contrast, in the Northeast U.S. Shelf Ecosystem, gradients in average environmental conditions among locations, filtered through nonlinear environmental response curves, limit synchrony. Simulations predict that environmental gradients and response diversity will continue to inhibit synchrony even if large-scale environmental extremes become common. However, if environmental gradients weaken, synchrony and periods of large-scale population decline may rise sharply among commercially important species on the Northeast Shelf. Our approach thus allows ecologists to 1) quantify how differences among local communities underpin landscape-scale resilience and 2) identify the kinds of future climatic changes most likely to amplify synchrony and erode species stability. 

ABSTRACT Spatial synchrony, the tendency for temporal fluctuations in an ecological variable to be positively associated in different locations, is a widespread and important phenomenon in ecology. Understanding of the nature and mechanisms of synchrony, and how synchrony is changing, has developed rapidly over the past 2 decades. Many recent developments have taken place through the study of long‐term data sets. Here, we review and synthesise some important recent advances in spatial synchrony, with a focus on how long‐term data have facilitated new understanding. Longer time series do not just facilitate better testing of existing ideas or more precise statistical results; more importantly, they also frequently make possible the expansion of conceptual paradigms. We discuss several such advances in our understanding of synchrony, how long‐term data led to these advances, and how future studies can continue to improve the state of knowledge.