Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time1,2,3. Although this theory has experimental support2,4,5, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time)6 and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series6,7,8,9 and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.
We thank members of the Kondoh laboratory in Ryukoku University; F. Grziwotz, A. Telschow and T. Miki for discussions; S.-I. Nakayama for advice on the twin surrogate method; and T. Yoshida and M. Kasada for providing time series of the algae–rotifer system. This research was supported by CREST, grant number JPMJCR13A2, Japan Science and Technology Agency; KAKENHI grant number 15K14610 and 16H04846, Japan Society for the Promotion of Science; Foundation for the Advancement of Outstanding Scholarship (Ministry of Science and Technology, Taiwan); DoD-Strategic Environmental Research and Development Program 15 RC-2509; Lenfest Ocean Program 00028335; NSF DBI-1667584; NSF DEB-1655203; the McQuown Fund and the McQuown Chair in Natural Sciences (University of California, San Diego).