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 time. Although this theory has experimental support, 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) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series 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.

Environmental DNA (eDNA) metabarcoding has emerged as a potentially powerful tool to assess aquatic community structures. However, the method has hitherto lacked field tests that evaluate its effectiveness and practical properties as a biodiversity monitoring tool. Here, we evaluated the ability of eDNA metabarcoding to reveal fish community structures in species-rich coastal waters. High-performance fish-universal primers and systematic spatial water sampling at 47 stations covering ~11 km2 revealed the fish community structure at a species resolution. The eDNA metabarcoding based on a 6-h collection of water samples detected 128 fish species, of which 62.5% (40 species) were also observed by underwater visual censuses conducted over a 14-year period. This method also detected other local fishes (≥23 species) that were not observed by the visual censuses. These eDNA metabarcoding features will enhance marine ecosystem-related research, and the method will potentially become a standard tool for surveying fish communities.

Environmental DNA (eDNA) analysis has successfully detected organisms in various aquatic environments. However, there is little basic information on eDNA, including the eDNA shedding and degradation processes. This study focused on water temperature and fish biomass and showed that eDNA shedding, degradation, and size distribution varied depending on water temperature and fish biomass. The tank experiments consisted of four temperature levels and three fish biomass levels. The total eDNA and size‐fractioned eDNA from Japanese Jack Mackerels (Trachurus japonicus) were quantified before and after removing the fish. The results showed that the eDNA shedding rate increased at higher water temperature and larger fish biomass, and the eDNA decay rate also increased at higher temperature and fish biomass. In addition, the small‐sized eDNA fractions were proportionally larger at higher temperatures, and these proportions varied among fish biomass. After removing the fish from the tanks, the percentage of eDNA temporally decreased when the eDNA size fraction was >10 µm, while the smaller size fractions increased. These results have the potential to make the use of eDNA analysis more widespread in the future.