eDNA‐Based Temporal Trajectories of Bacterial Communities in Salmon Farm Sediments: Disentangling Seasonal Variability From Aquaculture Impacts

Benthic bacterial communities are increasingly recognized as sensitive indicators of aquaculture impacts, yet disentangling the effects of organic enrichment from natural variability remains a challenge, especially in salmon farming. We leveraged 16S-rRNA V3-V4 eDNA metabarcoding and ecological trajectory analysis across an enrichment gradient and two salmon production cycles, testing how cumulative disturbance and management history affect microbial dynamics. Our analyzes revealed that nutrient enrichment associated with aquaculture was the dominant factor structuring bacterial communities, while seasonal variability exerted only a modest influence. Diversity metrics consistently distinguished impacted from reference sites, with bacterial richness approximately 3.9× higher and Shannon diversity 1.4× higher at the reference site compared to the cage edge. Multivariate analyzes confirmed that organic enrichment explained 59% of the variation in benthic bacterial assemblage composition, surpassing smaller but significant contributions from temperature and production cycle, indicating that seasonal effects do not obscure enrichment-related patterns, including during peak biomass. Trajectory analysis further revealed contrasting temporal dynamics, where reference sites retained variable but resilient assemblages, while cage edge communities stabilized into enrichment-tolerant states with reduced microbial variability. Intermediate sites were most sensitive, shifting from stochastic to directional change in response to altered exposure following farm relocation and longer fallowing. Collectively, we showed that cumulative enrichment not only alters community composition, but also changes how stable and predictable microbial communities are through time. This has critical implications for biomonitoring, as trajectory-based approaches can help build time-aware bacterial indicators that separate natural variability from disturbance, giving managers clearer signals to guide sustainable aquaculture practices.