Time-series analysis identifies microbial community shifts in a reservoir, indicating impacts on water quality management.
Large reservoirs are human-managed ecosystems where microbial communities play pivotal roles in nutrient cycling and ecological stability. However, the mechanisms underlying microbial multistability and stress-induced functional shifts remain inadequately understood. Here, we employed a one-year high-resolution time-series 16S rRNA gene amplicon high-throughput sequencing dataset from the Danjiangkou Reservoir(China) to characterize the alternative stable states(ASS) of microbial communities. Two distinct ASSs were identified: State A, dominated by Cyanobacteria and Actinobacteriota, is characterized by higher alpha diversity, strong local connectivity, and phototrophy-driven energy acquisition. In contrast, State B, dominated by Bacteroidota and Proteobacteria, exhibits enhanced network modularity and functional resilience, supported by robust nitrogen and carbon cycling. Dissolved oxygen, temperature, and ammonia nitrogen were identified as the key environmental stressors regulating state transitions, with distinct thresholds and hysteresis phenomena elucidated via stability-landscape analysis. Functional prediction and structural equation modeling further confirmed that environmental stress reorganizes microbial metabolism pathways from light-dependent processes to nitrogen-cycling- dominated processes, which is mediated by alterations in microbial diversity and network stability. Collectively, these findings provide critical empirical evidence for microbial multistability and stress-driven regime shifts in large reservoirs. This work thereby informs adaptive water quality management strategies for large drinking water reservoirs, pivotal for mitigating nutrient pollution, safeguarding water security, and promoting sustainable freshwater ecosystem management. • Time-series revealed two stable states of prokaryotic communities in Danjiangkou Reservoir. • Temperature, oxygen, and ammonia nitrogen were stressors driving nonlinear shifts. • Network topology and diversity jointly regulated community resilience and stability. • Function shifted from light-driven metabolism to nitrogen cycling under high stress.
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Lyu et al. (2026) studied this question.
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