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Active non-redundancy and viral orchestration sustain diel microbial successions in the coastal ocean

Preprint Created on 23 Jun 2026 bioRxiv

Ecosystem resilience in dynamic coastal oceans is conventionally ascribed to functional redundancy, where taxonomically distinct microbes buffer environmental fluctuations through interchangeable metabolic roles. In this study, we reveal a deterministic succession architecture sustained by active non redundancy and temporal metabolic coupling, uncovered via autonomous drone array metatranscriptomic sampling in Daya Bay, China. By resolving the transcriptional landscape into six chronometrically phased modules rather than simple time points, we demonstrate a near total renewal of the active gene pool, with greater than 90% of transcribed clusters showing phase exclusivity within approximatively a two-hour window. This radical functional reshaping exposes a tight, scale dependent taxonomic functional coupling where community composition is a strong, linear predictor of metabolic output, peaking at the genus level (p < 0.0001). Functional continuity is maintained not by redundant generalists, but by a precisely sequential relay of specialists, each optimized for transient microniches with minimal overlap between successive phases. Deep learning structural adjudication of the psbA gene pool further reveals viral orchestration of this temporal coupling, where incoming cyanophages introduce structurally distinct protein variants that sustain photosynthetic electron flow under peak irradiance. These findings redefine coastal microbiome stability as a fine-tuned rapid succession of temporal specialists rather than a redundant backdrop. We propose a fundamental revision of marine ecosystem models, shifting from passive buffering frameworks to deterministic, clock driven architectures, which may prove to be critical for forecasting microbiome responses to accelerating short term climate variability.

Pereira, O., Ottesen, E. A., DePoy, A. N., Ramond, P., Chen, S., Ji, F., Hou, S., Jiao, N., Zhang, C.

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