Production and persistence of bacterial and labile organic matter at the hypoxic water–sediment interface of the St. Lawrence Estuary
Bibliographic record
Abstract
Abstract Amino acid (AA) l‐ and d‐enantiomers were quantified in whole seawater samples from the Lower St. Lawrence Estuary (LSLE) and the Gulf of St. Lawrence (GSL). The bottom waters of the LSLE display a recent decrease in dissolved O2 concentrations. Concentrations of AA, including bacterial d‐enantiomers of AA (d‐AA), generally decreased with depth, but sharply increased in the nepheloid layer of the LSLE (not in GSL) with values slightly exceeding those measured in surface waters. The organic matter (OM) in this nepheloid layer was also enriched in AA and d‐AA. Although the particles of the nepheloid layer contributed to less than 13% of total organic carbon (TOC) their contributions to total AA and AA concentration increase were estimated to be almost as important as the dissolved phase. Estimates indicated that bacterial OM represented 67.1–79.4% of TOC in the nepheloid layer of the LSLE, but 18.5–56.9% in the other analyzed waters. All the diagenetic indicators confirmed that the OM just above the sediment in the LSLE was on average less altered than in the rest of the water column or in the GSL. This study suggests that bacteria recycle relatively altered OM into biomass and bacterial dissolved OM near the water–sediment interface in the LSLE. The presence of heterogeneous OM and hypoxic conditions likely reduce OM degradation rate and thus allow for the accumulation of labile OM. Unfavorable conditions for OM degradation might be present in many areas and represent a negative feedback limiting O2 consumption and CO2 production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".