Transport inventories and exchanges of organic matter throughout the St. Lawrence Estuary continuum (Canada)
Bibliographic record
Abstract
Hypoxia (O 2 < 2 mg/L) driven by eutrophication in estuaries and shelves is a worldwide expanding problem. The role of organic matter (OM) inputs is emerging as an important contributor to this issue, beside the well-known implication of inorganic nutrients. The St. Lawrence Estuary, one of the largest and deepest estuarine system in the world is facing strong persistent and increasing hypoxia. In this context, transport and exchange of particulate and dissolved organic matter (POM and DOM, respectively) were investigated as a first step to understand their implication in hypoxia. Tributaries and Gulf contributions were compared to St. Lawrence Estuary inventories for the spring freshet (May), the summer low-flow (August), and the fall-mixing (October). Furthermore, changes in OM ratios were examined along the estuarine gradient from the upper St. Lawrence Estuary (USLE), downstream of the maximum turbidity zone, to the lower estuary (LSLE). For the USLE, net transport was always positive and net export/loading ratios suggested that 64–90% of POM and 30–63% of DOM were either retained or transformed during its course from tributaries to LSLE. Net transport from the USLE toward the LSLE was 3–13 fold more important in May than in August or October. For the LSLE, net transport to the Gulf was generally negative meaning that OM production was the dominating proces. The extremely high net export/loading ratios in August indicate that POM production was 28.8 to 41.4 times the combined inputs of tributaries and Gulf. Net export/loading ratios remained superior to one during May and October (1.7–9.4) for the LSLE. Changes along the upstream–downstream continuum were seen for POM, with a steady increase relative to total suspended matter from 7.3% to 50.2%, but they were not observed for DOM, for which no obvious trends were detected. Our results highlight the importance of explicitly considering OM in eutrophication monitoring programs of the St. Lawrence Estuary, as the mineralisation of a portion of the large OM pool size could influence our understanding of hypoxia and acidification of the deep waters of LSLE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".