Dissolved Methane in the World's Largest Semi‐Enclosed Estuarine System: The Estuary and Gulf of St. Lawrence (Canada)
Bibliographic record
Abstract
Abstract We report the first water‐column dissolved methane data set from the Estuary and Gulf of St. Lawrence (EGSL). Per surface‐water methane concentration and sea‐to‐air flux, the upper estuary behaved like a typical shallow macrotidal estuary, while the lower estuary and the gulf resembled outer shelf seas and ocean slopes, respectively. The EGSL emitted 166.3 (71.5–214.4) × 106 mol CH4 year−1 to the atmosphere, representing 0.3% (0.1%–0.4%) of the total emission from global estuarine environments. A net production of 11.7 × 107 mol CH4 year−1 was required to sustain this emission. Methane distributions in the upper estuary were dominated by physical mixing, while those in the lower estuary and the gulf bore characteristic subsurface maxima and deep minima shedding light on the methane consumption and production pathways. Elevated but highly variable near‐bottom methane concentrations (10.4–695.3 nmol L−1) transpired over pockmarks on the seabed of the lower estuary, inferring an upward diffusive flux of up to ∼700 mmol CH4 m2 d−1. Hypoxia in the lower estuary bottom water had little influence on methane concentrations. Lab incubations yielded methane cycling rates from a net production of 0.0068 nmol L−1 d−1 to net consumption with turnover times of 33.3–263 days. Methane in the EGSL was isotopically enriched with 13C (δ13CCH4: −40.9‰ to −27.4‰ relative to Peedee Belemnite). This study reveals that the EGSL is a smaller proportional contributor to methane emission from estuarine environments and that complex physical‐biogeochemical interactions control methane cycling and isotopic composition in this vast estuarine system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".