Continuous Dynamics of Dissolved Methane Over 2 Years and its Carbon Isotopes (δ<sup>13</sup>C, Δ<sup>14</sup>C) in a Small Arctic Lake in the Mackenzie Delta
Bibliographic record
Abstract
Abstract Seasonally ice‐covered permafrost lakes in the Arctic emit methane to the atmosphere during periods of open‐water. However, processes contributing to methane cycling under‐ice have not been thoroughly addressed despite the potential for significant methane emission to the atmosphere at ice‐out. We studied annual dissolved methane dynamics within a small (0.2 ha) Mackenzie River Delta lake using sensor and water sampling packages that autonomously and continuously collected lake water samples, respectively, for two years at multiple water column depths. Lake physical and biogeochemical properties (temperature; light; concentrations of dissolved oxygen, manganese, iron, and dissolved methane, including stable carbon, and radiocarbon isotopes) revealed annual patterns. Dissolved methane concentrations increase under‐ice after electron acceptors (oxygen, manganese, and iron oxides) are depleted or inaccessible from the water column. The radiocarbon age of dissolved methane suggests a source from recently decomposed carbon as opposed to thawed ancient permafrost. Sources of dissolved methane under‐ice include a diffusive flux from the sediments and may include water column methanogenesis and/or under‐ice hydrodynamic controls. Following ice‐out, the water column only partially mixes allowing half of the winter‐derived dissolved methane to be microbially oxidized. Despite oxidation at depth, surface water was a source of methane to the atmosphere. The greatest diffusive fluxes to the atmosphere occurred following ice‐out (75 mmol CH4 m−2 d−1) and during a mixing episode in mid‐July, likely driven by a storm event. This study demonstrates the importance of fine‐scale temporal sampling to understand dissolved methane processes in seasonally ice‐covered lakes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".