The Extent and Regulation of Summer Methane Oxidation in Northern Lakes
Bibliographic record
Abstract
Abstract Inland waters have a significant influence on atmospheric methane (CH 4 ) levels. However, processes determining the strength of CH 4 emissions from these systems are not well defined. Aerobic oxidation is a major sink of CH 4 in freshwater environments and thus an important determinant of aquatic CH 4 emissions, yet strikingly little is known about its drivers. Here we assessed the extent of water column CH 4 oxidation at the whole ecosystem scale using stable carbon isotopic (δ 13 C) mass balance of CH 4 in 14 northern lakes spanning wide range of dissolved organic carbon (DOC) concentrations. We show that the extent of oxidation can vary from near zero to near complete, and for concentrations of 1.9–11 mg/L, DOC is a key modulator of CH 4 oxidation during the summer stratification period. Increasing DOC concentrations enhances oxidation in the upper layers by reducing light inhibition on methanotrophic activity, while reducing oxygen available for oxidation in the deeper layers. The effect of this light inhibition was also observable over the diurnal cycle. We developed simple predictive empirical models ( r 2 > 0.82) to estimate the extent of oxidation in the different layers of lakes for the summer period. Applying our surface layer model to a larger data set suggests that about 30% of CH 4 transported to or generated within the epilimnion of Québec lakes is oxidized during summer. Our results imply that DOC concentration, through its effect on the light regime of lakes, has the potential to affect strongly the magnitude and patterns of summer CH 4 emissions.
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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 | 0.000 | 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".