Methane ebullition and diffusion from northern ponds and lakes regulated by the interaction between temperature and system productivity
Bibliographic record
Abstract
Abstract Methane (CH 4 ) emissions from aquatic systems should be coupled to CH 4 production, and thus a temperature‐dependent process, yet recent evidence suggests that modeling CH 4 emissions may be more complex due to the biotic and abiotic processes influencing emissions. We studied the magnitude and regulation of two CH 4 pathways—ebullition and diffusion—from 10 shallow ponds and 3 lakes in Québec. Ebullitive fluxes in ponds averaged 4.6 ± 4.1 mmol CH 4 m −2 d −1 , contributing ∼56% to total (diffusive + ebullitive) CH 4 emissions. In lakes, ebullition only occurred in waters < 3 m deep, averaging 1.1 ± 1.5 mmol CH 4 m −2 d −1 , and when integrated over the whole lake, contributed only 18% to 22% to total CH 4 emissions. While pond CH 4 fluxes were related to sediment temperature, with ebullition having a stronger dependence than diffusion (Q 10 , 13 vs. 10; activation energies, 168 kJ mol −1 vs. 151 kJ mol −1 ), the temperature dependency of CH 4 fluxes from lakes was absent. Combining data from ponds and lakes shows that the temperature dependency of CH 4 diffusion and ebullition is strongly modulated by system trophic status (as total phosphorus), suggesting that organic substrate limitation dampens the influence of temperature on CH 4 fluxes from oligotrophic systems. Furthermore, a strong phosphorus‐temperature interaction determines the dominant emission pathway, with ebullition disproportionately enhanced. Our results suggest that aquatic CH 4 ebullition is regulated by the interaction between ecosystem productivity and climate, and will constitute an increasingly important component of carbon emissions from northern aquatic systems under climate and environmental change.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".