The evolution of methane production rates from young to mature thermokarst lakes
Bibliographic record
Abstract
Thermokarst lakes, formed by permafrost thaw in the Arctic, are hotspots for methane (CH 4 ) and carbon dioxide (CO 2 ) emissions and are expected to double permafrost carbon emissions by the end of the century. While the implications of ongoing permafrost thaw on CH 4 dynamics in these lakes have been modeled, here we provide empirical data on CH 4 production dynamics as lakes evolve from young recently formed lakes to older lakes that have been present for hundreds of years. Sediment cores (up to 4 m long) were collected from the centers and thermokarst margins of a new thermokarst lake (Big Trail Lake (BTL), < 70 years old) and from an older thermokarst lake (Goldstream Lake (GSL), ∼ 900 years old) from the same interior Alaskan watershed. The highest CH 4 production rates were observed in the uppermost sediments near the sediment–water interface at the thermokarst margins of both lakes, with a steep decrease with sediment depth into the talik. BTL exhibited elevated CH 4 production rates, correlated with higher carbon lability for thermal-induced reactions measured by Rock-Eval analyses, suggesting its potential use as a proxy for organic carbon breakdown by methanogenesis. In contrast, GSL displayed lower CH 4 production rates, likely due to a longer period of organic carbon degradation and reduced carbon lability. The integrated sediment-column CH 4 production rates were similar (around 7 to 10 mol m −2 yr −1 ), primarily due to the thinner talik at BTL. Our data support the predictions that the formation and expansion of thermokarst lakes over the next centuries will increase CH 4 production in newly thawed Yedoma permafrost sediments, while CH 4 production will decrease as taliks mature and labile organic carbon is used up.
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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 | 0.001 | 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) | 0.001 | 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".