The evolution of methane production rates from young to mature thermokarst lakes
Bibliographic record
Abstract
Abstract. Thermokarst lakes, formed by permafrost thaw in the Arctic, are hotspots for methane (CH4) and carbon dioxide (CO2) emissions and are expected to double permafrost carbon emissions by the end of the century. While the implications of ongoing permafrost thaw on CH4 dynamics in these lakes have been modeled, here we provide empirical data on CH4 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 CH4 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 CH4 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 CH4 production rates, likely due to a longer period of organic carbon degradation and reduced carbon lability. The integrated sediment-column CH4 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 CH4 production in newly thawed Yedoma permafrost sediments, while CH4 production will decrease as taliks mature and labile organic carbon is used up.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".