Winter Accumulation of Methane and its Variable Timing of Release from Thermokarst Lakes in Subarctic Peatlands
Bibliographic record
Abstract
Abstract Previous studies of thermokarst lakes have drawn attention to the potential for accumulation of CH 4 under the ice and its subsequent release in spring; however, such observations have not been available for thermokarst waters in carbon‐rich peatlands. Here we undertook a winter profiling of five black‐water lakes located on eroding permafrost peatlands in subarctic Quebec for comparison with summer profiles and used a 2‐year data set of automated water temperature, conductivity, and oxygen measurements to evaluate how the annual mixing dynamics may affect the venting of greenhouse gases to the atmosphere. All of the sampled lakes contained large amounts of dissolved CH 4 under their winter ice cover. These sub‐ice concentrations were up to 5 orders of magnitude above air equilibrium (i.e., the expected concentration in lake water equilibrated with the atmosphere), resulting in calculated emission rates at ice breakup that would be 1–2 orders of magnitude higher than midsummer averages. The amount of CO 2 dissolved in the water column was reduced in winter, and the estimated ratio of potential diffusive CO 2 to CH 4 emission in spring was half the measured summer ratio, suggesting a seasonal shift in methanogenesis and bacterial activity. All surface lake ice contained bubbles of CH 4 and CO 2 , but this amounted to <5% of the total amount of the dissolved CH 4 and CO 2 in the corresponding lake water column. The continuous logging records suggested that lake morphometry may play a role in controlling the timing and extent of CH 4 and CO 2 release from the water column to the atmosphere.
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 | 0.002 | 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) | 0.001 | 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 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".