Atmospheric <scp>CH</scp><sub>4</sub> oxidation by Arctic permafrost and mineral cryosols as a function of water saturation and temperature
Bibliographic record
Abstract
Abstract The response of methanotrophic bacteria capable of oxidizing atmospheric CH4 to climate warming is poorly understood, especially for those present in Arctic mineral cryosols. The atmospheric CH4 oxidation rates were measured in microcosms incubated at 4 °C and 10 °C along a 1‐m depth profile and over a range of water saturation conditions for mineral cryosols containing type I and type II methanotrophs from Axel Heiberg Island (AHI), Nunavut, Canada. The cryosols exhibited net consumption of ~2 ppmv CH4 under all conditions, including during anaerobic incubations. Methane oxidation rates increased with temperature and decreased with increasing water saturation and depth, exhibiting the highest rates at 10 °C and 33% saturation at 5 cm depth (260 ± 60 pmol CH4 gdw−1 d−1). Extrapolation of the CH4 oxidation rates to the field yields net CH4 uptake fluxes ranging from 11 to 73 μmol CH4 m−2 d−1, which are comparable to field measurements. Stable isotope mass balance indicates ~50% of the oxidized CH4 is incorporated into the biomass regardless of temperature or saturation. Future atmospheric CH4 uptake rates at AHI with increasing temperatures will be determined by the interplay of increasing CH4 oxidation rates vs. water saturation and the depth to the water table during summer thaw.
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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) | 0.001 | 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".