Characterization of atmospheric methane release at hotspots in the outer Mackenzie River Delta
Bibliographic record
Abstract
Spatio-temporal patterns of methane (CH4) and carbon dioxide (CO2) release from natural sources needs to be better understood across the Arctic region. Climate change in the Arctic is occurring at a pace that may be 2 to 4 times the global average, and existing measurements derive from a limited number of field sites, and most originate during the growing season although important studies show that release continues during winter. The Mackenzie River Delta in the western Canadian Arctic holds thin and destabilizing permafrost, high organic content soils, a high proportion of wetlands, and vast natural gas occurrences at depth, all of which create high methane potential. In the present study, we conducted atmospheric CH4 and CO2 measurements using a mobile laboratory equipped with a greenhouse gas analyzer during the summer and winter. We also visited known aquatic and terrestrial CH4 flux hotspots, including pingos, lakes, river channels and wetlands, where we measured concentration transects and stable carbon isotope (13C-CH4) values to characterize CH4source and spatial pattern. Source stable carbon isotope (δ13C-CH4) signatures at hotspots ranged from -42 to -88 ‰ δ13C-CH4. Active surface microbial production was responsible for at least 4 of the 8 hotspots investigated, indicating that microbial production may be responsible for a greater number of CH4 hotspots than is indicated by previous studies in the region. Mobile surveys showed that shrubland, grassland and deep water were the most important ecosystems for CH4 and CO2 production during the wintertime and that low lying areas of the Delta had the highest atmospheric mixing ratios of CH4.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".