CH 4 sink capacity across the geodiversity of Arctic drylands and extreme soils
Bibliographic record
Abstract
Using atmospheric methane (CH4), certain soil microbes are able to sustain their metabolism, and in turn remove this powerful greenhouse gas from the atmosphere. Recent studies have demonstrated the occurrence of CH4 consumption in upland dry tundra soils in Arctic and High Arctic environments. Oxidation of CH4 in these cold, dry soils in the Arctic region can counteract CH4 emissions from Arctic wetlands and thereby play a potential important role for the net Arctic CH4 exchange budget. Currently, knowledge gaps exist on the overall magnitude of the net CH4 sink in these cold, dry systems as the spatial and environmental limits for CH4 oxidation is unknown. In particular, the extent, magnitude and drivers of CH4 oxidation in mountains and alpine landforms, which occupy large land areas in the Arctic and High Arctic has not yet been investigated leaving a potentially vast CH4 sink unquantified with major potential implications for our conceptual view of Arctic CH4 budget in both a past, present and future changing climate. To address this important knowledge gap and identify the most relevant spatial scaling parameters, we studied in situ CH4 net exchange across several large landscape transects in West Greenland as well as in Alpine landscapes in the Yukon Territory, Arctic Canada. The aim of the research was to quantify the variation in flux magnitude and determine the spatial extent of net uptake of atmospheric CH4 across a variety of previously unexplored dry tundra and post-glacial landforms in the Arctic. Our results show a persistent net uptake of CH4 uptake in these dry, extreme environments that rival the sink strength observed in temperate forest soils, otherwise considered the primary global terrestrial sink of atmospheric CH4. Quite surprisingly, we found high CH4 sink rates in conditions when soils were both extremely thin (< 10 cm to bedrock), very dry (< 5-10 % soil moisture), weakly developed and exposed to harsh environmental conditions such as mountain tops, alpine tundra and abrasion plateaus, which are historically overlooked “extreme soils” regarding CH4 exchange. The results show that the physical areas and landforms where CH4 oxidation and net CH4 deposition occurs has not been delimited for the Arctic and calls for further studies of the spatiotemporal nature and occurrence of the CH4 sink across the Arctic.
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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 | 0.000 |
| 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".