The net exchange of methane with high Arctic landscapes during the summer growing season
Bibliographic record
Abstract
Abstract. High Arctic landscapes are essentially vast cold deserts interspersed with streams, ponds and wetlands. These landscapes may be important consumers and sources of the greenhouse gas methane (CH4), though few measurements exist from this region. To quantify the flux of CH4 (FCH4) between the atmosphere and high Arctic landscapes on northern Ellesmere Island, Canada, we made static chamber measurements over five and three growing seasons at a desert and wetland, respectively, and eddy covariance (EC) measurements at a wetland in 2012. Chamber measurements revealed that, during the growing season, desert soils consumed CH4 (−1.37 ± 0.06 mg-CH4 m−2 d−1), whereas the wetland margin emitted CH4 (+0.22 ± 0.14 mg-CH4 m−2 d−1). Desert CH4 consumption rates were positively associated with soil temperature among years, and were similar to temperate locations, likely because of suitable landscape conditions for soil gas diffusion. Wetland FCH4 varied closely with stream discharge entering the wetland and hence extent of soil saturation. Landscape-scale FCH4 measured by EC was +1.27 ± 0.18 mg-CH4 m−2 d−1 and varied with soil temperature and carbon dioxide flux. FCH4 measured using EC was higher than using chambers because EC measurements incorporated a larger, more saturated footprint of the wetland. Using EC FCH4 and quantifying the mass of CH4 entering and exiting the wetland in stream water, we determined that methanogenesis within wetland soils was the dominant source of FCH4. Low FCH4 at the wetland was likely due to a shallow organic soil layer, and thus limited carbon resources for methanogens. Considering the prevalence of dry soils in the high Arctic, our results suggest that these landscapes cannot be overlooked as important consumers of atmospheric CH4.
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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 | 0.001 | 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 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".