A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands
Bibliographic record
Abstract
Wetlands are the largest natural source of atmospheric methane. Here, we assess controls on methane flux using a database of approximately 19 000 instantaneous measurements from 71 wetland sites located across subtropical, temperate, and northern high latitude regions. Our analyses confirm general controls on wetland methane emissions from soil temperature, water table, and vegetation, but also show that these relationships are modified depending on wetland type (bog, fen, or swamp), region (subarctic to temperate), and disturbance. Fen methane flux was more sensitive to vegetation and less sensitive to temperature than bog or swamp fluxes. The optimal water table for methane flux was consistently below the peat surface in bogs, close to the peat surface in poor fens, and above the peat surface in rich fens. However, the largest flux in bogs occurred when dry 30-day averaged antecedent conditions were followed by wet conditions, while in fens and swamps, the largest flux occurred when both 30-day averaged antecedent and current conditions were wet. Drained wetlands exhibited distinct characteristics, e.g. the absence of large flux following wet and warm conditions, suggesting that the same functional relationships between methane flux and environmental conditions cannot be used across pristine and disturbed wetlands. Together, our results suggest that water table and temperature are dominant controls on methane flux in pristine bogs and swamps, while other processes, such as vascular transport in pristine fens, have the potential to partially override the effect of these controls in other wetland types. Because wetland types vary in methane emissions and have distinct controls, these ecosystems need to be considered separately to yield reliable estimates of global wetland methane release.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 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".