Stable Isotopes Reveal Widespread Anaerobic Methane Oxidation Across Latitude and Peatland Type
Bibliographic record
Abstract
Peatlands are an important source of the atmospheric greenhouse gas methane (CH4). Although CH4 cycling and fluxes have been quantified for many northern peatlands, imprecision in process-based approaches to predicting CH4 emissions suggests that our understanding of underlying processes is incomplete. Microbial anaerobic oxidation of CH4 (AOM) is an important CH4 sink in marine sediments, but AOM has only recently been identified in a few nonmarine systems. We used (13)C isotope tracers and followed the fate of (13)C into CO2 and peat in order to study the geographic extent, relative importance, and biogeochemistry of AOM in 15 North American peatlands spanning a ∼1500 km latitudinal transect that varied in hydrology, vegetation, and soil chemistry. For the first time, we demonstrate that AOM is a widespread and quantitatively important process across many peatland types and that anabolic microbial assimilation of CH4-C occurs. However, AOM rate is not predicted by CH4 production rates and the primary mechanism of C assimilation remains uncertain. AOM rates are higher in fen than bog sites, suggesting electron acceptor constraints on AOM. Nevertheless, AOM rates were not correlated with porewater ion concentrations or stimulated following additions of nitrate, sulfate, or ferric iron, suggesting that an unidentified electron acceptor(s) must drive AOM in peatlands. Globally, we estimate that AOM could consume a large proportion of CH4 produced annually (1.6-49 Tg) and thereby constrain emissions and greenhouse gas forcing.
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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".