Methane in West Siberia terrestrial seeps: Origin, transport, and metabolic pathways of production
Bibliographic record
Abstract
Abstract The expansive plains of West Siberia contain globally significant carbon stocks, with Earth's most extensive peatland complex overlying the world's largest‐known hydrocarbon basin. Numerous terrestrial methane seeps have recently been discovered on this landscape, located along the floodplains of the Ob and Irtysh Rivers in hotspots covering more than 2500 km2. We articulated three hypotheses to explain the origin and migration pathways of methane within these seeps: (H1) uplift of Cretaceous‐aged methane from deep petroleum reservoirs along faults and fractures, (H2) release of Oligocene‐aged methane capped or trapped by degrading permafrost, and (H3) horizontal migration of Holocene‐aged methane from surrounding peatlands. We tested these hypotheses using a range of geochemical tools on gas and water samples extracted from seeps, peatlands, and aquifers across the 120,000 km2 study area. Seep‐gas composition, radiocarbon age, and stable isotope fingerprints favor the peatland hypothesis of seep‐methane origin (H3). Organic matter in raised bogs is the primary source of seep methane, but observed variability in stable isotope composition and concentration suggest production in two divergent biogeochemical settings that support distinct metabolic pathways of methanogenesis. Comparison of these parameters in raised bogs and seeps indicates that the first is bogs, via CO2 reduction methanogenesis. The second setting is likely groundwater, where dissolved organic carbon from bogs is degraded via chemolithotrophic acetogenesis followed by acetate fermentation methanogenesis. Our findings highlight the importance of methane lateral migration in West Siberia's bog‐dominated landscapes via intimate groundwater connections. The same phenomenon could occur in similar landscapes across the boreal‐taiga biome, thereby making groundwater‐fed rivers and springs potent methane sources.
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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 | 0.000 | 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".