Enrichment in <sup>13</sup> C of atmospheric CH <sub>4</sub> during the Younger Dryas termination
Bibliographic record
Abstract
Abstract. The abrupt warming across the Younger Dryas termination (~11 600 yr before present) was marked by a large increase in the global atmospheric methane mixing ratio. The debate over sources responsible for the rise in methane centers on the roles of global wetlands, marine gas hydrates, and thermokarst lakes. We present a new, higher-precision methane stable carbon isotope ratio (δ13CH4) dataset from ice sampled at Påkitsoq, Greenland that shows distinct 13C-enrichment associated with this rise. We investigate the validity of this finding in face of known anomalous methane concentrations that occur at Påkitsoq. Comparison with previously published datasets to determine the robustness of our results indicates a similar trend in ice from both an Antarctic ice core and previously published Påkitsoq data measured using four different extraction and analytical techniques. The δ13CH4 trend suggests that 13C-enriched CH4 sources played an important role in the concentration increase. In a first attempt at quantifying the various contributions from our data, we apply a methane triple mass balance of stable carbon and hydrogen isotope ratios and radiocarbon. The mass balance results suggest biomass burning (42–66% of total methane flux increase) and thermokarst lakes (27–59%) as the dominant contributing sources. Given the high uncertainty and low temporal resolution of the 14CH4 dataset used in the triple mass balance, we also performed a mass balance test using just δ13C and δD. These results further support biomass burning as a dominant source, but do not allow distinguishing of thermokarst lake contributions from boreal wetlands, aerobic plant methane, or termites. Our results in both mass balance tests do not suggest as large a role for tropical wetlands or marine gas hydrates as commonly proposed.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".