Carbon dioxide and methane emissions from the Yukon River system
Bibliographic record
Abstract
Carbon dioxide (CO 2 ) and methane (CH 4 ) emissions are important, but poorly quantified, components of riverine carbon (C) budgets. This is largely because the data needed for gas flux calculations are sparse and are spatially and temporally variable. Additionally, the importance of C gas emissions relative to lateral C exports is not well known because gaseous and aqueous fluxes are not commonly measured on the same rivers. We couple measurements of aqueous CO 2 and CH 4 partial pressures ( p CO 2 , p CH 4 ) and flux across the water‐air interface with gas transfer models to calculate subbasin distributions of gas flux density. We then combine those flux densities with remote and direct observations of stream and river water surface area and ice duration, to calculate C gas emissions from flowing waters throughout the Yukon River basin. CO 2 emissions were 7.68 Tg C yr −1 (95% CI: 5.84 −10.46), averaging 750 g C m −2 yr −1 normalized to water surface area, and 9.0 g C m −2 yr −1 normalized to river basin area. River CH 4 emissions totaled 55 Gg C yr −1 or 0.7% of the total mass of C emitted as CO 2 plus CH 4 and ∼6.4% of their combined radiative forcing. When combined with lateral inorganic plus organic C exports to below head of tide, C gas emissions comprised 50% of total C exported by the Yukon River and its tributaries. River CO 2 and CH 4 derive from multiple sources, including groundwater, surface water runoff, carbonate equilibrium reactions, and benthic and water column microbial processing of organic C. The exact role of each of these processes is not yet quantified in the overall river C budget.
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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 | 0.001 | 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".