Yukon River incision drove organic carbon burial in the Bering Sea during global climate changes at 2.6 and 1 Ma
Bibliographic record
Abstract
Abstract. River erosion affects the carbon cycle and thus climate by exporting terrigenous carbon to seafloor sediment and by nourishing CO2-consuming marine life. The Yukon River–Bering Sea system preserves rare source-to-sink records of these processes across profound changes in global climate during the past 5 million years (Ma). Here, we expand the terrestrial erosion record by dating terraces along the Charley River, Alaska, and explore linkages among previously published Yukon River tributary incision chronologies and Bering Sea sedimentation. Cosmogenic 26Al/10Be isochron burial ages of Charley River terraces match previously documented central Yukon River tributary incision from 2.6 to 1.6 Ma during Pliocene–Pleistocene glacial expansion, and at 1.1 Ma during the 1.2–0.7 Ma Middle Pleistocene climate transition. Bering Sea sediments preserve 2–4-fold rate increases of Yukon River-derived continental detritus, terrestrial and marine organic carbon, and silicate microfossil deposition at 2.6–2.1 and 1.1–0.8 Ma. These tightly coupled records demonstrate elevated terrigenous nutrient and carbon export and concomitant Bering Sea productivity in response to climate-forced Yukon River incision. Carbon burial related to accelerated terrestrial erosion may contribute to CO2 drawdown across the Pliocene–Pleistocene and Middle Pleistocene climate transitions observed in many proxy records worldwide.
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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".