Oceanographic and Climatic Change in the Bering Sea, Last Glacial Maximum to Holocene
Bibliographic record
Abstract
Abstract Post‐glacial sea level rise led to a direct connection between the Arctic and Pacific Oceans via the Bering Strait. Consequently, the Bering Sea experienced changes in connectivity, size, and sediment sources that were among the most drastic of any ocean basin in the past 30,000 years. However, the sedimentary response to the interplay between climate change and sea level rise in high‐latitude settings such as Beringia remains poorly resolved. To ascertain changes in sediment delivery, productivity, and regional oceanography from the Last Glacial Maximum (LGM) to the Holocene, we analyzed sedimentological, geochemical, and isotopic characteristics of three sediment cores from the Bering Sea. Interpretations of productivity, terrestrial input, nutrient utilization, and circulation are based on organic carbon isotopes (δ13Corg), total organic carbon (TOC), bulk nitrogen isotopes, total organic nitrogen, carbon/nitrogen ratios, elemental X‐ray fluorescence data, grain size, and presence of laminated or dysoxic, green intervals. Principal component analysis of these data captures key climatic intervals. The LGM was characterized by low productivity across the region. In the Bering Sea, deglaciation began around 18–17 ka, with increasing terrestrial sediment and TOC input. Marine productivity increased during the Bølling‐Allerød when laminated sediments revealed dysoxic bottom waters where denitrification was extreme. The Younger Dryas manifested increased terrestrial input and decreased productivity, in contrast with the Pre‐Boreal, when productivity markedly rebounded. The Pre‐Boreal and Bølling‐Allerød were similarly productive, but changes in the source of TOC and a δ13Corg depletion suggest the influence of a gradually flooding Bering Shelf during the Pre‐Boreal and Holocene.
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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 | 0.001 | 0.001 |
| 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".