Productivity collapses in the Arabian Sea during glacial cold phases
Bibliographic record
Abstract
Productivity in the Arabian Sea is one of the highest in the world. It is controlled by seasonally reversing monsoonal wind‐driven upwelling of nutrient‐rich deeper waters which fuel phytoplankton growth. The detailed history of upwelling‐induced productivity in the eastern Arabian Sea is unknown. Here we present paleoproductivity records from a composite sediment core at the millennial scale during the last 80 kyr B.P. These records are based on relative abundance counts of planktonic foraminifera and organic carbon contents, which are shown to mainly vary in concert. The eastern Arabian Sea upwelling‐induced productivity was higher in the glacial period than in the Holocene, but it fell repeatedly on millennial timescales. These productivity declines occurred during cold events in the North Atlantic region, with the most pronounced changes prevailing during the Heinrich events. Hence, seasonal monsoon winds that drive upwelling‐induced productivity in the east were weak when the North Atlantic was cold. These weak winds resulted in stratification of the water column, comparable to today's Arabian Sea stratification in the intermonsoonal period. Combining the new eastern with published western Arabian Sea results shows that the entire biological factory was severely diminished during the North Atlantic Heinrich events, and the seasonal productivity change in the Arabian Sea monsoon system was reduced with year‐round low productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".