Vertical flux of particulate matter in low productivity environments: A tale from the North
Bibliographic record
Abstract
The vertical export flux of particulate matter drives the transfer of carbon from ocean surface to depths and, thus, plays a key role in marine carbon sequestration. However, the mechanisms controlling the occurrence and intensity of this flux in oligotrophic and low-productivity environments are still actively debated. We present here original investigations on sediment cores from the low productivity Hudson Bay, northern Canada. Interestingly, despite a globally increased atmospheric import of anthropogenic lead, lead concentration in sediment cores from the Hudson Bay are relatively constant for the past centuries, as if the Anthropocene did not leave any track in this environment. This is not consistent with significant increased lead concentrations observed in nearby lakes, during the same period. Because atmospheric deposition is the source of lead for both the lakes and the Hudson Bay, the very low productivity condition that characterize the Hudson Bay is used to explain the reduced vertical export of lead. A reduced vertical export is also consistent with the trend observed in the lead isotopic composition. The 206Pb/207Pb isotopic value from bottom to top of cores indicates an apparent gradual overprint of anthropogenic lead, typical of mixed Canada-USA aerosol origins, during the 1900’s. In other words, the anthropogenic nature of lead is clearly registered in our record but not the total concentration, which suggests that something is limiting its export to the sediment. This is coherent with data from PCB accumulation in the sediment, which did not reflect actual inputs in the surface water of the Hudson Bay, again pointing to a limitation of the vertical export of contaminant. This supports the hypothesis that primary productivity is the most important factor to drive the vertical export of particulate matter, and thus contaminants, in low productivity environments.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".