Biogeochemical‐Argo data suggest significant contributions of small particles to the vertical carbon flux in the subpolar North Atlantic
Bibliographic record
Abstract
Abstract The biological carbon pump exerts a strong control on atmospheric CO2 levels. It includes a range of processes that generate organic carbon in the surface ocean and transport this organic matter from the surface to the deep ocean where it is remineralized and sequestered as inorganic carbon for decades to millennia. While ocean productivity is relatively well observed through a combination of approaches including remote sensing, the magnitude of vertical carbon transport remains poorly constrained by observations and the detailed processes involved are insufficiently understood. In particular, attention to the contribution of small particles has increased in recent years, but previous estimates of the associated vertical carbon flux have ignored remineralization and particle fragmentation. The resulting estimates are likely biased. In this study, we present a method for estimating (1) vertical carbon flux of two different size classes of organic particles and (2) the effect of remineralization and particle fragmentation on mesopelagic flux attenuation using Biogeochemical‐Argo profiles of backscattering and dissolved oxygen. We applied this method to observations from the subpolar North Atlantic and found that, on annual timescales, gravitational settling of large organic particles is dominating the vertical flux through the lower mesopelagic zone. However, small particles contribute significantly to the vertical carbon flux at 100 m (around 36% but can be up to 63%), via different mechanisms, and at 600 m (0–25%) since they can be produced by the fragmentation within the mesopelagic zone.
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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".