Seasonality of Dissolved Organic Carbon in the Upper Northeast Pacific Ocean
Bibliographic record
Abstract
Abstract From seasonal cruises in the NE Pacific Ocean during 2017, we (1) determined dissolved organic carbon concentrations; (2) calculated net community production (NCP) from nitrate drawdown; and (3) established relationships between NCP and seasonal dissolved organic carbon (DOC) accumulation in the upper 75 m. The fraction of NCP that accumulated as DOC, hereafter referred to as the net dissolved production ratio, was calculated for several stations during spring and summer. The net dissolved production ratio was about 0.26 at the oceanic station Ocean Station Papa during different seasons and years. Using nitrate concentration profiles obtained from Bio‐Argo floats during 2009–2018 operating near Ocean Station Papa, we calculated NCP at high temporal resolution and then applied the 0.26 constant in order to (4) estimate DOC variability for the 9‐year period. We found strong seasonality near Ocean Station Papa, with NCP maxima during summers ranging from 0.3 to 2.9 mol C/m2 and surface DOC concentrations estimated from 56 μmol/kg in winters to 73 μmol/kg in summers. There was a 10‐fold interannual variability in the seasonally accumulated inventory of DOC, ranging from 0.078 to 0.75 mol C/m2. This study reinforces the value of deploying floats equipped with chemical sensors in order to better understand marine biogeochemical cycles, especially when high resolution data cannot be obtained otherwise. Given that ~26% of NCP accumulates as DOC in the central Gulf of Alaska, the remaining balance of ~74% is available for export as sinking biogenic particles.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".