Decoupling of net community production and particulate organic carbon dynamics in near shore surface ocean waters
Bibliographic record
Abstract
Abstract. We report results from two Lagrangian surveys off the coast of Oregon, using continuous ship-board sensors to estimate mixed layer net community production (NCP) from diel cycles in biological oxygen saturation (∆O2 / Ar) and optically-derived estimates of particulate organic carbon (POC) and phytoplankton carbon (Cph). The first drifter survey, conducted in a nearshore upwelling zone during the development of a microplankton bloom, exhibited significant differences in NCP derived from ∆O2 / Ar and POC diel cycles, suggesting the presence of large POC losses from the mixed layer. At this site, we utilized the discrepancy between NCPO2 / Ar and NCPPOC, along with additional constraints derived from mixed layer nutrient inventories and surface water excess nitrous oxide (N2O), to estimate particle export, vertical mixing fluxes and DOC production. We estimate that export, vertical mixing and DOC production account for 13–45 %, 24–38 % and 25–49 % of the daily NCP discrepancy, respectively. In contrast, the second drifter survey occurred in more oligotrophic offshore waters, where NCP derived from ∆O2 / Ar and POC measurements were more closely coupled, suggesting a tighter relationship between production and community respiration. These results support the use of diel POC measurements to accurately estimate NCP in lower productivity waters with limited vertical carbon export. Although diel POC measurements may underestimate NCP in higher productivity waters, our results highlight the potential utility of coupled O2 and optical measurements to estimate the fate of POC in such regions.
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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".