A two‐dimensional nitrogen and carbon flux model in a coastal upwelling region
Bibliographic record
Abstract
Coastal upwelling regions are associated with high primary production and disproportionately large fluxes of organic matter relative to the global ocean. However, coastal regions are usually homogenized in global ocean carbon models. We have developed a carbon and nitrogen flux model including all major processes both within and below the euphotic zone over seasonal to decadal timescales for coastal upwelling regions. These fluxes control surface pCO2. The model is applied to the west coast of Vancouver Island, Canada (∼49°N, 126°W). Net annual air‐sea CO2 exchange and export flux of inorganic and organic carbon and nitrogen from the system to the rest of the ocean are estimated for different model scenarios. Model sensitivities are discussed. Results show strong biological drawdown of pCO2during summer and atmospheric CO2 invasion. However, this invasion is nearly balanced by gas evasion during winter. Therefore the region is a much smaller sink of atmospheric CO2 (6 g C m−2yr−1, or equivalently 200 kg C yr−1per m coastline) than the summer season predicts. More significantly, there is a large flux of inorganic carbon (3 × 104 kg C yr−1per m coastline) from intermediate depth ocean water to the surface ocean via the coastal system compared to a small export of organic carbon (all dissolved) (2 × 103 kg C yr−1 per m coastline) back into the lower layer of the open ocean. Thus we suggest that the dominant effect of coastal upwelling on the global ocean is providing a conduit for inorganic carbon to the surface ocean.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".