A modeling study of temporal and spatial <i>p</i> CO <sub>2</sub> variability on the biologically active and temperature-dominated Scotian Shelf
Bibliographic record
Abstract
Abstract. Continental shelves are thought to be affected disproportionately by climate change and are a large contributor to global air-sea carbon dioxide (CO2) fluxes. It is often reported that low-latitude shelves tend to act as net sources of CO2 whereas mid- and high-latitude shelves act as net sinks. Here, we combine a high-resolution regional model with surface water time-series and repeat transect observations from the Scotian Shelf, a mid-latitude region in the northwest North Atlantic, to determine what processes are driving the temporal and spatial variability of partial pressure of CO2 (pCO2). In contrast to the global trend, the Scotian Shelf acts as a net source. Surface pCO2 undergoes a strong seasonal cycle associated with both a strong biological drawdown of Dissolved Inorganic Carbon (DIC) in spring, and pronounced effects of temperature, which ranges from 0 °C in the winter to near 20 °C in the summer. Throughout the summer, events with low surface-water pCO2 occur nearshore associated with coastal upwelling. This effect of upwelling on pCO2 is also in contrast to the general assumption that upwelling increases surface pCO2 by delivering DIC-enriched water to the surface. Aside from these localized events, pCO2 is relatively uniform across the shelf. Our model agrees with regional observations, reproduces seasonal patterns of pCO2, and simulates annual outgassing of CO2 from the ocean of +1.9 ± 0.2 mol C m−2 yr−1 for the Scotian Shelf, net neutral CO2 flux of −0.09 ± 0.16 mol C m−2 yr−1 for the Gulf of Maine and uptake by the ocean of −0.88 ± 0.4 mol C m−2 yr−1 for the Grand Banks.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".