Dissolved Oxygen Variability on the Canadian Pacific Shelf: Trends, Drivers, and Projections in the Context of Emerging Hypoxia in Queen Charlotte Sound
Bibliographic record
Abstract
Abstract Hypoxia is an increasing concern along the Northeast Pacific continental margin, driven by dissolved oxygen () declines related to a warming climate. Although the North Pacific inventory has declined for decades, hypoxia was rarely observed on the central coast of British Columbia, Canada, before 2020. Recent observations from Queen Charlotte Sound (QCS)—the largest shelf sea in the Canadian Pacific—indicate that hypoxia is now an emerging issue in this region. This study synthesizes measurements from numerous platforms to describe regional distributions during 2022 and 2023. These observations reveal persistent shelf‐wide hypoxia during summer months, including periods of statistically defined extreme hypoxia. Comparisons with the hydrographic record from 2003 to 2021 show that concentrations were lower and hypoxia more common in 2022 and 2023 than in previous years. This recent hypoxia is caused by long‐term deoxygenation trends of approximately 5–10 mol per decade at isopycnals representing QCS deep waters, combined with seasonal and interannual variability of similar or larger magnitude. Drivers of regional variability are identified over a broad range of scales. On sub‐decadal time scales, upwelling strength, upwelling timing, and utilization drive variability. On decadal time scales, variability is modulated by the offshore supply of , which appears to propagate from the northwestern Pacific via North Pacific Gyre circulation with an 8‐year lag. Data‐based projections indicate that bottom water hypoxia will occur with increasing frequency in the coming decades, while larger portions of the regional deep layer could experience consistent summertime hypoxia by 2050.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".