Effects of the North Pacific Current on the productivity of 163 Pacific salmon stocks
Bibliographic record
Abstract
Abstract Horizontal ocean transport can influence the dynamics of higher‐trophic‐level species in coastal ecosystems by altering either physical oceanographic conditions or the advection of food resources into coastal areas. In this study, we investigated whether variability in two North Pacific Current (NPC) indices was associated with changes in productivity of North American Pacific salmon stocks. Specifically, we used Bayesian hierarchical models to estimate the effects of the north‐south location of the NPC bifurcation (BI) and the NPC strength, indexed by the North Pacific Gyre Oscillation (NPGO), on the productivity of 163 pink, chum, and sockeye salmon stocks. We found that for salmon stocks located in Washington (WA) and British Columbia (BC), both the BI and NPGO had significant positive effects on productivity, indicating that a northward‐shifted bifurcation and a stronger NPC are associated with increased salmon productivity. For the WA and BC regions, the estimated NPGO effect was over two times larger than the BI effect for pink and chum salmon, whereas for sockeye salmon the BI effect was 2.4 times higher than the NPGO. In contrast to WA and BC stocks, we found weak effects of both horizontal ocean transport processes on the productivity of salmon stocks in Alaska. Our results indicated that horizontal transport pathways might strongly influence population dynamics of Pacific salmon in the southern part of their North American ranges, but not the northern part, suggesting that different environmental pathways may underlie changes in salmon productivity in northern and southern areas for the species under consideration.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".