Nonstationary effects of ocean temperature on Pacific salmon productivity
Bibliographic record
Abstract
We tested the hypothesis that ocean temperature effects on productivity for northeast Pacific pink (Oncorhynchus gorbuscha), sockeye (Oncorhynchus nerka), and chum salmon (Oncorhynchus keta) changed after 1988–1989, coincident with a decline in Aleutian Low variance. Nonstationary temperature effects were tested with three different analytical methods (correlation, mixed-effects models, and variable coefficient generalized additive models) applied to spawner–recruit time series from 86 wild runs between Puget Sound and the northern Bering Sea. All three methods supported the hypothesis, with evidence for change in temperature effects that was strongest in the Gulf of Alaska, British Columbia, and Washington and weakest in the Bering Sea. Productivity for all three species showed generally positive responses to ocean temperature in Alaska before 1988–1989, but generally neutral responses after 1988–1989. British Columbia and Washington salmon showed either neutral responses to temperature (pink), negative responses that weakened after 1988–1989 (sockeye), or a switch from neutral to negative responses (chum). We conclude that the inverse response of Alaskan and more southern salmon populations to temperature variability is a time-dependent phenomenon.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".