Low productivity of Chinook salmon strongly correlates with high summer stream discharge in two Alaskan rivers in the Yukon drainage
Bibliographic record
Abstract
Yukon River Chinook salmon (Oncorhynchus tshawytscha) populations are declining for unknown reasons, creating hardship for thousands of stakeholders in subsistence and commercial fisheries. An informed response to this crisis requires understanding the major sources of variation in Chinook salmon productivity. However, simple stock–recruitment models leave much of the variation in this system’s productivity unexplained. We tested adding environmental predictors to stock–recruitment models for two Yukon drainage spawning streams in interior Alaska — the Chena and Salcha rivers. Low productivity was strongly associated with high stream discharge during the summer of freshwater residency for young-of-the-year Chinook salmon. This association was more consistent with the hypothesis that sustained high discharge negatively affects foraging conditions than with acute mortality during floods. Productivity may have also been reduced in years when incubating eggs experienced major floods or cold summers and falls. These freshwater effects — especially density dependence and high discharge — helped explain population declines in both rivers. They are plausible as contributors to the decline of Chinook salmon throughout the Yukon River drainage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".