Climate regimes and water temperature changes in the Columbia River: bioenergetic implications for predators of juvenile salmon
Bibliographic record
Abstract
We examined how climatic regime shifts may have affected predation rates on juvenile Pacific salmonids (Oncorhynchus spp.) by northern squawfish (Ptychocheilus oregonensis, also called northern pikeminnow), smallmouth bass (Micropterus dolomieu), and walleye (Stizostedion vitreum) in the Columbia River. During 19331996, oceanic, coastal, and freshwater indices of climate were highly correlated, and an index for the Columbia River Basin suggested that climate shifts may have occurred about 1946, 1958, 1969, and 1977. Summer water temperature varied as much as 2°C between climate periods. We used a bioenergetics model for northern squawfish, the most important piscivore, to predict that predation on salmonids would have been 2631% higher during two periods with relatively warm springsummer water temperatures (19331946, 19781996) than during an extremely cold period (19471958). Predicted predation rates of northern squawfish were 6896% higher in the warmest year compared with the coldest year. Predation rates of smallmouth bass and walleye on juvenile salmonids varied among climate periods similar to rates predicted for northern squawfish. Climatic effects need to be understood in both freshwater and nearshore marine habitats, since growth rates of salmon populations are especially sensitive to mortality during early life stages.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".