Costs of living for juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) in an increasingly warming and invaded world
Bibliographic record
Abstract
Rapid environmental change in freshwater ecosystems has created a need to understand the interactive effects of multiple stressors, with temperature and invasive predators identified as key threats to imperiled fish species. We tested the separate and interactive effects of water temperature and predation by non-native smallmouth bass ( Micropterus dolomieu ) on the lethal (mortality) and sublethal (behavior, physiology, and growth) effects for juvenile Chinook salmon ( Oncorhynchus tshawytscha ) in seminatural stream channel experiments. Over 48 h trials, there was no difference in direct predation with warmer temperatures, but significant interactive effects on sublethal responses of juvenile salmon. Warmer temperatures resulted in significantly stronger and more variable antipredator responses (surface shoaling and swimming activity), while physiological indicators (plasma glucose, plasma cortisol) suggested suppression of physiological mechanisms in response to the combined stressors. These patterns corresponded with additive negative growth in predation, temperature, and combined treatments. Our results suggest that chronic increases in temperature may not increase direct predation over short periods, but can result in significant sublethal costs with negative implications for long-term development, disease resistance, and subsequent size-selective mortality of Pacific salmon.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".