Physiological effects of environmentally relevant, multi-day thermal stress on wild juvenile Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
) river where water temperatures can exceed the proposed upper thermal limit for the species (~27°C). Current legislation closes the river to recreational angling when water temperatures exceed 20°C for two consecutive nights. We aimed to examine how natural thermal variation, representative of extreme high thermal events, affected the thermal tolerance and physiology of wild, juvenile Atlantic salmon. We acclimated fish to four thermal cycles, characteristic of real-world thermal conditions while varying daily thermal minima (16°C, 18°C, 20°C or 22°C) and diel thermal fluctuation (e.g. Δ5°C-Δ9°C). In each cycling condition, we assessed the role that thermal minima played on the acute thermal tolerance (critical thermal maximum, (CTMax)), physiological (e.g. heat shock protein 70 (HSP70), ubiquitin) and energetic (e.g. hepatic glycogen, blood glucose and lactate) status of juvenile Atlantic salmon throughout repeated thermal cycles. Exposure to 16-21°C significantly increased CTMax (+0.9°C) compared to a stable acclimation temperature (16°C), as did exposure to diel thermal fluctuations of 18-27°C, 20-27°C and 22-27°C, yet repeated exposure provided no further increases in acute thermal tolerance. In comparison to the reference condition (16-21°C), consecutive days of high temperature cycling with different thermal minima resulted in significant increases in HSP70 and ubiquitin, a significant decrease in liver glycogen, and no significant cumulative effect on either blood glucose or lactate. However, comparison between thermally taxed treatments suggested the diel thermal minima had little influence on the physiological or energetic response of juvenile salmon, despite the variable thermal cycling condition. Our results suggest that relatively cooler night temperatures in the summer months may play a limited role in mitigating physiological stress throughout warm diel cycle events.
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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 | 0.000 |
| 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".