Influences of stress phenotype, nutrition and genetic background on the \nupper thermal tolerance of Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Anthropogenic climate change threatens the sustainability of the Atlantic salmon (Salmo salar) aquaculture industry. This thesis studied the effects of three factors [i) stress phenotype; ii) supplemental dietary cholesterol; and iii) family/genetic background] on the performance of farmed Atlantic salmon when exposed to an incremental thermal maximum (ITMax, +0.2°C day⁻¹) challenge that mimicked natural summer sea-cage conditions. No differences in the ITMax of male Atlantic salmon characterized as either low (LR) or high stress responders (HR) based on measurements of post-stress cortisol levels at 9°C was found, and interestingly, stress phenotypes were no longer distinguishable from one another when post-stress cortisol levels were analyzed at elevated temperatures. However, some differences in gene expression were found between LR and HR fish in response to bacterial immune stimulation. Notably, HR salmon mounted a greater (p < 0.05) innate antibacterial immune response than LR salmon at 20°C, whereas LRs had a greater (p = 0.057) response among stress-related transcripts relative to HR fish at 12°C. Supplemental dietary cholesterol did not affect the ITMax of female triploid Atlantic salmon. However, ≤ 5% of the salmon (irrespective of diet) died before temperature reached 22°C, and this suggests that the commercial production of triploids is possible in eastern Canada. In addition, inclusion of +1.30 and 1.76% cholesterol in the diet reduced fillet bleaching above 18°C. Finally, family-based differences in ITMax were detected in diploid, mixed sex, Atlantic salmon, with a 1.7°C separation between the least and most tolerant families. This study also showed that ITMax is a more sensitive and relevant indicator of upper thermal tolerance than the more common/convenient approach of assessing a fish’s critical thermal maximum (CTMax). In the final chapter of this thesis, I characterized the four paralogues of serpinh1 [alias heat shock protein 47 (hsp47)] in Atlantic salmon. This is a well-established biomarker of heat stress \nin salmonids, and the reported data provide important insights into the evolutionary history and regulatory functions of this essential gene. Overall, this thesis provides novel information on how the Atlantic salmon aquaculture industry can most effectively assess upper thermal tolerance, and navigate this era of accelerated climate change.
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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".