Effects of generations in captivity and elevated rearing temperature on Ontario hatchery brook trout ( <i>Salvelinus fontinalis</i> ) fry quality and survival
Bibliographic record
Abstract
Abstract With increasing environmental temperatures causing concern for the status of freshwater fishes, captive breeding programs may become increasingly important for conservation efforts as well as to support fisheries. Although captive broodstocks provide reliable gamete sources for production stocking, prolonged generations under hatchery conditions selection for hatchery conditions (domestication) and reduced phenotypic plasticity to novel environmental stressors. We assessed the effects of rearing temperature and number of generations spent in captivity on the survival and quality (indicated by lack of malformations) of long-term (F 20+ ) and newly-captive (F 1 ) strains of Ontario hatchery brook trout ( Salvelinus fontinalis ) with shared genetic history. We found that elevated temperatures decreased likelihood of survival between the hatched and fry stages. Additionally, we found that elevated temperature reduced fry quality of F 1 fish whereas F 20+ fish were less thermally sensitive, suggesting no reduction in plasticity due to captivity. The combined effects of elevated rearing temperatures and number of hatchery generations suggest that selection for captivity can occur rapidly (in one generation) even under benign conditions, and that additive stressor effects of captivity and temperature may impact newly established strains.
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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".