Life in captivity: varied behavioural responses to novel setting and food types in first-generation hybrids of farmed and wild juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>)
Bibliographic record
Abstract
Aquaculture practices continuously seek to improve efficiency to produce larger fish at lower cost. Selective breeding within brood stocks can result in undesirable effects, promoting hatcheries to use outbreeding to increase or maintain genetic diversity. This practice however, could result in the introduction of wild behavioural phenotypes unable to adapt to captive-living conditions. Using four hatchery first-generation hybrid crosses and two fully domesticated stocks of Chinook salmon (Oncorhynchus tshawytscha) in British Columbia, we examined behavioural responses to common aquaculture practices such as abrupt environmental change and novel feed types in juvenile fish. Controlling for mass, we found crosses varied in their behaviours to a novel setting and preferences for natural versus commercial diets. These differences were furthermore associated with rearing environment and stock-level growth rate and body size. Our results suggest selecting for phenotypes that behaviourally exhibit better coping mechanisms and greater flexibility in response to change is possible, and when in combination with growth metrics, should be an integral part of producing the desired farmed fish. Behaviours that allow commercial anadromous fish to easily transition to captive environmental conditions can benefit production and also animal welfare.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".