Stress and food deprivation: linking physiological state to migration success in a teleost fish
Bibliographic record
Abstract
Food deprivation is a naturally occurring stressor that is thought to influence the ultimate life-history strategy of individuals. Little is known about how food deprivation interacts with other stressors to influence migration success. European populations of brown trout (Salmo trutta) exhibit partial migration, whereby a portion of the population smoltifies and migrates to the ocean, and the rest remain in their natal stream. This distinct, natural dichotomy of life-history strategies provides an excellent opportunity to explore the roles of energetic state (as affected by food deprivation) and activation of the glucocorticoid stress response in determining life-history strategy and survival of a migratory species. Using an experimental approach, the relative influences of short-term food deprivation and experimental cortisol elevation (i.e. intra-coelomic injection of cortisol suspended in cocoa butter) on migratory status, survival and growth of juvenile brown trout relative to a control were evaluated. Fewer fish migrated in both the food deprivation and cortisol treatments; however, migration of fish in cortisol and control treatments occurred at the same time while that of fish in the food deprivation treatment was delayed for approximately 1 week. A significantly greater proportion of trout in the food deprivation treatment remained in their natal stream, but unlike the cortisol treatment, there were no long-term negative effects of food deprivation on growth, relative to the control. Overall survival rates were comparable between the food deprivation and control treatments, but significantly lower for fish in the cortisol treatment. Food availability and individual energetic state appear to dictate the future life-history strategy (migrate or remain resident) of juvenile salmonids while experimental elevation of the stress hormone cortisol causes impaired growth and reduced survival of both resident and migratory individuals.
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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".