Long-term consequences of variation in timing and manner of fry introduction on juvenile Atlantic salmon (<i>Salmo salar</i>) growth, survival, and life-history expression
Bibliographic record
Abstract
We tested the influence of introduction time and the manner of introduction on growth, survival, and life-history expression of Atlantic salmon (Salmo salar). Introduction treatments included three fry stocking times and stream rearing of embryos. Despite poor growth conditions during the early stocking period, early-stocked fish were larger throughout the entire study period, likely the result of prior residence advantage. This interpretation was reinforced by the laboratory study, where early-stocked fish outgrew late-stocked fish when reared together, but not when they were reared separately. In contrast to growth, abundance of stocked fish was greatest for fish stocked during the middle period, and this stocking group produced the greatest number of smolts. Despite smaller size, survival of stream-incubated fish was generally greater than survival of stocked fish. Introduction timing had a pronounced effect on smolt age but a weak effect on extent of parr maturation. Overall, these observations indicate that small differences (~2 weeks) in introduction time can have long-term effects on size, survival, and life-history expression. Results suggest stabilizing selection on introduction times, mediated by the interaction between prior residence (advantage to fish introduced earlier) and habitat suitability (advantage to fish introduced later).
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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 | 0.001 |
| 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".