Factors Influencing Rearing Success of Atlantic Salmon Stocked as Fry and Parr in Lake Ontario Tributaries
Bibliographic record
Abstract
Abstract From 1995 to 1999, we evaluated the suitability of various stream conditions for rearing juvenile Atlantic salmon Salmo salar in the Lake Ontario watershed. As part of an ongoing initiative to reestablish this species in Lake Ontario, fry and parr were stocked into sites with contrasting amounts of rock and wood cover, fine materials in the substrate, and densities of rainbow trout Onchorhynchus mykiss. Resulting Atlantic salmon densities exceeded the target density of five age-0 fall fingerlings/100 m2 at 52% of the site-years surveyed. Atlantic salmon stocked as parr (fed in hatchery before stocking; annual mean weights, 0.45-0.95 g) consistently had greater survival to the age-0 fall fingerling stage than those stocked as fry (not fed before stocking, annual mean weights, 0.13-0.20 g). The percentage of rock cover at a site was the best predictor of high densities of fall fingerling Atlantic salmon for the parr stocking strategy. For Atlantic salmon stocked as fry, the density of rainbow trout was the most influential variable, exhibiting a negative correlation, whereas the percentage of rock cover was also influential in discerning Atlantic salmon densities in a positive way. Our study also found that densities of fall fingerling Atlantic salmon at sites with high densities of rainbow trout (>1.5/m2) were greater than at sites where rainbow trout were present at lower densities, suggesting that habitat influenced the outcome of competitive interactions. High-quality habitat supported high densities of both species. The results of this study indicate that both above and below barriers in the north shore tributaries of Lake Ontario, sites exist with conditions suitable for rearing Atlantic salmon from the fry to the fall fingerling stage.
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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 | 0.001 | 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".