Release strategies affect the freshwater residence and survival of hatchery-reared juvenile Chinook Salmon
Bibliographic record
Abstract
Abstract Objective This study investigated the effects of size, location and timing of release on the freshwater residence and survival hatchery-reared Chinook Salmon ( Oncorhynchus tshawytscha ) in the Toquaht River, BC. Methods Juvenile salmon were PIT tagged and released on three separate dates (May 23, June 9 and 19, 2021) and three distinct locations within the river (lower river [below lake], lake, and upper river [above lake]). Fish were detected near the river mouth using a PIT array, and detection data were analyzed with an integrated model of freshwater residence and capture-recapture using Bayesian inference. Result The median duration of freshwater residence was 13.8 days and was longer for fish released in the lake and upper river earlier in the study. The median survival probability was 0.35 and it was higher for fish released in the lake and upper river later in the study. Both freshwater residence time and survival declined with fish size at release. Conclusion These findings highlight that hatchery release strategies can significantly influence survival and freshwater residence times, underscoring the need for adaptable management practices. Impact statement Juvenile Chinook Salmon survival during freshwater residence and outmigration is strongly influenced by hatchery release strategies, thus optimizing these strategies is key for hatcheries to support the recovery of salmon populations.
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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".