Comparing the stress physiology of hard- and soft-released juvenile Atlantic Salmon after transportation for reintroduction
Bibliographic record
Abstract
Abstract Objective We examined whether an extended acclimatization period prior to release (soft release) can allow transported fish to recover from the physiological stress associated with transport compared with conventional release methods, which provide fish with no acclimatization period prior to release (hard release). Methods We monitored an Atlantic Salmon Salmo salar stocking team during a standard reintroduction operation and compared their conventional hard-release method (i.e., immediate release after transport with no acclimatization period) to a soft-release method (i.e., 2 and 4 days in-river acclimatization prior to release). Following a 2.5-h transport event, hard-release fish were immediately blood-sampled for their physiological stress response (cortisol, glucose, and lactate). Soft-release fish were blood-sampled for their physiological stress response following 2 or 4 days of in-river acclimatization. Result While hard- and soft-release fish demonstrated significantly higher cortisol, glucose, and lactate concentrations compared with control fish, cortisol concentrations remained elevated for both the hard- and soft-release groups. However, glucose and lactate concentrations were significantly lower in soft-release fish compared with hard-release fish. Conclusion Soft-release provides fish an extended acclimatization period that was found to impact transport-related physiological stress in fish. Our findings will inform management agencies and practitioners focused on improving the success of salmonid stocking and reintroduction programs.
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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".