Quantifying the effects of post-surgery recovery time on the migration dynamics and survival rates in the wild of acoustically tagged Atlantic Salmon Salmo salar smolts
Bibliographic record
Abstract
Abstract Background The experimental effects of surgically implanting fish with acoustic transmitters are likely to have negative effects on survival and behaviour. Measuring the extent of these negative effects is important if we wish to extrapolate inferences from tagged animals to un-manipulated animals. In this study, we examine the effect of surgery and post-tagging recovery time on the survival and migration rate of acoustically tagged wild Atlantic Salmon ( Salmo salar) smolts through freshwater, estuarine and ocean phases of migration. Four treatment groups were used: pre-smolt captured in the fall that overwintered in a hatchery and were tagged either 75 days prior to release (winter hatchery) or within 24 h prior to release (spring hatchery) and smolt captured during the spring smolt run, tagged 24 h prior to release and released during the day (day-released) or night (night-released). Results The spring hatchery treatment group served as a reference treatment group such that recovery time (comparison to winter hatchery treatment) and hatchery effects (comparison to day-released and night-released treatments) could both be discerned. The hatchery effect increased migration rate, whereas short recovery times and captivity in a hatchery negatively affected survival. These effects were most pronounced within the first 5 days and/or 48 km downstream post-release, however, the residual recovery time effects appeared to persist during the transition from the estuary into salt water. Conclusions Even with smolts originating from the wild and spending relatively little time within the hatchery environment, post-release survival was still negatively affected. Migration speed was faster for hatchery smolts, but is likely only due to their larger size. Recovery time effects were most prominent during the initial migration period in freshwater and again in the transition from the estuary to saltwater which may be due to added stress during these transitional zones. As surgery-related bias will likely never be completely removed from telemetry studies, it is important to quantify and account for these effects in situ when making inferences on the un-manipulated component of the population.
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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 | 0.001 | 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".