Swimming Performance of Brook Trout after Simulated Catch-and-Release Angling: Looking for Air Exposure Thresholds
Bibliographic record
Abstract
Abstract Air exposure has been hypothesized as one of the primary stressors present during catch-and-release angling. However, there are few studies that systematically vary air exposure duration and evaluate the consequences on individual fish. Here, we evaluated the short-term, sublethal effects of exercise (to simulate angling) and air exposure on the swimming performance of hatchery brook trout Salvelinus fontinalis at 10°C. The duration of the angling event (i.e., chasing the fish by hand) was held constant at 30 s, while air exposure duration was systematically varied between 0, 30, 60, and 120 s. The results showed that air exposures of 60 s or less did not affect swimming performance. However, air exposure of 120 s resulted in a dramatic (∼75%) reduction in swimming performance. In fact, nearly half of the fish held out of the water for 120 s were unwilling or unable to swim at all. No mortality was observed after any of the treatments (fish were monitored for 3 months). This work suggests that fish possess air exposure thresholds that, once exceeded, result in performance impairments. Fish released after extended air exposure may become easy prey for predators or could be displaced downstream by flows in fluvial environments. We conclude that air exposure should be restricted to less than 60 s and ideally should be avoided entirely.
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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".