Does catch-and-release angling pose a threat to American eel? A hooking mortality experiment
Bibliographic record
Abstract
Incidental capture of protected fishes usually calls for immediate release, however, post-release survival has not been investigated for many protected species. The American eel Anguilla rostrata is an example of an imperiled species that is incidentally captured by recreational anglers, but for which the impacts of catch and release are unknown. In this study, we examined the short-term (7 d) mortality and injury of American eels (n = 207) following simulated catch-and-release scenarios (involving manually embedded hooks) in a controlled experiment. Specifically, we compared the effects of cutting the line versus removing the hook, as well as shallow versus deep hooking, in holding tanks. No mortalities occurred in any of the groups during a 7 d monitoring period, and most eels exhibited little to mild injury. A high degree of hook shedding occurred in groups where the hook was shallowly embedded. Hooking depth was significantly related to hook-shedding rate, with 93.7% of hooks shed in the shallow-hook-line-cut group compared to 71.8% of hooks shed in the deep-hook-line-cut group. Our results suggest that recreationally captured American eels may be relatively resilient to catch and release, but validation of these results in a field setting is recommended.
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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 | 0.001 |
| 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".