Diel patterns of hooking depth for active and passive angling methods for two freshwater teleost fishes
Bibliographic record
Abstract
The increasing popularity of catch-and-release angling indicates a need to identify best practices that minimize sublethal injuries, impairments, and mortality. One factor impacting the viability of catch and release is the risk of hooking injury, which can impact survival in released fishes. In particular, deep hooking is known to increase post-release mortality in numerous species. As such, best practices include the use of equipment and promotion of angler behaviors that reduce incidences of deep hooking. In some areas, angling at night is restricted because of concerns that deep hooking is elevated relative to angling during the day. However, there has been little empirical research investigating whether deep hooking is influenced by the time of day (light levels). In the present study, we captured bluegill (Lepomis macrochirus Rafinesque, 1810) and pumpkinseed (Lepomis gibbosus Linnaeus, 1758) using active angling (cast and retrieve) and passive angling (with a bobber) throughout the 24-hr period, and recorded hook depth and hook location for each fish. We found that passive angling methods resulted in deeper hooking than active angling methods for both bluegill and pumpkinseed across all time periods. Although few pumpkinseed were caught at night, we found that the pumpkinseed caught were hooked more deeply and in more damaging hooking locations at night relative to the day. Hooking injury was independent of diel period for the more frequently landed species, bluegill. These findings emphasize the species-specific nature of catch-and-release outcomes, and suggest that further research is warranted to adequately quantify the impacts of recreational fishing at night.
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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 | 0.001 | 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".