Recreational angling intensity correlates with alteration of vulnerability to fishing in a carnivorous coastal fish species
Bibliographic record
Abstract
Increased timidity is a behavioral response to exploitation caused by a combination of learning and fisheries-induced selection favoring shy fish. In our study, the potential for angling-induced change in fish behavior was examined in two marine coastal fishes exploited by boat recreational fishing in the Mediterranean (Mallorca, Spain). It was expected that the mean vulnerability to capture of surviving individuals would differ across a gradient of previous exposure to recreational angling and that this effect would be present in multiple species. The prediction received partial empirical support. Recreational angling intensity was correlated with enhanced gear-avoidance behavior in only one of the two study species, the carnivorous painted comber (Serranus scriba). By contrast, the omnivorous fish species in our study, the annular seabream (Diplodus annularis), did not differ in its behavior towards hooks in exploited compared with unexploited sites. These results suggest that recreational angling may contribute to patterns of hyperdepletion in catch rates because of increased timidity and associated reduced vulnerability to fishing gear in some exploited species. Such effects would lead to erroneous interpretations about the status of the fish stocks when assessed by fishery-dependent data and would negatively affect catch rates and quality of the fishery in the affected species.
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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 | 0.000 |
| 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".