Identifying Potential Critical Angel Shark Areas in Türkiye, Eastern Mediterranean Based on New Records of Squatina spp. Identified through Fisher Engagement
Bibliographic record
Abstract
This study presents new records of three Critically Endangered angel shark species (Family: Squatinidae) occurring in the Eastern Mediterranean—Smoothback Angelshark S. oculata Bonaye, 1840, Sawback Angelshark S. aculeata Cuvier, 1829, and Angelshark S. squatina (Linnaeus, 1758). The supporting data serves to highlight three potential Critical Angel Shark Areas (CASAs) in Türkiye: Fethiye Bay, Çanakkale Strait (i.e., Dardanelles), and Antalya Bay. These data also demonstrate that female S. oculata may mature at a smaller size than prior published estimates of length at first maturity. This new dataset provides details of 23 S. squatina specimens, 52 S. oculata specimens, and 5 S. aculeata specimens, totalling 80 recent angel shark specimens found in Turkish waters mostly sent to us from small-scale fishers who had incidentally caught angel sharks. Also presented are four capture-induced parturition events in Turkish waters onboard fishing vessels, thus providing details on internal yolk sacs, reproductive habitats, and indications of spawning season. Our dataset presented here spans from 2018 to 2023 and suggests that mature adults of S. squatina and S. oculata still occur in Turkish waters, in Fethiye Bay and Çanakkale, respectively. Due to elevated chances of fishers encountering Critically Endangered angel sharks in Türkiye, we suggest that fishers are trained in handling and safe-release methods, to ensure reduced incidents of capture-induced parturition, and improved post-release survival. This study demonstrates that bottom set nets set by small-scale fishers pose less risk to mortality for angel sharks as they are almost always encountered alive after a usual 12 h soak time, suggesting that bottom trawling in critical habitats should be better regulated (or phased out) to help improve national angel shark conservation initiatives.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".