DNA barcoding reveals overlooked species diversity in rays and sharks of Côte d'Ivoire
Bibliographic record
Abstract
Abstract Rays and sharks are increasingly at risk of extinction due to anthropogenic pressures, including industrial fishing, bycatch and habitat degradation, and climate change. Their slow life histories and challenges in accurate species identification further hinder effective conservation. This study focused on ray and shark species along the coast of Côte d’Ivoire, aiming to achieve more accurate taxonomic resolution to improve specimen identification. To achieve this, we employed an integrative taxonomic approach combining morphological analyses and genetic data from two mitochondrial markers: COI (cytochrome c oxidase subunit I) and NADH2 (NADH dehydrogenase subunit 2), in order to describe the diversity of elasmobranchs landed, identify potential species complexes requiring further investigation, and assess the vulnerability of the captured elasmobranchs. Our study included 220 specimens of rays and sharks collected from 11 landing sites between February 2022 and September 2024. Sequence analysis revealed 32 Barcode Index Numbers (BINs), 11 of which were newly recorded in the Barcode of Life Data System (BOLD). Several unidentified genetic lineages were detected, suggesting the presence of cryptic species, misidentified taxa or potential undescribed species, including Torpedo cf. torpedo, Aetomylaeus cf. bovinus, Gymnura cf. sereti, Raja cf. miraletus, and Squalus cf. blainville. Notably, most of the identified species are listed as threatened on the IUCN Red List. These findings underscore the urgent need for comprehensive taxonomic evaluations and reassessments of conservation statuses, while also highlighting the importance of incorporating molecular tools into national fisheries monitoring and management strategies.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".