Monitoring an Alien Invasion: DNA Barcoding and the Identification of Lionfish and Their Prey on Coral Reefs of the Mexican Caribbean
Bibliographic record
Abstract
BACKGROUND: In the Mexican Caribbean, the exotic lionfish Pterois volitans has become a species of great concern because of their predatory habits and rapid expansion onto the Mesoamerican coral reef, the second largest continuous reef system in the world. This is the first report of DNA identification of stomach contents of lionfish using the barcode of life reference database (BOLD). METHODOLOGY/PRINCIPAL FINDINGS: We confirm with barcoding that only Pterois volitans is apparently present in the Mexican Caribbean. We analyzed the stomach contents of 157 specimens of P. volitans from various locations in the region. Based on DNA matches in the Barcode of Life Database (BOLD) and GenBank, we identified fishes from five orders, 14 families, 22 genera and 34 species in the stomach contents. The families with the most species represented were Gobiidae and Apogonidae. Some prey taxa are commercially important species. Seven species were new records for the Mexican Caribbean: Apogon mosavi, Coryphopterus venezuelae, C. thrix, C. tortugae, Lythrypnus minimus, Starksia langi and S. ocellata. DNA matches, as well as the presence of intact lionfish in the stomach contents, indicate some degree of cannibalism, a behavior confirmed in this species by the first time. We obtained 45 distinct crustacean prey sequences, from which only 20 taxa could be identified from the BOLD and GenBank databases. The matches were primarily to Decapoda but only a single taxon could be identified to the species level, Euphausia americana. CONCLUSIONS/SIGNIFICANCE: This technique proved to be an efficient and useful method, especially since prey species could be identified from partially-digested remains. The primary limitation is the lack of comprehensive coverage of potential prey species in the region in the BOLD and GenBank databases, especially among invertebrates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".