Well-Known, Misidentified, or Unnamed? A DNA Barcode-Based Reassessment of the Lepidoptera Fauna of Cyprus Supported by Morphology
Bibliographic record
Abstract
This study presents the first comprehensive molecular analysis of the Lepidoptera fauna of Cyprus based on DNA barcoding. A total of 1859 DNA barcode sequences were generated, representing 701 Barcode Index Numbers (BINs) and thus putative species. Morphological examination enabled the assignment of 596 BINs to 580 Linnaean species. Based on this genetically validated species inventory—complemented by morphologically examined specimens and a critical review of the literature—a new checklist for the Lepidoptera of Cyprus is provided. In total, 1213 species are accepted as confirmed or considered likely based on published but unverified records. The checklist includes 57 genetically confirmed first records for Cyprus and 62 new records supported solely by morphology. Remarkably, 10 species are recorded as new to Europe: Alloclita deprinsi, Cochylimorpha diana, C. additana, Pammene avetianae, P. nannodes, Cydia alienana, Ephestia abnormalella, Hypsotropa paucipunctella, Dysauxes parvigutta, and Bryophilopsis roederi. In addition, 105 BINs could not be assigned to a species. Preliminary morphological assessment indicates that many of these represent cryptic taxa or belong to taxonomically unresolved species complexes. Furthermore, 35 morphology-based records could be identified at best to the genus level. The study also lists 158 previously published species that are now considered likely misidentifications and therefore excluded from the Cypriot fauna.
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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".