Single-locus species delimitation of Pronophilina butterflies (Nymphalidae: Satyrini) in the Colombian Andes: congruence between morphology and MOTUs
Bibliographic record
Abstract
The subtribe Pronophilina (Nymphalidae: Satyrinae: Satyrini) is one of the most diverse subtribes within the Lepidoptera. In Colombia, these butterflies are distributed throughout the Andes, where they play a key role in montane ecosystems and exhibit high levels of endemism. Despite their complex genital morphology, species within the same genus often exhibit highly similar wing patterns, complicating taxonomic identification. In this study, we analyzed the concordance between DNA barcode-based species delimitation and morphological identifications using 334 cytochrome c oxidase subunit I barcodes from 94 a priori identified morphospecies in Colombia. We applied four molecular species delimitation methods (Automatic Barcode Gap Discovery, Refined Single Linkage, Poisson Tree Processes, and Assemble Species by Automatic Partitioning), delimitating between 98 and 108 molecular operational taxonomic units. Overall, the methods showed high consistency, with high congruence between morphological and molecular delimitations (81%). Additionally, 96.8% of the morphospecies exhibited a barcode gap, indicating clear genetic differentiation. However, we found some inconsistencies, including 6 cases of species merging and 12 cases of species splitting. Our findings underscore the utility of DNA barcoding for species delimitation in Pronophilina, while highlighting the need for integrative approaches to resolve taxonomic uncertainties in this diverse group.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".