Integrative analyses unveil speciation linked to host plant shift in <i><scp>S</scp>pialia</i> butterflies
Bibliographic record
Abstract
Discovering cryptic species in well-studied areas and taxonomic groups can have profound implications in understanding eco-evolutionary processes and in nature conservation because such groups often involve research models and act as flagship taxa for nature management. In this study, we use an array of techniques to study the butterflies in the Spialia sertorius species group (Lepidoptera, Hesperiidae). The integration of genetic, chemical, cytogenetic, morphological, ecological and microbiological data indicates that the sertorius species complex includes at least five species that differentiated during the last three million years. As a result, we propose the restitution of the species status for two taxa often treated as subspecies, Spialia ali (Oberthür, 1881) stat. rest. and Spialia therapne (Rambur, 1832) stat. rest., and describe a new cryptic species Spialia rosae Hernández-Roldán, Dapporto, Dincă, Vicente & Vila sp. nov. Spialia sertorius (Hoffmannsegg, 1804) and S. rosae are sympatric and synmorphic, but show constant differences in mitochondrial DNA, chemical profiles and ecology, suggesting that S. rosae represents a case of ecological speciation involving larval host plant and altitudinal shift, and apparently associated with Wolbachia infection. This study exemplifies how a multidisciplinary approach can reveal elusive cases of hidden diversity.
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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 | 0.002 | 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".