Morpho-Molecular Discordance and Cryptic Diversity in Jumping Bristletails: A Mitogenomic Analysis of Pedetontus silvestrii (Insecta: Archaeognatha: Machilidae)
Bibliographic record
Abstract
Archaeognatha (bristletails) represent an evolutionarily significant but understudied insect group. Notably, the morphological identification method proposed by Mendes for Archaeognatha has certain limitations, which may lead to the underestimation or misidentification of some cryptic species. To address this issue, we employed an integrated strategy that combines morphological and molecular identification methods. Therefore, this study aimed to (1) identify cryptic diversity within Pedetontus silvestrii using mitogenomic data; (2) clarify phylogenetic relationships among Archaeognatha lineages; and (3) estimate divergence times for key taxonomic splits. We analyzed mitochondrial genomes from six P. silvestrii populations (Liaoning, Jilin, and Hebei Provinces) alongside 14 published Archaeognatha genomes. Key findings include the following: (1) Integrative analyses of genetic distances, phylogenetic reconstruction, bPTP-based molecular species delimitation, and divergence time estimation collectively revealed four evolutionarily distinct lineages within P. silvestrii. (2) Machilidae and Machilinae were non-monophyletic, whereas Petrobiellinae showed close affinity to Meinertellidae. (3) Archaeognatha originated ~301.19 Mya (Late Carboniferous); the Machilinae–Petrobiinae split occurred approximately 153.99 Mya (Jurassic). This study underscores the critical importance of mitogenomic analysis in elucidating cryptic biodiversity, while emphasizing the necessity of integrating morphological identification with molecular characterization for comprehensive species delineation in future taxonomic investigations.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".