Evolutionary history of the scorpionfly <i>Dicerapanorpa magna</i> (Mecoptera, Panorpidae)
Bibliographic record
Abstract
Abstract Climate changes can have fundamental impacts on the distributional patterns of montane species, and range shifts frequently lead to allopatric divergence followed by the establishment of secondary contact zones. Many European and North American organisms have retreated to southern refugia during glacial periods and colonized northward during postglacial periods, but little is known about the evolutionary response of cold‐adapted insects to Pleistocene climate changes in eastern Asia. The scorpionfly Dicerapanorpa magna (Chou), with cold temperate habitat preference and weak dispersal ability, provides a good model system to explore how climate changes have influenced the distribution and divergence of cold‐adapted insects in eastern Asia. This study reconstructed the demographic dynamics and evolutionary history of D. magna with phylogeographic approaches, and predicted the species’ suitable areas under the Last Glacial Maximum (LGM) and current scenarios with the ecological niche modelling analysis. The mitochondrial cytochrome c oxidase subunit I resolved three phylogenetic lineages in D. magna dating back to Pleistocene, corresponding well with the geographically isolated Qinling, Bashan and Minshan Mountains. The ecological niche modelling recovered the suitable habitats for D. magna were the Qinling and Bashan Mountains under LGM and current conditions. The three lineages of D. magna might be in a process of incipient speciation, and likely derived their current distribution from separate glacial origins, followed by vicariance and divergence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".