Robust phylogeny from 481 nuclear genes and plastomes refines infrageneric classification and species delimitation in Chinese hawthorns (Crataegus, Rosaceae)
Bibliographic record
Abstract
Crataegus L. (hawthorns) is a taxonomically challenging genus within the Rosaceae family, exhibiting extensive morphological variation, frequent hybridization, and polyploidy. In China, approximately 17–18 species are recognized, but their subgeneric classification and species boundaries remain unresolved. To clarify these relationships, we analyzed 481 nuclear genes, 73 plastid coding sequences, and comprehensive plastome dataset for 17 Chinese Crataegus species to date. Phylogenomic analyses of both nuclear and plastid data produced well-supported trees that refine the taxonomy and elucidate evolutionary relationships within the genus. All Chinese species are resolved within two subgenera, C. subg. Crataegus and C. subg. Sanguineae, although most currently recognized species are not monophyletic, reflecting complex reticulate evolution involving hybridization and polyploidy. Integrating phylogenomic and morphological evidence, we provide an updated taxonomic synopsis of Chinese Crataegus, describe one new species, five new combinations, and designate 31 lectotypes. This study establishes a robust framework for future systematic, conservation, and horticultural research on this ecologically and economically important lineage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".