A robust phylogenomic framework supports a revised intrafamilial classification of Urticaceae
Bibliographic record
Abstract
Over the past decade, phylogenomics has significantly enhanced our understanding of relationships among numerous angiosperm lineages. However, comprehensive phylogenetic studies combining broad sampling of both genomic sequences and taxa within the nettle family (Urticaceae) are still lacking. Here, we reconstructed the phylogeny of Urticaceae (345 species across 89% of accepted genera) using concatenated and coalescent analyses from plastome and nuclear ribosomal DNA sequences. Different plastid datasets and tree inference methods yielded a consistent phylogenetic backbone, with 98% of nodes achieving > 90% bootstrap support — a significant improvement compared to 54% of nodes in the latest published phylogenetic study of Urticaceae. Plastid and nuclear phylogenetic relationships were largely congruent, with several exceptions that warrant further study. In the context of the updated phylogenetic relationships, we propose dividing the family into seven tribes that correspond to seven major clades or subclades, including a newly established tribe, Sarcochlamydeae stat. nov . Our phylogenetic analysis indicates that Debregeasia and Phenax are non-monophyletic. By combing morphological, molecular and distributional evidence, we describe a new genus Chiajuia gen . nov . Additionally, we propose synonymizing the following genera: Cypholophus (to Boehmeria ), Haroldiella (to Pilea ), Hemistylus , Neodistemon , Rousselia (all to Pouzolzia ), Hesperocnide (to Urtica ), and Pellionia (to Elatostema ), while recognizing Elatostematoides , Gonostegia , Leptocnide , Margarocarpus , Scepocarpus , and Sceptrocnide as distinct genera. This robust phylogenomic framework and revised classification lays a foundation for future studies on the evolution and ecology of Urticaceae. The approach applied here may also serve as an important reference for other large plant families in angiosperms.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".