An integrative approach clarifies species delimitation and biogeographic history of Debregeasia (Urticaceae)
Bibliographic record
Abstract
Integrative data from plastid and nuclear loci are increasingly utilized to resolve species boundaries and phylogenetic relationships within major angiosperm clades. Debregeasia (Urticaceae), an economically important genus, presents challenges in species delimitation due to its overlapping morphological traits and unstable taxonomic assignments. Here, we analyzed 14 morphological traits and generated 12 data matrices from the plastomes and nrDNA using genome skimming from the nine recognized morphospecies to clarify species boundaries and assess barcode performance in Debregeasia . We also used a universal set of 353 nuclear genes to explore reticulate evolution and biogeographic history of Debregeasia . Plastomes of Debregeasia exhibited the typical quadripartite structure with conserved gene content and marginal independent variations in the SC/IR boundary at inter- and intra-specific levels. Three Debregeasia species were non-monophyletic and could not be discerned by any barcode; however, ultra-barcodes identified the remaining six (67%), outperforming standard barcodes (56%). Our phylogenetic analyses placed Debregeasia wallichiana outside the genus and suggested six monophyletic clades in Debregeasia , although the placement between Debregeasia hekouensis and Debregeasia libera varied. There was extensive trait overlap in key morphologically diagnostic characters, with reticulation analysis showing potentially pervasive hybridization, likely influenced by speciation patterns and overlaps between species ranges. We inferred that Debregeasia crown diversification began at ca . 12.82 Ma (95% HPD: 11.54−14.63 Ma) in the mid-Miocene within Australia, followed by vicariance and later long-distance dispersal, mainly out of southern China. Our findings highlight the utility of genomic data with integrative lines of evidence to refine species delimitation and explore evolutionary relationships in complex plant lineages .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".