MétaCan
Menu
Back to cohort
Record W4410523417 · doi:10.1101/2025.05.16.651835

Classification of Urticaceae based on morphology and phylogenetic inference

2025· preprint· en· W4410523417 on OpenAlexaff
Alexandre K. Monro, Olivier Maurin, Long‐Fei Fu, Tom Wells, C. M. Wilmot‐Dear, Juliet Beentje, D. J. N. Hind, Ib Friis, Yi‐Gang Wei, Grace E. Brewer, Robyn S. Cowan, Steven Dodsworth, Jia Dong, Niroshini Epitawalage, Izai A. B. Sabino Kikuchi, Isabel Larridon, Alison Moore, Hervé Sauquet, Jacquie Ujetz, Zeng‐Yuan Wu, Félix Forest, William J. Baker, Elliot M. Gardner

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Species Descriptions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsUrticaceaeMorphology (biology)Phylogenetic treeInferenceEvolutionary biologyBiologyBotanyArtificial intelligenceZoologyComputer scienceGenetics

Abstract

fetched live from OpenAlex

Abstract The Urticaceae (ca. 2600 species) were first formally recognized by Jussieu in the 18th century and last comprehensively monographed by Weddell in the 19th century. Since Weddell’s work, family delimitation has been modified and many genera described in a fragmented manner. Over the past two decades, numerous molecular studies have supported the inclusion of Cecropiaceae within Urticaceae and identified paraphyly in several genera, notably Laportea, Urera, Boehmeria, Parietaria, Pellionia, and Pouzolzia . However, few studies have translated these molecular insights into a revised taxonomy. This study aimed to provide a robust, updated classification for Urticaceae by: a) increasing taxon and genomic locus sampling through the integration of newly generated sequence data with previously published datasets; and b) incorporating morphological data to support a revised delimitation of tribes and genera, and to establish a new linear sequence for the family. We also sought to identify remaining taxonomic challenges. Using Sanger and Angiosperms353 sequence data, we constructed a phylogenetic framework for 57 out of 59 currently accepted genera. We also assessed the phylogenetic informativeness of 57 morphological characters by mapping them onto the phylogeny. Our analyses support the delimitation of 61 monophyletic genera and an infrafamilial classification comprising seven tribes, two of which we describe as new: Myriocarpeae and Leukosykeae. We provide a revised linear sequence for the family. Our classification reinstates several names previously treated as synonyms ( Fleurya, Leptocnide, Margarocarpus, Polychroa, Scepocarpus, Sceptrocnide ), places several genera in synonymy ( Hemistylus and Rousselia under Pouzolzia ; Hesperocnide under Urtica ; Gesnouinia and Soleirolia under Parietaria ), and proposes the recognition of two new genera, Muimar gen. nov. and Pouzolziella gen. nov., to accommodate Boehmeria nivea and Pouzolzia australis, respectively. Mapping morphological characters onto the phylogeny indicates that while most states are homoplastic at the family level, their combination is valuable for recognizing genera. Geographic character mapping suggests a high degree of spatial conservatism at the genus rank. Our dated ultrametric tree suggests an origin for Urticaceae in Indomalaya during the mid-Cretaceous, followed by establishment in the Laurasian boreotropical flora and subsequent dispersal to the neotropics and Africa. Once classified within an evolutionary framework we believe that the Urticaceae represent a valuable study system in evolutionary biology for investigating transitions across biomes, the drivers of floral trait evolution, and intrinsic speciation mechanisms. New tribes : —Leukosykeae, Myriocarpeae New genera : — Muimar, Pouzolziella

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.018
GPT teacher head0.232
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicPlant and Fungal Species DescriptionsFrench-language works237,207