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Record W7106505084 · doi:10.1111/geb.70159

Here, There and Everywhere: Widespread Non‐Native Plants in the World's Urban Ecosystems

2025· article· en· W7106505084 on OpenAlexafffund

Bibliographic record

VenueGlobal Ecology and Biogeography · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersAkademie Věd České RepublikyConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of TorontoGrantová Agentura České RepublikyFundação de Amparo à Pesquisa do Estado de Minas GeraisDeutsche ForschungsgemeinschaftDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigNatural Sciences and Engineering Research Council of CanadaEuropean CommissionUniversity of Toronto ScarboroughNextGenerationEUNational Science Foundation
KeywordsUrban ecologyTaxonUrban ecosystemOrdinationTemperate climateEcosystemIntroduced speciesSpecies richnessVascular plant

Abstract

fetched live from OpenAlex

ABSTRACT Aim To (a) produce a list of the most widespread naturalised non‐native plant species across cities of the world; (b) explore whether cities on different continents are invaded by the same group of widespread naturalised species; and (c) elucidate the origins of the most widespread naturalised urban species. Location Global. Time Period No specific period. Major Taxa Studied Vascular plants. Method Using the most comprehensive and up‐to‐date dataset of non‐native urban floras yet assembled (GUBIC; Global Urban Biological Invasions Compendium), we identified the most widespread naturalised plant species (the global urban florome) by filtering for taxa present across all continents (except Antarctica) and their frequency in urban areas. To assess global patterns of urban plant naturalisation, we conducted ordination analyses and visualised species co‐occurrence. We also examined species origins and their environmental impact. Results Among the 7792 naturalised plant species recorded in 553 urban centres, 302 species (4%) were found on all six continents. Of these, 96 species, considered the most widespread species, were present in more than half of urban centres in Oceania, North America and South America; this proportion was higher than in Africa, Asia and Europe. Cities outside Europe and Asia are more homogeneous in terms of the species composition of the most widespread invaders. An analysis of species origins showed that temperate Asia contributed the most species globally, while intercontinental exchange patterns varied, with a notable one‐directional flow from North to South America. Main Conclusions Our results suggest that urban ecosystems outside Europe and Asia are more susceptible to recent invasions than those within these two continents. Understanding the composition and origins of these widespread species is crucial for developing coordinated management strategies and improving the resilience of urban biodiversity.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.005
GPT teacher head0.233
Teacher spread0.228 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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