Evidence map›Paper›PMID 42824456›Full record

ArticleFrontiers in plant science2026

Urban land-use filtering favors herbaceous spontaneous flora and reshapes alien-native composition in a semi-humid inland city.

Yichao Wang, Qian Wang, Xinyi Zhang, Xinna Li, Mir Muhammad Nizamani, Qinghui Sun

Abstract read
In one paragraph

Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yichao Wang *National Health Commission Key Laboratory of Control of Tropical Diseases, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Qian Wang *National Health Commission Key Laboratory of Control of Tropical Diseases, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Xinyi ZhangSchool of Environment and Geography, Qingdao University, Qingdao, China.
Xinna LiNational Health Commission Key Laboratory of Control of Tropical Diseases, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Mir Muhammad NizamaniGuangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention, Institute of Marine Sciences, Shantou University, Shantou, China.
Qinghui SunNational Health Commission Key Laboratory of Control of Tropical Diseases, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urban spontaneous plants record how vegetation responds to land use, disturbance, management, and propagule pressure, but their composition and assembly remain insufficiently studied in semi-humid inland cities. We surveyed 151 urban functional units (UFUs) in Jinan, China, combining field vegetation inventories, high-resolution land-cover interpretation, socioeconomic and management variables, and count-data robustness models to test how urban habitat filters structure spontaneous plant richness and composition. Across all UFUs, 379 vascular plant species were recorded, including 140 spontaneous species. The spontaneous flora was almost entirely herbaceous (138 species, 98.6%), with only two woody species occurring as seedlings and no mature spontaneous trees recorded. Alien species accounted for 74 spontaneous species (52.9%), slightly exceeding native species. Spontaneous richness differed among UFUs, with residential districts supporting the highest mean richness and transportation areas supporting the lowest. Exploratory linear regression identified positive associations of richness with residential land use, fertilization frequency, housing price, and UFU area. After accounting for overdispersed count data, however, negative binomial models retained residential land use and total UFU area as the most stable positive predictors, whereas fertilization and housing price were not significant. These results indicate that spontaneous plant diversity in Jinan is primarily organized by land-use filtering and habitat capacity, while socioeconomic and management gradients provide weaker and model-dependent signals. The study highlights the value of UFU-based analysis for linking urban plant community assembly with practical land-management units in rapidly urbanizing inland cities.

Indexed as

alien-native compositionherbaceous floraland-use filteringsemi-humid inland cityurban functional unitsurban plant diversityurban spontaneous plants

Identifiers

PMID42824456
PMCPMC13627410

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.