Evidence map›Paper›PMID 39834377›Full record

ArticleFrontiers in microbiology2024

Urbanized lands degrade surrounding grasslands by deteriorating the interactions between plants and soil microbiome.

Mengchao Fang, Guang Lu, Shuping Zhang, Wei Liang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mengchao FangCollege of Life and Environment Science, Minzu University of China, Beijing, China.
Guang LuCollege of Life and Environment Science, Minzu University of China, Beijing, China.
Shuping ZhangCollege of Life and Environment Science, Minzu University of China, Beijing, China.
Wei LiangMinistry of Education Key Laboratory for Ecology of Tropical Islands, College of Life Sciences, Hainan Normal University, Haikou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To mitigate overgrazing on grasslands, towns were constructed in some pastoral regions of China to relocate pastoralists. Nevertheless, whether and how the urbanized lands impact the surrounding grassland ecosystem remains unclear. We assessed the impacts of urbanized lands on the plant and soil interactions within the surrounding grasslands in order to ensure an eco-sustainable pastoralist relocation. The town with 1 km radius was selected as urbanization sample and a grassland with 1 km radius was selected as nature grassland sample. Plants and soil were investigated in nature grassland (NG), and areas 1 km (T-1 km), 2 km (T-2 km), and 3 km (T-3 km) from the center of the town. In T-1 km and T-2 km, compared to the NG, plant diversity, the abundance of dominant plant species, the abundance of soil wood saprotroph fungi, soil water content (SWC), and total organic carbon (TOC) decreased, while soil plant pathogen fungi, soil pH, and total phosphatase (TP) increased. Conversely, no such changes were observed in T-3 km. The results of Mantel test and Partial least squares path model suggest that the decrease in soil TOC and SWC, along with the increase in pH and TP in T-1 km and T-2 km, lead to a decline in wood saprotroph fungi and an increase in plant pathogen fungi, ultimately resulting in reductions in plant diversity and the abundance of dominant plant species. These results indicate that towns in pastoral areas can lead to surrounding grassland degradation by deteriorating the plant-soil interactions.

Indexed as

degradationgrassland ecosystemplant communitysoil microbial communityurbanization

Identifiers

PMID39834377
PMCPMC11743986

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Registered trials

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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.