Evidence map›Paper›PMID 40574730›Full record

ArticlePeerJ2025

Impact of precipitation levels on vegetation in ecologically fragile karst areas in the Guangxi (China) karst region.

Mingzhi Li, Ying Xie, Yanli Chen, Yue Zhang, Weihua Mo

Abstract read
In one paragraph

Article in PeerJ, 2025. 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. Genomic Insights into Adaptation ofPlants (Basel, Switzerland) · 2026
    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

5 authors.

Mingzhi LiBaise Meteorological Bureau, Baise, China.
Ying XieGuangxi Institute of Meteorological Sciences, Nanning, China.
Yanli ChenGuangxi Institute of Meteorological Sciences, Nanning, China.
Yue ZhangCollege of Resources and Environmental Sciences, China Agricultural University, Beijing, China.
Weihua MoGuangxi Institute of Meteorological Sciences, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate the distribution pattern of regional rainstorm disasters and their impact on vegetation in karst regions of Guangxi, two vegetation parameters, fractional vegetation cover (FVC) and net primary productivity (NPP), are selected to analyze the spatial response characteristics and forest species from five rainfall levels: moderate rainfall, heavy rain, rainstorm, heavy rainstorm and extremely heavy rainstorm). Normalized Difference Vegetation Index (NDVI), fractional vegetation cover (FVC), and net primary productivity (NPP) are used to analyze the spatial response characteristics of different vegetation remote sensing parameters. The results show that: (1) The effects of extremely heavy rainfall on the NDVI, FVC and NPP of vegetation are significantly greater than those of other types of rainfall; (2) The southwestern and central parts are the concentration areas of high negative impacts of extremely heavy rainfall and heavy rainfall on the remote sensing indices of vegetation; (3) Different levels of rainfall have a great negative effect on NDVI and FVC in economic and broadleaf forests, while eucalyptus forests have a less effect. The results indicate that vegetation protection should be carried out in a concentrated manner based on geographical and species-specific differences, especially in areas with high incidence of extremely heavy rainfall and regions dominated by economical value and vegetation types. This study can provide a scientific basis for improving the management of rocky desertification and assessing the impact of rainstorm disaster on vegetation in karst regions of Guangxi.

Indexed as

EcosystemForestsRainChinaRemote Sensing TechnologyKarst areasNet primary productivityRainstormVegetation cover

Identifiers

PMID40574730
PMCPMC12199740

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.