Evidence map›Paper›PMID 37790962›Full record

ArticleHeliyon2023

Response of vegetation normalized different vegetation index to different meteorological disaster indexes in karst region of Guangxi, China.

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

Abstract read
In one paragraph

Article in Heliyon, 2023. 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

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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

6 authors.

Ying XieGuangxi Institute of Meteorological Sciences, Nanning, 530022, China.
Yanli ChenGuangxi Institute of Meteorological Sciences, Nanning, 530022, China.
Yue ZhangCollege of Agronomy, Northwest A&F University, Yanglin, 712100, China.
Mingzhi LiBaise Meteorological Bureau, Baise, 533000, China.
Min XieGuangxi Zhuang Autonomous Region Climate Center, Nanning, 530022, China.
Weihua MoGuangxi Institute of Meteorological Sciences, Nanning, 530022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fragile karst areas of Guangxi are the key areas of vegetation protection and restoration work of the government. It is of great significance to study the effects of meteorological disasters on vegetation change for disaster prevention and reduction and ecological protection in the karst areas. The Normalized Differential Vegetation Index (NDVI), as a tool for monitoring vegetation growth, has a strong responsiveness to vegetation and can qualitatively and quantitatively evaluate the vegetation cover and its growth vitality. Therefore, in this study, we analyzed the trend of vegetation change and the impacts of multiple meteorological hazards, such as drought, torrential rainfall, high temperature, and low temperature, on the vegetation of the karst region in Guangxi by using the linear trend method, GIS spatial analysis, and correlation analysis, using the MODIS NDVI and temperature and precipitation information from 2000 to 2020 in the karst region of Guangxi. The results show that: (1) NDVI increased significantly in the karst areas, and 32.2% of the areas had significant improvement in vegetation. The improvement was the most obvious mainly in the central part of the study area, while the vegetation degradation trend was obvious in partial scattered areas in northeast and southwest. (2) On the interannual scale, NDVI was negatively correlated with some meteorological disaster indexes, such as relative humidity index, the number of drought days, the amount of extremely heavy rainstorm, the amount of heavy rainstorm, the number of days with high temperature of ≥35 °C, the number of days with high temperature of 35-37 °C, the number of days with high temperature of ≥37 °C, the minimum temperature, and the effective accumulated temperature of ≤0 °C. The obvious negative effect area of drought on vegetation was mainly concentrated in the middle of the study area, and that of rainfall was mainly distributed in the southwest, northeast and northwest; that of high temperature was mainly distributed in the northwest and northeast, and that of low temperature was mainly concentrated in the southwest and north. (3) On the multi-year monthly scale, the responses of NDVI to drought, high temperature and low temperature disaster indexes had a lag effect, but had no lag effect on rainfall disaster indexes. The lag time of vegetation to drought was 1 month, and the lag time to high temperature and low temperature was 3 months.

Indexed as

Correlation analysisEcologically fragile regionLag effectMeteorological hazard factorRemote sensing index

Identifiers

PMID37790962
PMCPMC10543227

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LicenceCC BY-NC-ND
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