Evidence map›Paper›PMID 41298543›Full record

ArticleScientific reports2025

Vegetation dynamics and associated driving mechanisms in the water source area of the central route of the South-to-North Water Diversion, China during 2000-2022.

Limei Wang, Yongtao Jiang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Limei WangSchool of Surveying and Urban Spatial Information, Henan University of Urban Construction, Pingdingshan, 467000, China.
Yongtao JiangSchool of Surveying and Urban Spatial Information, Henan University of Urban Construction, Pingdingshan, 467000, China. 20221033@huuc.edu.cn.

Funding

Start-up Project for High-level Talent Recruitment, Henan University of Urban Construction K-Q2024012the Henan Provincial Science and Technology Research Project 242102321123the Key Scientific Research Project of Colleges and Universities in Henan Province 25A420006the National Natural Science Foundation of China 42074094
6 · The paper itself

Abstract

The water source area (WSA) of the central route of the South-to-North Water Diversion Project (SNWD-C) is crucial for China's water and ecological security. However, vegetation dynamics and associated driving mechanisms in this region remain understudied. This study integrates Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Normalized Difference Vegetation Index (NDVI) data (2000-2022) with climatic and anthropogenic factors using the Google Earth Engine platform. To quantify vegetation dynamics, we employed Sen's slope estimator, the Mann-Kendall test, and the coefficient of variation. Furthermore, the Optimal Partition Geographical Detector (OPGD) model was applied to identify the dominant drivers of vegetation change and to explore their interactive effects. Results show that 98.8% of the WSA (excluding water bodies) maintained a high average NDVI (> 0.5), with significant greening trends (+ 0.0038/a) in 81.4% of the area, mainly in mid-low altitude grasslands. Urban areas showed localized vegetation decline (1.8%). Land surface temperature (LST), Digital Elevation Model (DEM), human footprint (HFP), and land cover (LC) were major drivers. Interactions among these factors significantly improved explanatory power. Cooling trends promoted greening, while warming and intense human activities were linked to vegetation decline. This study provides insights into the mechanisms of vegetation change in the WSA and offers scientific guidance for ecological restoration and sustainable water resource management under the SNWD-C framework.

Indexed as

Driving mechanismsEcological restorationGeographical detectorNDVIThe central route of the South-to-North Water Diversion ProjectVegetation dynamics

Identifiers

PMID41298543
PMCPMC12658195

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LicenceCC BY-NC-ND
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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.