Quantitatively analyzing the driving factors of vegetation change in China: Climate change and human activities

Chen, Yang; Zhang, Tingbin; Zhu, Xuan; Yi, Guihua; Li, Jingji; Bie, Xiaojuan; Hu, Jiao; Liu, Xian

doi:10.1016/j.ecoinf.2024.102667

Ecological Informatics

2024

DOI: 10.1016/j.ecoinf.2024.102667

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Quantitatively analyzing the driving factors of vegetation change in China: Climate change and human activities

Yang Chen,

Tingbin Zhang,

Xuan Zhu

et al.

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Cited by 5 publications

References 92 publications

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Desertification in northern China from 2000 to 2020: The spatial–temporal processes and driving mechanisms

Wang,

2024

Ecological Informatics

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Desertification in northern China from 2000 to 2020: The spatial–temporal processes and driving mechanisms

Wang,

2024

Ecological Informatics

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Spatiotemporal changes and driving mechanism of ecosystem carbon sink in karst peak cluster depression basin in Southwest Guangxi based on the interaction of “water-rock-soil-air-biology”

Huang,

Tian,

Zhang

et al. 2024

Ecological Informatics

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Disentangling the Response of Vegetation Dynamics to Natural and Anthropogenic Drivers over the Minjiang River Basin Using Dimensionality Reduction and a Structural Equation Model

Kang,

Wang,

et al. 2024

Forests

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Located at an average elevation of approximately 2000 m, the Minjiang River Basin (MJB), a key tributary of the Upper Yangtze River, straddles the Western Sichuan Plateau and the Sichuan Basin. Vegetation here is crucial for human life, providing oxygen and energy. However, the influence of climatic variables, human activities, and rugged terrain on vegetation vitality is still debated. This study mainly leverages data from the Normalized Difference Vegetation Index (NDVI), meteorological stations data, and land use data. Analytical techniques include trend analysis, partial correlation coefficient analysis (PCC), principal component analysis (PCA), and partial least squares structural equation modeling (PLS-SEM). Results indicate a stable upward trend in vegetation growth with minimal fluctuations, with a growth rate of 0.95 × 10−3/a (p < 0.01). PCC analysis shows a positive correlation between NDVI and key climatic elements in over 60% of the area. The areas with significant vegetation growth had the highest average PCC. PCA and PLS-SEM identify temperature and precipitation as primary growth drivers, while elevation and land use intensity hinder growth. The MJB landscape reveals thresholds and tipping points, with specific temperature and precipitation benchmarks varying by elevation, delineating the boundary between flourishing vegetation and growth inhibition.

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Quantitatively analyzing the driving factors of vegetation change in China: Climate change and human activities

Cited by 5 publications

References 92 publications

Desertification in northern China from 2000 to 2020: The spatial–temporal processes and driving mechanisms

Desertification in northern China from 2000 to 2020: The spatial–temporal processes and driving mechanisms

Spatiotemporal changes and driving mechanism of ecosystem carbon sink in karst peak cluster depression basin in Southwest Guangxi based on the interaction of “water-rock-soil-air-biology”

Disentangling the Response of Vegetation Dynamics to Natural and Anthropogenic Drivers over the Minjiang River Basin Using Dimensionality Reduction and a Structural Equation Model

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