Neglecting non-photosynthetic vegetation leads to serious underestimation of the wind erosion prevention service provided by the Grain for Green Program in Inner Mongolia, China

Wind erosion is a major driver of land degradation in drylands. China’s Grain for Green Program (GGP) aims to mitigate this by converting cropland to forest and grassland. However, previous assessments of its effectiveness remain uncertain due to imprecise delineation of implementation areas and the frequent neglect of non-photosynthetic vegetation (NPV), which plays a critical role in wind erosion prevention during non-growing seasons. Focusing on the GGP in Inner Mongolia, this study quantitatively evaluated its wind erosion prevention service by integrating remote sensing–based estimates of photosynthetic and non-photosynthetic vegetation cover, the Revised Wind Erosion Equation (RWEQ), and a buffer-based comparative analysis with adjacent croplands. Results show that GGP-stands significantly enhanced NPV cover by an annual average of 6.80%, contributing to a 3.91% increase in fractional vegetation cover during spring and 5.21% in autumn–winter. In 2023, GGP implementation reduced wind erosion by 264,194 tons relative to croplands, with 69.52% of the reduction occurring in spring. Ignoring NPV would lead to a 45.51% underestimation of the annual wind erosion prevention service. These findings underscore the vital role of NPV in dryland restoration and present a scalable framework for evaluating the GGP’s erosion prevention services at regional to global scales.

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Publication Details

Journal
International Journal of Digital Earth
Published
2025-08-17
DOI
https://doi.org/10.1080/17538947.2025.2543566
Primary Topic
Aeolian processes and effects
Type
article
Field-Weighted Citation Impact
0.00

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article

Neglecting non-photosynthetic vegetation leads to serious underestimation of the wind erosion prevention service provided by the Grain for Green Program in Inner Mongolia, China

Cuicui Ji, Tie‐Gang Wang, Tong Shen, Licheng Zhao et al.
1 links
International Journal of Digital Earth
Aeolian processes and effects
article

Neglecting non-photosynthetic vegetation leads to serious underestimation of the wind erosion prevention service provided by the Grain for Green Program in Inner Mongolia, China

Cuicui Ji, Tie‐Gang Wang, Tong Shen, Licheng Zhao, Hengcong Yang, Xiaosong Li, Tianshi Xiao, Gaoke Yueliang, Gentana Ge
article en

Abstract

Wind erosion is a major driver of land degradation in drylands. China’s Grain for Green Program (GGP) aims to mitigate this by converting cropland to forest and grassland. However, previous assessments of its effectiveness remain uncertain due to imprecise delineation of implementation areas and the frequent neglect of non-photosynthetic vegetation (NPV), which plays a critical role in wind erosion prevention during non-growing seasons. Focusing on the GGP in Inner Mongolia, this study quantitatively evaluated its wind erosion prevention service by integrating remote sensing–based estimates of photosynthetic and non-photosynthetic vegetation cover, the Revised Wind Erosion Equation (RWEQ), and a buffer-based comparative analysis with adjacent croplands. Results show that GGP-stands significantly enhanced NPV cover by an annual average of 6.80%, contributing to a 3.91% increase in fractional vegetation cover during spring and 5.21% in autumn–winter. In 2023, GGP implementation reduced wind erosion by 264,194 tons relative to croplands, with 69.52% of the reduction occurring in spring. Ignoring NPV would lead to a 45.51% underestimation of the annual wind erosion prevention service. These findings underscore the vital role of NPV in dryland restoration and present a scalable framework for evaluating the GGP’s erosion prevention services at regional to global scales.

International Journal of Digital EarthVol. 18(1)
Chinese Academy of Sciences (CN), Beijing Institute of Big Data Research (CN), State Forestry and Grassland Administration (CN), Aerospace Information Research Institute (CN), University of Chinese Academy of Sciences (CN), Chongqing Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 76%
Aeolian processes and effects
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