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Analysis of the Driving Forces in Vegetation Variation in the Grain for Green Program Region, China

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  • Hao Wang

    (Department of Geography, School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Guohua Liu

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing 100085, China)

  • Zongshan Li

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing 100085, China)

  • Xin Ye

    (Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China)

  • Bojie Fu

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing 100085, China)

  • Yihe Lü

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing 100085, China)

Abstract

The Chinese government introduced six ecological restoration programs to improve its natural environment. Although these programs have proven successful in improving local environmental conditions, some studies have questioned their effectiveness when regions suffer from extreme weather conditions. Using the Grain for Green Program (GGP) region as a study area, we estimated vegetation activities in the GGP region from 2000 to 2010 to clarify the trends in vegetation growth and their driving forces. The results showed that: (1) vegetation activities improved in the GGP region during 2000-2010, with 58.94% of the area showing an increased trend in the NDVI (normalized difference vegetation index); (2) 26.33% of the increased vegetation was caused by human interference, and 11.61% by climate variation, human activity was the dominant cause, and resulted in 54.68% of the degradation compared to 4.74% from climate change; and, (3) the contribution of different land use types to the NDVI interannual variations showed that high contribution regions were focused in the arid and semiarid areas, where the vegetation growth is associated with variations in recipitation and temperature. However, conversions between farmland and grassland or forest had a significant effect on the change in the NDVI trend. Therefore, although climate conditions can affect vegetation growth, human activities are more important in vegetation changes, and appropriate human activities would contribute to its continual improvement. Hence, we recommend establishing an assessment and scientific management mechanism for eco-risks in the design and management of ecosystem restoration programs.

Suggested Citation

  • Hao Wang & Guohua Liu & Zongshan Li & Xin Ye & Bojie Fu & Yihe Lü, 2017. "Analysis of the Driving Forces in Vegetation Variation in the Grain for Green Program Region, China," Sustainability, MDPI, vol. 9(10), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:10:p:1853-:d:115104
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    References listed on IDEAS

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    1. Xiao Zhang & Yuanjie Deng & Mengyang Hou & Shunbo Yao, 2021. "Response of Land Use Change to the Grain for Green Program and Its Driving Forces in the Loess Hilly-Gully Region," Land, MDPI, vol. 10(2), pages 1-28, February.
    2. Yuanjie Deng & Lei Jia & Yajun Guo & Hua Li & Shunbo Yao & Liqi Chu & Weinan Lu & Mengyang Hou & Binbin Mo & Yameng Wang & Haiyu Yang & Tongyue Zhang, 2022. "Evaluation of the Ecological Effects of Ecological Restoration Programs: A Case Study of the Sloping Land Conversion Program on the Loess Plateau, China," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
    3. Shidong Li & Bing Wang & Sheng Zhang & Yingfa Chen & Guangshuai Zhao, 2022. "Comprehensive Monitoring and Benefit Evaluation of Converting Farmlands into Forests and Grasslands in China," IJERPH, MDPI, vol. 19(11), pages 1-16, June.
    4. Qiu, Lingling & Kant, Shashi & Zeng, Weizhong, 2023. "Indigenous people's perceptions of benefits and costs of China's second phase of the grain for green program and the influencing factors," Ecological Economics, Elsevier, vol. 214(C).

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