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Evaluation of Future Trends Based on the Characteristics of Net Primary Production (NPP) Changes over 21 Years in the Yangtze River Basin in China

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  • Yuzhou Zhang

    (School of Public Administration, China University of Geosciences (Wuhan), Wuhan 430074, China
    Hubei Key Laboratory of Biological Resources Protection and Utilization, Hubei Minzu University, Enshi 445000, China)

  • Jian Gong

    (School of Public Administration, China University of Geosciences (Wuhan), Wuhan 430074, China)

  • Jianxin Yang

    (School of Public Administration, China University of Geosciences (Wuhan), Wuhan 430074, China)

  • Jin Peng

    (Hubei Key Laboratory of Biological Resources Protection and Utilization, Hubei Minzu University, Enshi 445000, China)

Abstract

As the third largest river basin in the world, the Yangtze River basin in China has vegetation ecosystems in its plain, mountain, and alpine regions. Studying the change characteristics of the vegetation’s net primary productivity (NPP) and its relationship with natural factors and human activities can aid with understanding, to a certain extent, the response of the ecosystem to global climate change. Based on a total of 21 years of MOD17A3 data products from 2000 to 2020, this paper analyzed the spatial variation characteristics and future trends of the NPP in this region by using the coefficient of variation (CV), trend analysis (β), and Hurst index (H) methods. Meanwhile, correlation analysis was used to explore the influence of natural factors and human activities on the NPP. The results show the following: (1) the total amount of the NPP in the Yangtze River Basin was relatively high, and the overall change trend is rising, while the inter-annual fluctuation is evident. The total amount of NPP ranges from 0.786 PgC (2000) to 1.024 PgC (2020), and the annual average was 0.932 PgC. This increase was mainly caused by the increase in the average NPP of forest land, cultivated land, and construction land. (2) The mean value of the NPP in the different regions of the Yangtze River Basin ranged from 0 (construction land) to 1902.89 gC/m 2 ·a. The mean value of the NPP in the Yangtze River Basin was high in the south and low in the north, as well as high in the middle and low in the east and west. The main high-value areas were located in the Hengduan Mountains and the Yunnan-Guizhou Plateau. The coefficient of variation (CV) was 0.0009–0.9980, and the mean CV was only 0.1126. Regarding the future development trend, 77.90% and 22.10% of the regions showed an increase, 22.10% showed a decrease, and 75.25% showed an anti-sustainable state. (3) The effect of human activities on the NPP was generally negative, and the loss of NPP due to land use change in 2020 was around 9.85 TgC when compared with the same in 2000. (4) The rainfall and temperature in the Yangtze River basin both showed a non-significant increase, and the correlation coefficient between the NPP and rainfall was between −0.874 and 0.910. Furthermore, the correlation coefficient of the temperature ranged from −0.928 to 0.929, with a positive correlation overall and a negative correlation locally, and the NPP changes were more susceptible to the influence of temperature than rainfall.

Suggested Citation

  • Yuzhou Zhang & Jian Gong & Jianxin Yang & Jin Peng, 2023. "Evaluation of Future Trends Based on the Characteristics of Net Primary Production (NPP) Changes over 21 Years in the Yangtze River Basin in China," Sustainability, MDPI, vol. 15(13), pages 1-19, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10606-:d:1187511
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    References listed on IDEAS

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    1. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    2. Zhuoya Zhang & Zheneng Hu & Fanglei Zhong & Qingping Cheng & Mingzhu Wu, 2022. "Spatio-Temporal Evolution and Influencing Factors of High Quality Development in the Yunnan–Guizhou, Region Based on the Perspective of a Beautiful China and SDGs," Land, MDPI, vol. 11(6), pages 1-19, May.
    3. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
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    1. Manman Peng & Chaoqun Li & Peng Wang & Xincong Dai, 2024. "Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia," Agriculture, MDPI, vol. 14(4), pages 1-19, April.
    2. Mengyao Tuo & Guoce Xu & Tiegang Zhang & Jianying Guo & Mengmeng Zhang & Fengyou Gu & Bin Wang & Jiao Yi, 2024. "Contribution of Climatic Factors and Human Activities to Vegetation Changes in Arid Grassland," Sustainability, MDPI, vol. 16(2), pages 1-22, January.

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