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Simulation of Vegetation NPP in Typical Arid Regions Based on the CASA Model and Quantification of Its Driving Factors

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  • Gulinigaer Yisilayili

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Baozhong He

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Yaning Song

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Xuefeng Luo

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Wen Yang

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Yuqian Chen

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

Abstract

To assess the carbon balance of terrestrial ecosystems, it is crucial to consider the net primary productivity (NPP) of vegetation. Understanding the response of NPP in Xinjiang’s vegetation to climate factors and human activities is essential for ecosystem management, the Belt and Road Initiative, and achieving carbon neutrality goals. Based on the CASA model, this study uses meteorological data, DEM data, and land cover data, employing trend analysis and partial derivative analysis methods to investigate the temporal trends and spatial distribution of NPP in Xinjiang from 2000 to 2020. Additionally, it quantifies the contributions of climate factors and human activities to NPP fluctuations. The key findings are: (1) The average annual NPP is 101.52 gC/m 2 , with an upward trend, showing an overall growth rate of 0.447 gC/m 2 /yr. Spatially, NPP is higher in northern Xinjiang than in the south, and in mountainous areas compared to basins. (2) Over 21 years, climate factors contributed an average of 1.054 gC/m 2 /yr, while human activities contributed 0.239 gC/m 2 /yr to NPP changes. Among climate factors, temperature, precipitation, and sunshine duration contributed 0.003, 0.169, and 0.588 gC/m 2 /yr, respectively, all showing positive effects on NPP. (3) Forests have the highest average NPP at 443.96 gC/m 2 , with an annual growth rate of 2.69 gC/m 2 /yr. When forest is converted to cropland, the net loss in NPP is −1.94 gC/m 2 , and the loss is even greater in conversion to grassland, reaching −17.33 gC/m 2 . (4) The changes in NPP are driven by both climate factors and human activities. NPP increased in 77.25% of the area, while it decreased in 22.69%. Climate factors have a greater positive impact than human activities.

Suggested Citation

  • Gulinigaer Yisilayili & Baozhong He & Yaning Song & Xuefeng Luo & Wen Yang & Yuqian Chen, 2025. "Simulation of Vegetation NPP in Typical Arid Regions Based on the CASA Model and Quantification of Its Driving Factors," Land, MDPI, vol. 14(2), pages 1-23, February.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:371-:d:1588420
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    References listed on IDEAS

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    1. Jinlong Zhang & Yuan Qi & Rui Yang & Xiaofang Ma & Juan Zhang & Wanqiang Qi & Qianhong Guo & Hongwei Wang, 2023. "Impacts of Climate Change and Land Use/Cover Change on the Net Primary Productivity of Vegetation in the Qinghai Lake Basin," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
    2. Simioni, Guillaume & Marie, Guillaume & Davi, Hendrik & Martin-St Paul, Nicolas & Huc, Roland, 2020. "Natural forest dynamics have more influence than climate change on the net ecosystem production of a mixed Mediterranean forest," Ecological Modelling, Elsevier, vol. 416(C).
    3. Michael J. Behrenfeld & Robert T. O’Malley & David A. Siegel & Charles R. McClain & Jorge L. Sarmiento & Gene C. Feldman & Allen J. Milligan & Paul G. Falkowski & Ricardo M. Letelier & Emmanuel S. Bos, 2006. "Climate-driven trends in contemporary ocean productivity," Nature, Nature, vol. 444(7120), pages 752-755, December.
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