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Decreasing Net Primary Productivity in Response to Urbanization in Liaoning Province, China

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  • Tan Chen

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China)

  • Qiuhao Huang

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China)

  • Miao Liu

    (Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China)

  • Manchun Li

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China
    Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China)

  • Le’an Qu

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China
    College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241000, China)

  • Shulin Deng

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China
    Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China)

  • Dong Chen

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Department of Geographic Information Science, Nanjing University, Nanjing 210093, China)

Abstract

Regional ecosystems have been greatly affected by the rapid expansion of urban areas. In order to explore the impact of land use change on net primary productivity (NPP) in rapidly developing cities during the current urbanization process, we quantified land use change in Liaoning province between 2000 and 2010 using net primary productivity as an indicator of ecosystem productivity and health. The Carnegie–Ames–Stanford Approach model was used to estimate NPP by region and land use. We used a unit circle-based evaluation model to quantify local urbanization effects on NPP around eight representative cities. The dominant land use types were farmland, woodland and urban, with urban rapidly replacing farmland. Mean annual NPP and total NPP decreased faster from 2005 to 2010 than from 2000 to 2005, reflecting increasing urbanization rates. The eastern, primarily woodland part of Liaoning province had the greatest reduction in NPP, while the western part, which was primarily farmland and grassland, had the lowest reduction.

Suggested Citation

  • Tan Chen & Qiuhao Huang & Miao Liu & Manchun Li & Le’an Qu & Shulin Deng & Dong Chen, 2017. "Decreasing Net Primary Productivity in Response to Urbanization in Liaoning Province, China," Sustainability, MDPI, vol. 9(2), pages 1-17, January.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:162-:d:88598
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    References listed on IDEAS

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    Cited by:

    1. Shulin Chen & Li Yang & Xiaotong Liu & Zhenghao Zhu, 2022. "Net Primary Productivity Variations Associated with Climate Change and Human Activities in Nanjing Metropolitan Area of China," IJERPH, MDPI, vol. 19(22), pages 1-18, November.
    2. Danardono & Sunariya M. Iqbal Taufiqurrahman & Fikriyah Vidya Nahdiyatul & Cholil Munawar, 2021. "Spatiotemporal Variation of Terrestrial Carbon Sequestration in Tropical Urban Area (Case Study in Surakarta District, Indonesia)," Quaestiones Geographicae, Sciendo, vol. 40(3), pages 5-20, September.
    3. Liu, Xin & Wang, Ping & Song, Hang & Zeng, Xiaoying, 2021. "Determinants of net primary productivity: Low-carbon development from the perspective of carbon sequestration," Technological Forecasting and Social Change, Elsevier, vol. 172(C).

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