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Roles of Climate Change and Increasing CO 2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

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  • Qing Huang

    (International Institute for Earth System Science, School of Geography and Ocean Sciences, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China)

  • Weimin Ju

    (International Institute for Earth System Science, School of Geography and Ocean Sciences, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing 210023, China)

  • Fangyi Zhang

    (School of Public Administration, Nanjing University of Finance & Economics, Nanjing 210023, China)

  • Qian Zhang

    (International Institute for Earth System Science, School of Geography and Ocean Sciences, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing 210023, China)

Abstract

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO 2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO 2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr −1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr −1 . The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO 2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr −1 respectively, higher than 4.2 and 3.9 Pg C yr −1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO 2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO 2 on NPP.

Suggested Citation

  • Qing Huang & Weimin Ju & Fangyi Zhang & Qian Zhang, 2019. "Roles of Climate Change and Increasing CO 2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model," Sustainability, MDPI, vol. 11(15), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:15:p:4176-:d:254186
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    References listed on IDEAS

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    1. Christoph Müller & Richard D. Robertson, 2014. "Projecting future crop productivity for global economic modeling," Agricultural Economics, International Association of Agricultural Economists, vol. 45(1), pages 37-50, January.
    2. W. Kolby Smith & Sasha C. Reed & Cory C. Cleveland & Ashley P. Ballantyne & William R. L. Anderegg & William R. Wieder & Yi Y. Liu & Steven W. Running, 2016. "Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization," Nature Climate Change, Nature, vol. 6(3), pages 306-310, March.
    3. Fangyi Zhang & Lijie Pu & Qing Huang, 2015. "Quantitative Assessment of the Human Appropriation of Net Primary Production (HANPP) in the Coastal Areas of Jiangsu, China," Sustainability, MDPI, vol. 7(12), pages 1-14, November.
    4. Detlef Vuuren & Jae Edmonds & Mikiko Kainuma & Keywan Riahi & Allison Thomson & Kathy Hibbard & George Hurtt & Tom Kram & Volker Krey & Jean-Francois Lamarque & Toshihiko Masui & Malte Meinshausen & N, 2011. "The representative concentration pathways: an overview," Climatic Change, Springer, vol. 109(1), pages 5-31, November.
    5. Benjamin Poulter & David Frank & Philippe Ciais & Ranga B. Myneni & Niels Andela & Jian Bi & Gregoire Broquet & Josep G. Canadell & Frederic Chevallier & Yi Y. Liu & Steven W. Running & Stephen Sitch , 2014. "Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle," Nature, Nature, vol. 509(7502), pages 600-603, May.
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    1. Qing Huang & Fangyi Zhang & Qian Zhang & Hui Ou & Yunxiang Jin, 2020. "Quantitative Assessment of the Impact of Human Activities on Terrestrial Net Primary Productivity in the Yangtze River Delta," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    2. Chi Zhang & Shaohong Wu & Yu Deng & Jieming Chou, 2021. "How the Updated Earth System Models Project Terrestrial Gross Primary Productivity in China under 1.5 and 2 °C Global Warming," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    3. Ruiming Cheng & Jing Zhang & Xinyue Wang & Zhidong Zhang, 2022. "Growth Suitability Evaluation of Larix principis-rupprechtii Mayr Based on Potential NPP under Different Climate Scenarios," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    4. Bo Yang & Xiaoshuang Li & Yaqi Xian & Yalin Chai & Min Li & Kaidie Yang & Xiaorui Qiu, 2022. "Assessing the Net Primary Productivity Dynamics of the Desert Steppe in Northern China during the Past 20 Years and Its Response to Climate Change," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
    5. Lei Hao & Shan Wang & Xiuping Cui & Yongguang Zhai, 2021. "Spatiotemporal Dynamics of Vegetation Net Primary Productivity and Its Response to Climate Change in Inner Mongolia from 2002 to 2019," Sustainability, MDPI, vol. 13(23), pages 1-16, December.

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