IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11744-d663715.html
   My bibliography  Save this article

How the Updated Earth System Models Project Terrestrial Gross Primary Productivity in China under 1.5 and 2 °C Global Warming

Author

Listed:
  • Chi Zhang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Shaohong Wu

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Yu Deng

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Jieming Chou

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China)

Abstract

Three Earth system models (ESMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) were chosen to project ecosystem changes under 1.5 and 2 °C global warming targets in the Shared Socioeconomic Pathway 4.5 W m −2 (SSP245) scenario. Annual terrestrial gross primary productivity (GPP) was taken as the representative ecological indicator of the ecosystem. Under 1.5 °C global warming, GPP in four climate zones—i.e., temperate continental; temperate monsoonal; subtropical–tropical monsoonal; high-cold Tibetan Plateau—showed a marked increase, the smallest magnitude of which was around 12.3%. The increase was greater under 2 °C of global warming, which suggests that from the perspective of ecosystem productivity, global warming poses no ecological risk in China. Specifically, in comparison with historical GPP (1986–2005), under 1.5 °C global warming GPP was projected to increase by 16.1–23.8% in the temperate continental zone, 12.3–16.1% in the temperate monsoonal zone, 12.5–14.7% in the subtropical–tropical monsoonal zone, and 20.0–37.0% on the Tibetan Plateau. Under 2 °C global warming, the projected GPP increase was 23.0–34.3% in the temperate continental zone, 21.2–24.4% in the temperate monsoonal zone, 16.1–28.4% in the subtropical–tropical monsoonal zone, and 28.4–63.0% on the Tibetan Plateau. The GPP increase contributed by climate change was further quantified and attributed. The ESM prediction from the Max Planck Institute suggested that the climate contribution could range from −12.8% in the temperate continental zone up to 61.1% on the Tibetan Plateau; however, the ESMs differed markedly regarding their climate contribution to GPP change. Although precipitation has a higher sensitivity coefficient, temperature generally plays a more important role in GPP change, primarily because of the larger relative change in temperature in comparison with that of precipitation.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11744-:d:663715
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11744/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/21/11744/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. D. S. Schimel & J. I. House & K. A. Hibbard & P. Bousquet & P. Ciais & P. Peylin & B. H. Braswell & M. J. Apps & D. Baker & A. Bondeau & J. Canadell & G. Churkina & W. Cramer & A. S. Denning & C. B. F, 2001. "Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems," Nature, Nature, vol. 414(6860), pages 169-172, November.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gupta, Rishabh & Mishra, Ashok, 2019. "Climate change induced impact and uncertainty of rice yield of agro-ecological zones of India," Agricultural Systems, Elsevier, vol. 173(C), pages 1-11.
    2. Voisin, Nathalie & Dyreson, Ana & Fu, Tao & O'Connell, Matt & Turner, Sean W.D. & Zhou, Tian & Macknick, Jordan, 2020. "Impact of climate change on water availability and its propagation through the Western U.S. power grid," Applied Energy, Elsevier, vol. 276(C).
    3. Cristina Cattaneo & Emanuele Massetti, 2019. "Does Harmful Climate Increase Or Decrease Migration? Evidence From Rural Households In Nigeria," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 1-36, November.
    4. Pascalle Smith & Georg Heinrich & Martin Suklitsch & Andreas Gobiet & Markus Stoffel & Jürg Fuhrer, 2014. "Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change," Climatic Change, Springer, vol. 127(3), pages 521-534, December.
    5. T.M.L. Wigley, 2018. "The Paris warming targets: emissions requirements and sea level consequences," Climatic Change, Springer, vol. 147(1), pages 31-45, March.
    6. Gong, Ziqian & Baker, Justin S. & Wade, Christopher M. & Havlík, Petr, 2024. "Irrigation intensification in U.S. agriculture under climate change – an adaptation mechanism or trade-induced response?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343581, Agricultural and Applied Economics Association.
    7. Kalkuhl, Matthias & Wenz, Leonie, 2020. "The impact of climate conditions on economic production. Evidence from a global panel of regions," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    8. Islam, AFM Tariqul & Islam, AKM Saiful & Islam, GM Tarekul & Bala, Sujit Kumar & Salehin, Mashfiqus & Choudhury, Apurba Kanti & Dey, Nepal C. & Hossain, Akbar, 2022. "Adaptation strategies to increase water productivity of wheat under changing climate," Agricultural Water Management, Elsevier, vol. 264(C).
    9. Jaewon Kwak & Huiseong Noh & Soojun Kim & Vijay P. Singh & Seung Jin Hong & Duckgil Kim & Keonhaeng Lee & Narae Kang & Hung Soo Kim, 2014. "Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea," IJERPH, MDPI, vol. 11(10), pages 1-19, October.
    10. Hwang, In Chang, 2013. "Stochastic Kaya model and its applications," MPRA Paper 55099, University Library of Munich, Germany.
    11. Roson, Roberto & Damania, Richard, 2016. "Simulating the Macroeconomic Impact of Future Water Scarcity an Assessment of Alternative Scenarios," Conference papers 332687, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    12. Le Bars, Dewi, 2018. "Uncertainty in sea level rise projections due to the dependence between contributors," Earth Arxiv uvw3s, Center for Open Science.
    13. Marcinkowski, Paweł & Piniewski, Mikołaj, 2024. "Future changes in crop yield over Poland driven by climate change, increasing atmospheric CO2 and nitrogen stress," Agricultural Systems, Elsevier, vol. 213(C).
    14. Yujin Li & Juying Jiao & Zhijie Wang & Binting Cao & Yanhong Wei & Shu Hu, 2016. "Effects of Revegetation on Soil Organic Carbon Storage and Erosion-Induced Carbon Loss under Extreme Rainstorms in the Hill and Gully Region of the Loess Plateau," IJERPH, MDPI, vol. 13(5), pages 1-15, April.
    15. Taylor, Chris & Cullen, Brendan & D'Occhio, Michael & Rickards, Lauren & Eckard, Richard, 2018. "Trends in wheat yields under representative climate futures: Implications for climate adaptation," Agricultural Systems, Elsevier, vol. 164(C), pages 1-10.
    16. Henzler, Julia & Weise, Hanna & Enright, Neal J. & Zander, Susanne & Tietjen, Britta, 2018. "A squeeze in the suitable fire interval: Simulating the persistence of fire-killed plants in a Mediterranean-type ecosystem under drier conditions," Ecological Modelling, Elsevier, vol. 389(C), pages 41-49.
    17. Abhiru Aryal & Albira Acharya & Ajay Kalra, 2022. "Assessing the Implication of Climate Change to Forecast Future Flood Using CMIP6 Climate Projections and HEC-RAS Modeling," Forecasting, MDPI, vol. 4(3), pages 1-22, June.
    18. Hemen Mark Butu & Yongwon Seo & Jeung Soo Huh, 2020. "Determining Extremes for Future Precipitation in South Korea Based on RCP Scenarios Using Non-Parametric SPI," Sustainability, MDPI, vol. 12(3), pages 1-26, January.
    19. Milan Ščasný & Emanuele Massetti & Jan Melichar & Samuel Carrara, 2015. "Quantifying the Ancillary Benefits of the Representative Concentration Pathways on Air Quality in Europe," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 383-415, October.
    20. Habtemariam, Lemlem Teklegiorgis & Abate Kassa, Getachew & Gandorfer, Markus, 2017. "Impact of climate change on farms in smallholder farming systems: Yield impacts, economic implications and distributional effects," Agricultural Systems, Elsevier, vol. 152(C), pages 58-66.

    More about this item

    Keywords

    GPP; climate change; CMIP6; ESM;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11744-:d:663715. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.