IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10606-d1187511.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10606/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/10606/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    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. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    2. Govind, Ajit & Chen, Jing Ming & Bernier, Pierre & Margolis, Hank & Guindon, Luc & Beaudoin, Andre, 2011. "Spatially distributed modeling of the long-term carbon balance of a boreal landscape," Ecological Modelling, Elsevier, vol. 222(15), pages 2780-2795.
    3. Eliseev, Alexey V. & Mokhov, Igor I., 2008. "Eventual saturation of the climate–carbon cycle feedback studied with a conceptual model," Ecological Modelling, Elsevier, vol. 213(1), pages 127-132.
    4. Brovkin, Victor & Cherkinsky, Alexander & Goryachkin, Sergey, 2008. "Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia," Ecological Modelling, Elsevier, vol. 216(2), pages 178-187.
    5. Ulaganathan, Kandasamy & Goud, Sravanthi & Reddy, Madhavi & Kayalvili, Ulaganathan, 2017. "Genome engineering for breaking barriers in lignocellulosic bioethanol production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1080-1107.
    6. Brazhnik, Ksenia & Shugart, H.H., 2016. "SIBBORK: A new spatially-explicit gap model for boreal forest," Ecological Modelling, Elsevier, vol. 320(C), pages 182-196.
    7. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
    8. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    9. Ouardighi, Fouad El & Sim, Jeong Eun & Kim, Bowon, 2016. "Pollution accumulation and abatement policy in a supply chain," European Journal of Operational Research, Elsevier, vol. 248(3), pages 982-996.
    10. Kim, Hyeyoung & House, Lisa A. & KIm, Tae-Kyun, 2016. "Consumer perceptions of climate change and willingness to pay for mandatory implementation of low carbon labels: the case of South Korea," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(4), October.
    11. Guoju, Xiao & Weixiang, Liu & Qiang, Xu & Zhaojun, Sun & Jing, Wang, 2005. "Effects of temperature increase and elevated CO2 concentration, with supplemental irrigation, on the yield of rain-fed spring wheat in a semiarid region of China," Agricultural Water Management, Elsevier, vol. 74(3), pages 243-255, June.
    12. Sogol Moradian & Farhad Yazdandoost, 2021. "Seasonal meteorological drought projections over Iran using the NMME data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1089-1107, August.
    13. Viola, Flavio M. & Paiva, Susana L.D. & Savi, Marcelo A., 2010. "Analysis of the global warming dynamics from temperature time series," Ecological Modelling, Elsevier, vol. 221(16), pages 1964-1978.
    14. Farrelly, Damien J. & Everard, Colm D. & Fagan, Colette C. & McDonnell, Kevin P., 2013. "Carbon sequestration and the role of biological carbon mitigation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 712-727.
    15. Marc Kennedy & Clive Anderson & Anthony O'Hagan & Mark Lomas & Ian Woodward & John Paul Gosling & Andreas Heinemeyer, 2008. "Quantifying uncertainty in the biospheric carbon flux for England and Wales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 109-135, January.
    16. Yonghua Li & Song Yao & Hezhou Jiang & Huarong Wang & Qinchuan Ran & Xinyun Gao & Xinyi Ding & Dandong Ge, 2022. "Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China," Land, MDPI, vol. 11(12), pages 1-22, December.
    17. Sara J. Germain & James A. Lutz, 2020. "Climate extremes may be more important than climate means when predicting species range shifts," Climatic Change, Springer, vol. 163(1), pages 579-598, November.
    18. Xiongwen Chen & Wilfred Post & Richard Norby & Aimée Classen, 2011. "Modeling soil respiration and variations in source components using a multi-factor global climate change experiment," Climatic Change, Springer, vol. 107(3), pages 459-480, August.
    19. Wang, Tao & Yu, Wei & Le Moullec, Yann & Liu, Fei & Xiong, Yili & He, Hui & Lu, Jiahui & Hsu, Emily & Fang, Mengxiang & Luo, Zhongyang, 2017. "Solvent regeneration by novel direct non-aqueous gas stripping process for post-combustion CO2 capture," Applied Energy, Elsevier, vol. 205(C), pages 23-32.
    20. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.

    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:15:y:2023:i:13:p:10606-:d:1187511. 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.