IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i11p2132-d1278475.html
   My bibliography  Save this article

Uncovering the Drivers and Regional Variability of Cotton Yield in China

Author

Listed:
  • Yaqiu Zhu

    (State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Bangyou Zheng

    (CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Queensland 4067, Australia)

  • Qiyou Luo

    (State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

  • Weihua Jiao

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Yadong Yang

    (State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

Abstract

Cotton ( Gossypium hirsutum L.) is an economically important crop in China, and responses of cotton yield in different regions to separate and joint changes in natural and anthropogenic factors are the foundation for sustainable development under climate change; however, these remain uncertain. Here, we analyzed the spatiotemporal evolution and heterogeneity of cotton cultivation in China from 1949 to 2020 and quantified the response of cotton yield variations in air temperature, precipitation, solar radiation, disaster, and crop management factors between 1980 and 2020 by the Pettitt mutation test and GeoDetector. Multi-site meteorological data were obtained from different cotton-growing regions and corresponding cotton yield and phenology data were obtained from provinces. Our findings showed that all 17 Chinese provinces experienced advancements in cotton yield. Relative to 1949–1967, China’s cotton production in 2007–2020 increased by 400% while cotton yield increased by 420%. Increases in factors such as minimum temperature (TES), average temperature (ADT), effective accumulated temperature (EAT), precipitation (PP), daily solar radiation (SSD), non-farm employment opportunities (O), disaster area (D), geographic region (GEO) and agricultural technologies like fertilizer usage (F), genetically modified varieties (Bt), and mechanized farming (M) have contributed to the enhanced cotton yield. The importance of single factors influencing cotton yield of China in descending order was as follows: F > Bt > M > GEO > EAT > O > PP > TES > ADT > SSD > D. However, the effects of different climatic and agriculture technological elements on cotton yield are spatially heterogeneous by region, and the combined effects of those elements are higher than those of single elements. The effects of driving factors vary across regional scales. The most significant interaction effects were observed between chemical fertilizer use and other driving factors. Specifically, the interaction between F and TES has the greatest explanatory influence in Northwest China. Our findings provide a reference for the development of more accurate adaptation strategies and management measures in different regions. We recommend that policymakers prioritize measures such as improving climate-resilient cotton varieties, encouraging technological advancements, and implementing policies that support equitable distribution of cultivation.

Suggested Citation

  • Yaqiu Zhu & Bangyou Zheng & Qiyou Luo & Weihua Jiao & Yadong Yang, 2023. "Uncovering the Drivers and Regional Variability of Cotton Yield in China," Agriculture, MDPI, vol. 13(11), pages 1-16, November.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:11:p:2132-:d:1278475
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/11/2132/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/11/2132/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alvaro Calzadilla & Katrin Rehdanz & Richard Betts & Pete Falloon & Andy Wiltshire & Richard Tol, 2013. "Climate change impacts on global agriculture," Climatic Change, Springer, vol. 120(1), pages 357-374, September.
    2. Lijun Zuo & Zengxiang Zhang & Kimberly M. Carlson & Graham K. MacDonald & Kate A. Brauman & Yingchun Liu & Wen Zhang & Huayong Zhang & Wenbin Wu & Xiaoli Zhao & Xiao Wang & Bin Liu & Ling Yi & Qingke , 2018. "Progress towards sustainable intensification in China challenged by land-use change," Nature Sustainability, Nature, vol. 1(6), pages 304-313, June.
    3. Umberto Lombardo & José Iriarte & Lautaro Hilbert & Javier Ruiz-Pérez & José M. Capriles & Heinz Veit, 2020. "Early Holocene crop cultivation and landscape modification in Amazonia," Nature, Nature, vol. 581(7807), pages 190-193, May.
    4. Florian Zabel & Ruth Delzeit & Julia M. Schneider & Ralf Seppelt & Wolfram Mauser & Tomáš Václavík, 2019. "Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    5. Charlotte L. Outhwaite & Peter McCann & Tim Newbold, 2022. "Agriculture and climate change are reshaping insect biodiversity worldwide," Nature, Nature, vol. 605(7908), pages 97-102, May.
    6. Song, Ge & Ren, Gaofeng, 2022. "Spatial response of cultivated land use efficiency to the maize structural adjustment policy in the "Sickle Bend" region of China: An empirical study from the cold area of northeast," Land Use Policy, Elsevier, vol. 123(C).
    7. Hu, Yajin & Ma, Penghui & Wu, Shufang & Sun, Benhua & Feng, Hao & Pan, Xiaolian & Zhang, Binbin & Chen, Guangjie & Duan, Chenxiao & Lei, Qi & Siddique, Kadambot H.M. & Liu, Boyang, 2020. "Spatial-temporal distribution of winter wheat (Triticum aestivum L.) roots and water use efficiency under ridge–furrow dual mulching," Agricultural Water Management, Elsevier, vol. 240(C).
    8. Gollini, Isabella & Lu, Binbin & Charlton, Martin & Brunsdon, Christopher & Harris, Paul, 2015. "GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i17).
    9. Li, Na & Yao, Ning & Li, Yi & Chen, Junqing & Liu, Deli & Biswas, Asim & Li, Linchao & Wang, Tianxue & Chen, Xinguo, 2021. "A meta-analysis of the possible impact of climate change on global cotton yield based on crop simulation approaches," Agricultural Systems, Elsevier, vol. 193(C).
    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. Jason F.L. Koopman & Onno Kuik & Richard S.J. Tol & Roy Brouwer, 2015. "Water Scarcity From Climate Change And Adaptation Response In An International River Basin Context," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-22.
    2. Qiu, Bingwen & Li, Haiwen & Tang, Zhenghong & Chen, Chongcheng & Berry, Joe, 2020. "How cropland losses shaped by unbalanced urbanization process?," Land Use Policy, Elsevier, vol. 96(C).
    3. Argueyrolles, Robin & Delzeit, Ruth, 2022. "The interconnections between Fossil Fuel Subsidy Reforms and biofuels," Conference papers 333492, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Zvi Baum & Ruslana Rachel Palatnik & Iddo Kan & Mickey Rapaport-Rom, 2016. "Economic Impacts of Water Scarcity Under Diverse Water Salinities," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 1-22, March.
    5. Jincai Zhao & Yiyao Wang & Xiufeng Zhang & Qianxi Liu, 2022. "Industrial and Agricultural Water Use Efficiency and Influencing Factors in the Process of Urbanization in the Middle and Lower Reaches of the Yellow River Basin, China," Land, MDPI, vol. 11(8), pages 1-18, August.
    6. Sheng, Yu & Zhao, Shiji & Yang, Sansi, 2021. "Weather shocks, adaptation and agricultural TFP: A cross-region comparison of Australian Broadacre farms," Energy Economics, Elsevier, vol. 101(C).
    7. Gainbi Park & Zengwang Xu, 2022. "The constituent components and local indicator variables of social vulnerability index," 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. 110(1), pages 95-120, January.
    8. Wu, Lihong & Quan, Hao & Wu, Lina & Zhang, Xi & Feng, Hao & Ding, Dianyuan & Siddique, Kadambot H.M., 2023. "Responses of winter wheat yield and water productivity to sowing time and plastic mulching in the Loess Plateau," Agricultural Water Management, Elsevier, vol. 289(C).
    9. Zaijun Li & Jianquan Cheng & Qiyan Wu, 2016. "Analyzing regional economic development patterns in a fast developing province of China through geographically weighted principal component analysis," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 233-245, October.
    10. Han, Bo & Jin, Xiaobin & Sun, Rui & Li, Hanbing & Liang, Xinyuan & Zhou, Yinkang, 2023. "Understanding land-use sustainability with a systematical framework: An evaluation case of China," Land Use Policy, Elsevier, vol. 132(C).
    11. Andréia S. Santos & Lucas Teles Faria & Mara Lúcia M. Lopes & Carlos R. Minussi, 2023. "Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges," Energies, MDPI, vol. 16(23), pages 1-19, November.
    12. Asfaw, S., 2018. "Market Participation, Weather Shocks and Welfare: Evidence from Malawi," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277029, International Association of Agricultural Economists.
    13. Xinbei Huang & Chengming Ye & Hongyu Tao & Junjie Zou & Yuzhan Zhou & Shufan Zheng, 2024. "Integrating Future Multi-Scenarios to Evaluate the Effectiveness of Ecological Restoration: A Case Study of the Yellow River Basin," Land, MDPI, vol. 13(7), pages 1-19, July.
    14. Chen, Feifei & Qiu, Huanguang & Zhao, Yilin & Wei, Xun & Wan, Xiangyuan, 2024. "Impact of new maize variety adoption on yield and fertilizer input in China: Implications for sustainable food and agriculture," Agricultural Systems, Elsevier, vol. 218(C).
    15. Verena Preusse & Nils Nölke & Meike Wollni, 2024. "Urbanization and adoption of sustainable agricultural practices in the rural‐urban interface of Bangalore, India," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(2), pages 167-198, June.
    16. Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.
    17. Victor Nechifor & Matthew Winning, 2017. "The impacts of higher CO2 concentrations over global crop production and irrigation water requirements," EcoMod2017 10487, EcoMod.
    18. Alexis Comber & Paul Harris, 2018. "Geographically weighted elastic net logistic regression," Journal of Geographical Systems, Springer, vol. 20(4), pages 317-341, October.
    19. Mikémina Pilo & Nicolas Gerber & Tobias Wünscher, 2021. "Impacts of Adaptation to Climate Change on Farmers’ Income in the Savanna Region of Togo," Revue économique, Presses de Sciences-Po, vol. 72(3), pages 421-442.
    20. Maamoun, Nada & Grünhagen, Caroline & Ward, Hauke & Kornek, Ulrike, 2024. "A Seat at the Table: Distributional impacts of food-price increases due to climate change," EconStor Preprints 281165, ZBW - Leibniz Information Centre for Economics.

    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:jagris:v:13:y:2023:i:11:p:2132-:d:1278475. 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.