IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i23p6659-d290641.html
   My bibliography  Save this article

Different Time Windows Provide Divergent Estimates of Climate Variability and Change Impacts on Maize Yield in Northeast China

Author

Listed:
  • Xi Deng

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yao Huang

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Wenjuan Sun

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China)

  • Lingfei Yu

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China)

  • Xunyu Hu

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Sheng Wang

    (State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Maize is the main crop in Northeast China (NEC), but is susceptible to climate variations. Using county-level data from 1980 to 2010, we established multiple linear regression models between detrended changes in maize yield and climate variables at two time windows—whole-season and vegetative and reproductive (V&R) phases. Based on climate change trends, these regression models were used to assess climate variability and change impacts on maize yield in different regions of NEC. The results show that different time windows provide divergent estimates. Climate change over the 31 years induced a 1.3% reduction in maize yield at the time window of whole-season, but an increase of 9.1% was estimated at the time window of V&R phases. The yield improvement is attributed to an increase in minimum temperature at the vegetative phase when the temperatures were much lower than the optimum. Yield fluctuations due to inter-annual climate variability were estimated to be ±9% per year at the time window of V&R phases, suggesting that the impact of climate variability on maize yield is much greater than climate change. Trends in precipitation were not responsible for the yield change, but precipitation anomalies contributed to the yield fluctuations. The impacts of warming on maize yield are regional specific, depending on the local temperatures relative to the optimum. Increase in maximum temperature led to a reduction of maize yield in western NEC, but to an increase in mid-east part of NEC. Our findings highlight the necessity of taking into account the phenological phase when assessing the climate impacts on crop yield, and the importance of buffering future crop production from climate change in NEC.

Suggested Citation

  • Xi Deng & Yao Huang & Wenjuan Sun & Lingfei Yu & Xunyu Hu & Sheng Wang, 2019. "Different Time Windows Provide Divergent Estimates of Climate Variability and Change Impacts on Maize Yield in Northeast China," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6659-:d:290641
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/23/6659/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/23/6659/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qunying Luo, 2011. "Temperature thresholds and crop production: a review," Climatic Change, Springer, vol. 109(3), pages 583-598, December.
    2. Corey Lesk & Pedram Rowhani & Navin Ramankutty, 2016. "Influence of extreme weather disasters on global crop production," Nature, Nature, vol. 529(7584), pages 84-87, January.
    3. Deepak K. Ray & James S. Gerber & Graham K. MacDonald & Paul C. West, 2015. "Climate variation explains a third of global crop yield variability," Nature Communications, Nature, vol. 6(1), pages 1-9, May.
    4. Qingfeng Meng & Peng Hou & David Lobell & Hongfei Wang & Zhenling Cui & Fusuo Zhang & Xinping Chen, 2014. "The benefits of recent warming for maize production in high latitude China," Climatic Change, Springer, vol. 122(1), pages 341-349, January.
    5. Shilong Piao & Philippe Ciais & Yao Huang & Zehao Shen & Shushi Peng & Junsheng Li & Liping Zhou & Hongyan Liu & Yuecun Ma & Yihui Ding & Pierre Friedlingstein & Chunzhen Liu & Kun Tan & Yongqiang Yu , 2010. "The impacts of climate change on water resources and agriculture in China," Nature, Nature, vol. 467(7311), pages 43-51, September.
    6. Neville Nicholls, 1997. "Increased Australian wheat yield due to recent climate trends," Nature, Nature, vol. 387(6632), pages 484-485, May.
    7. Mansouri-Far, Cyrus & Modarres Sanavy, Seyed Ali Mohammad & Saberali, Seyed Farhad, 2010. "Maize yield response to deficit irrigation during low-sensitive growth stages and nitrogen rate under semi-arid climatic conditions," Agricultural Water Management, Elsevier, vol. 97(1), pages 12-22, January.
    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. Wang, Teng & Yi, Fujin & Liu, Huilin & Wu, Ximing & Zhong, Funing, 2021. "Can Agricultural Mechanization Have a Mitigation Effect on China's Yield Variability?," 2021 Conference, August 17-31, 2021, Virtual 315098, International Association of Agricultural Economists.
    2. Wang, Jianqing & Liu, Xiaoyu & Cheng, Kun & Zhang, Xuhui & Li, Lianqing & Pan, Genxing, 2018. "Winter wheat water requirement and utilization efficiency under simulated climate change conditions: A Penman-Monteith model evaluation," Agricultural Water Management, Elsevier, vol. 197(C), pages 100-109.
    3. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    4. Shahzad, Muhammad Faisal & Abdulai, Awudu, 2020. "Adaptation to extreme weather conditions and farm performance in rural Pakistan," Agricultural Systems, Elsevier, vol. 180(C).
    5. Robert Becker Pickson & Ge He & Elliot Boateng, 2022. "Impacts of climate change on rice production: evidence from 30 Chinese provinces," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3907-3925, March.
    6. Bucheli, Janic & Visse, Margot & Herrera, Juan & Häner, Lilia Levy & Tack, Jesse & Finger, Robert, 2022. "Precipitation causes quality losses of economic relevance in wheat production," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321208, Agricultural Economics Society - AES.
    7. Taoyuan Wei & Solveig Glomsrød & Tianyi Zhang, 2017. "Extreme weather, food security and the capacity to adapt – the case of crops in China," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(3), pages 523-535, June.
    8. Huili Chen & Zhongyao Liang & Yong Liu & Qingsong Jiang & Shuguang Xie, 2018. "Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling," 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. 92(1), pages 525-541, May.
    9. Chen, Xiaoping & Qi, Zhiming & Gui, Dongwei & Gu, Zhe & Ma, Liwang & Zeng, Fanjiang & Li, Lanhai, 2019. "Simulating impacts of climate change on cotton yield and water requirement using RZWQM2," Agricultural Water Management, Elsevier, vol. 222(C), pages 231-241.
    10. Florian Schierhorn & Max Hofmann & Taras Gagalyuk & Igor Ostapchuk & Daniel Müller, 2021. "Machine learning reveals complex effects of climatic means and weather extremes on wheat yields during different plant developmental stages," Climatic Change, Springer, vol. 169(3), pages 1-19, December.
    11. Su, Zheng’e & Zhao, Jin & Marek, Thomas H. & Liu, Ke & Harrison, Matthew Tom & Xue, Qingwu, 2022. "Drought tolerant maize hybrids have higher yields and lower water use under drought conditions at a regional scale," Agricultural Water Management, Elsevier, vol. 274(C).
    12. Feng, Puyu & Wang, Bin & Liu, De Li & Yu, Qiang, 2019. "Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia," Agricultural Systems, Elsevier, vol. 173(C), pages 303-316.
    13. Tan, Lili & Feng, Puyu & Li, Baoguo & Huang, Feng & Liu, De Li & Ren, Pinpin & Liu, Haipeng & Srinivasan, Raghavan & Chen, Yong, 2022. "Climate change impacts on crop water productivity and net groundwater use under a double-cropping system with intensive irrigation in the Haihe River Basin, China," Agricultural Water Management, Elsevier, vol. 266(C).
    14. Chatzopoulos, Thomas & Domínguez, Ignacio Pèrez & Zampieri, Matteo & Toreti, Andrea, 2017. "Extreme Weather and Global Agricultural Markets: Experimental Analysis of the Impacts of Heat Waves on Wheat Markets," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 2017(1), June.
    15. Shengli Liu & Wenbin Wu & Xiaoguang Yang & Peng Yang & Jing Sun, 2020. "Exploring drought dynamics and its impacts on maize yield in the Huang-Huai-Hai farming region of China," Climatic Change, Springer, vol. 163(1), pages 415-430, November.
    16. Emilie Stokeld & Simon A. Croft & Jonathan M. H. Green & Christopher D. West, 2020. "Climate change, crops and commodity traders: subnational trade analysis highlights differentiated risk exposure," Climatic Change, Springer, vol. 162(2), pages 175-192, September.
    17. Ching-Pong Poo, Mark & Wang, Tianni & Yang, Zaili, 2024. "Global food supply chain resilience assessment: A case in the United Kingdom," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    18. Junjun Cao & Guoyong Leng & Peng Yang & Qingbo Zhou & Wenbin Wu, 2022. "Variability in Crop Response to Spatiotemporal Variation in Climate in China, 1980–2014," Land, MDPI, vol. 11(8), pages 1-13, July.
    19. Yan, Dan & Liu, Litao & Li, Jinkai & Wu, Jiaqian & Qin, Wei & Werners, Saskia E., 2021. "Are the planning targets of liquid biofuel development achievable in China under climate change?," Agricultural Systems, Elsevier, vol. 186(C).
    20. Ngawang Chhogyel & Lalit Kumar & Yadunath Bajgai, 2020. "Consequences of Climate Change Impacts and Incidences of Extreme Weather Events in Relation to Crop Production in Bhutan," Sustainability, MDPI, vol. 12(10), pages 1-18, May.

    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:11:y:2019:i:23:p:6659-:d:290641. 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.