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

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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Qunying Luo, 2011. "Temperature thresholds and crop production: a review," Climatic Change, Springer, vol. 109(3), pages 583-598, December.
    4. Neville Nicholls, 1997. "Increased Australian wheat yield due to recent climate trends," Nature, Nature, vol. 387(6632), pages 484-485, May.
    5. 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.
    6. 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.
    7. 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.
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