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Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China

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  • Huang, Mingxia
  • Wang, Jing
  • Wang, Bin
  • Liu, De Li
  • Feng, Puyu
  • Yu, Qiang
  • Pan, Xuebiao
  • Li, Siyi
  • Jiang, Tengcong

Abstract

The potential of climate adaptation has been widely investigated with a climate-crop modeling approach. Although different sources of uncertainty in projected crop yields have been quantified in climate change impact assessments, uncertainty in simulating the crop adaptation to future climate has not been fully assessed.

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  • Huang, Mingxia & Wang, Jing & Wang, Bin & Liu, De Li & Feng, Puyu & Yu, Qiang & Pan, Xuebiao & Li, Siyi & Jiang, Tengcong, 2022. "Dominant sources of uncertainty in simulating maize adaptation under future climate scenarios in China," Agricultural Systems, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:agisys:v:199:y:2022:i:c:s0308521x22000476
    DOI: 10.1016/j.agsy.2022.103411
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    References listed on IDEAS

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    1. Xiao, Dengpan & Liu, De Li & Wang, Bin & Feng, Puyu & Waters, Cathy, 2020. "Designing high-yielding maize ideotypes to adapt changing climate in the North China Plain," Agricultural Systems, Elsevier, vol. 181(C).
    2. Belay Kassie & Senthold Asseng & Reimund Rotter & Huib Hengsdijk & Alex Ruane & Martin Ittersum, 2015. "Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models," Climatic Change, Springer, vol. 129(1), pages 145-158, March.
    3. Ma, Wenqi & Li, Jianhui & Ma, Lin & Wang, Fanghao & Sisák, István & Cushman, Gregory & Zhang, Fusuo, 2008. "Nitrogen flow and use efficiency in production and utilization of wheat, rice, and maize in China," Agricultural Systems, Elsevier, vol. 99(1), pages 53-63, December.
    4. S. Asseng & F. Ewert & C. Rosenzweig & J. W. Jones & J. L. Hatfield & A. C. Ruane & K. J. Boote & P. J. Thorburn & R. P. Rötter & D. Cammarano & N. Brisson & B. Basso & P. Martre & P. K. Aggarwal & C., 2013. "Uncertainty in simulating wheat yields under climate change," Nature Climate Change, Nature, vol. 3(9), pages 827-832, September.
    5. Bin Wang & De Li Liu & Cathy Waters & Qiang Yu, 2018. "Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia," Climatic Change, Springer, vol. 151(2), pages 259-273, November.
    6. Parkes, Ben & Higginbottom, Thomas P. & Hufken, Koen & Ceballos, Francisco & Kramer, Berber & Foster, Timothy, 2019. "Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change:," IFPRI discussion papers 1870, International Food Policy Research Institute (IFPRI).
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    Cited by:

    1. Chen, Fangzheng & Xu, Xinlei & Chen, Shaoqing & Wang, Zihan & Wang, Bin & Zhang, Yajie & Zhang, Chenxia & Feng, Puyu & Hu, Kelin, 2024. "Soil buffering capacity enhances maize yield resilience amidst climate perturbations," Agricultural Systems, Elsevier, vol. 215(C).
    2. Dahri, Shahzad Hussain & Shaikh, Irfan Ahmed & Talpur, Mashooque Ali & Mangrio, Munir Ahmed & Dahri, Zakir Hussain & Hoogenboom, Gerrit & Knox, Jerry W., 2024. "Modelling the impacts of climate change on the sustainability of rainfed and irrigated maize in Pakistan," Agricultural Water Management, Elsevier, vol. 296(C).
    3. Ennan Zheng & Mengting Qin & Peng Chen & Tianyu Xu & Zhongxue Zhang, 2022. "Climate Change Affects the Utilization of Light and Heat Resources in Paddy Field on the Songnen Plain, China," Agriculture, MDPI, vol. 12(10), pages 1-19, October.
    4. Jiang, Tengcong & Wang, Bin & Duan, Xiaoning & Liu, De Li & He, Jianqiang & He, Liang & Jin, Ning & Feng, Hao & Yu, Qiang, 2023. "Prioritizing agronomic practices and uncertainty assessment under climate change for winter wheat in the loess plateau, China," Agricultural Systems, Elsevier, vol. 212(C).

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