气候变化下黄土高原冬小麦潜在分布预测及冻害风险分析

doi:10.1016/j.jia.2024.02.006

Journal of Integrative Agriculture ›› 2024, Vol. 23 ›› Issue (9): 2941-2954.DOI: 10.1016/j.jia.2024.02.006

气候变化下黄土高原冬小麦潜在分布预测及冻害风险分析

收稿日期:2023-06-09 接受日期:2023-11-27 出版日期:2024-09-20 发布日期:2024-08-19

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

Qing Liang^{1, 2}, Xujing Yang^{1, 2}, Yuheng Huang^{1, 2}, Zhenwei Yang², Meichen Feng^{1, 2#}, Mingxing Qing^{2, 3}, Chao Wang^{1, 2}, Wude Yang^{1, 2}, Zhigang Wang^{1, 2}, Meijun Zhang^{1, 2}, Lujie Xiao^{1, 2}, Xiaoyan Song^{1, 2}

¹College of Agriculture, Shanxi Agricultural University, Taigu 030801, China
²Smart Agriculture College, Shanxi Agricultural University, Taigu 030801, China
³College of Resources and Environment, Shanxi Agricultural University, Taigu 030801, China

Received:2023-06-09 Accepted:2023-11-27 Online:2024-09-20 Published:2024-08-19
About author:Qing Liang, E-mail: liangqingliam@163.com; #Correspondence Meichen Feng, Tel: +86-354-6285019, E-mail: fmc101@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (31201168), the Basic Research Program of Shanxi Province, China (20210302123411), and the earmarked fund for Modern Agro-industry Technology Research System, China (2022-07).

摘要/Abstract

摘要：

了解气候变化下冬小麦的适宜区和评估冻害风险对于冬小麦的种植至关重要。本研究利用优化的MaxEnt模型预测4种共享社会经济路径下当前时期（1970—2020年）和未来时期（2021—2100年）冬小麦的潜在地理分布。采用统计降尺度方法对未来气候数据进行降尺度处理，考虑冬小麦生育期建立科学实用的冻害指数（FII），并利用M-K检验分析冬小麦冻害突变特征。结果表明，优化的MaxEnt模型预测精度AUC值为0.976；影响冬小麦空间分布范围的主要环境变量是最冷月份最低温、最湿季节降水量和年降水量；冬小麦总适宜区面积约为4.40×10⁷hm²。在2070年代，中等适宜区面积在SSP245下增幅最大，为9.02×10⁵hm²，在SSP370下增幅最小，为6.53×10⁵hm²。总适宜区质心坐标有北移趋势。黄土高原高纬度高海拔地区冻害的潜在风险显著增加，山西忻州北部冻害最严重，黄土高原南部冻害最轻。温度、降水、地理位置等环境因子对冬小麦适宜区分布和冻害风险有重要影响。未来应更加关注冬小麦种植区北界和冻害风险区，提供冻害预警和相应的管理策略。

Abstract:

Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat. We used an optimized Maximum Entropy (MaxEnt) Model to predict the potential distribution of winter wheat in the current period (1970–2020) and the future period (2021–2100) under four shared socioeconomic pathway scenarios (SSPs). We applied statistical downscaling methods to downscale future climate data, established a scientific and practical freezing injury index (FII) by considering the growth period of winter wheat, and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall (M-K) test. The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976. The minimum temperature in the coldest month, precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat. The total suitable area of winter wheat was approximately 4.40×10⁷ ha in the current period. In the 2070s, the moderately suitable areas had the greatest increase by 9.02×10⁵ ha under SSP245 and the least increase by 6.53×10⁵ ha under SSP370. The centroid coordinates of the total suitable areas tended to move northward. The potential risks of freezing injury in the high-latitude and -altitude areas of the Loess Plateau, China increased significantly. The northern areas of Xinzhou in Shanxi Province, China suffered the most serious freezing injury, and the southern areas of the Loess Plateau suffered the least. Environmental factors such as temperature, precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat. In the future, greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

Key words: climate change scenarios , winter wheat , freezing injury risk , downscaling , MaxEnt

Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang, Lujie Xiao, Xiaoyan Song. 气候变化下黄土高原冬小麦潜在分布预测及冻害风险分析[J]. Journal of Integrative Agriculture, 2024, 23(9): 2941-2954.

Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang, Lujie Xiao, Xiaoyan Song. Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change[J]. Journal of Integrative Agriculture, 2024, 23(9): 2941-2954.

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气候变化下黄土高原冬小麦潜在分布预测及冻害风险分析

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

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