Climate variation explains more than half of cotton yield variability in China

文献类型： 外文期刊

第一作者： Han, Wanrui

作者： Han, Wanrui;Zhang, Yongjiang;Wang, Zhanbiao;Liu, Shengli;Feng, Lu;Li, Yabing;Wang, Zhanbiao;Wang, Jian;Lei, Yaping;Han, Yingchun;Wang, Guoping;Feng, Lu;Li, Xiaofei;Li, Yabing;Wang, Zhanbiao;Wang, Zhanbiao;Han, Wanrui

作者机构：

关键词： Climate variation; Cotton; Yield variability; Quantitative analysis; Farming adaptation

期刊名称：INDUSTRIAL CROPS AND PRODUCTS （ 影响因子：5.9； 五年影响因子：6.0 ）

ISSN： 0926-6690

年卷期： 2022 年 190 卷

页码：

收录情况： SCI

摘要： Many studies have examined the role of mean climate change in agriculture. However, the impact of interannual climate change in different regions on crop yields remains poorly understood. Here, this study combined historical climate and yield data to quantitatively analyze the effects of climate variation on cotton (Gossypium hirsutum L.) yield variability in major cotton-growing areas of China. Climate variation accounted for 54.42%, 58.10%, and 50% of the cotton yield variability in the Yellow River basin (YER), Yangtze River basin (YAR) and northwest inland (NOI), respectively. The combined effect of the three climate variables increased the cotton yields by 9.51% in the YER but decreased the yields by 6.77% and 0.45% in the YAR and NOI, respectively. In addition, the cotton yield increased mainly because the average temperature increased and the solar radiation decreased in the YER, with values of 2.82% and 5.56%, respectively. Rainfall was the main driver of the cotton yield in the YAR, and the increased rainfall reduced the cotton yield by 3.92%. In the NOI, increased solar radiation reduced the cotton yield by 3.47%. Yield variation at the provincial scale was mainly generated by complex models. Moreover, cotton yields showed nonlinear changes in most provinces, and the yield greatly fluctuated in the NOI. The study uniquely illustrates the impact of climatic variation on cotton yield variability in China and further identifies the main driving factors affecting yield variability, with the aim of formulating effective agricultural cultivation management strategies to buffer future crop production from the effects of climate change and to improve cotton production.

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