Uncovering the Drivers and Regional Variability of Cotton Yield in China

Yaqiu Zhu, Bangyou Zheng, Qiyou Luo, Weihua Jiao and Yadong Yang ()
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Yaqiu Zhu: State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Bangyou Zheng: CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Queensland 4067, Australia
Qiyou Luo: State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Weihua Jiao: School of Economics, Shandong University of Finance and Economics, Jinan 250014, China
Yadong Yang: State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Agriculture, 2023, vol. 13, issue 11, 1-16

Abstract: Cotton ( Gossypium hirsutum L.) is an economically important crop in China, and responses of cotton yield in different regions to separate and joint changes in natural and anthropogenic factors are the foundation for sustainable development under climate change; however, these remain uncertain. Here, we analyzed the spatiotemporal evolution and heterogeneity of cotton cultivation in China from 1949 to 2020 and quantified the response of cotton yield variations in air temperature, precipitation, solar radiation, disaster, and crop management factors between 1980 and 2020 by the Pettitt mutation test and GeoDetector. Multi-site meteorological data were obtained from different cotton-growing regions and corresponding cotton yield and phenology data were obtained from provinces. Our findings showed that all 17 Chinese provinces experienced advancements in cotton yield. Relative to 1949–1967, China’s cotton production in 2007–2020 increased by 400% while cotton yield increased by 420%. Increases in factors such as minimum temperature (TES), average temperature (ADT), effective accumulated temperature (EAT), precipitation (PP), daily solar radiation (SSD), non-farm employment opportunities (O), disaster area (D), geographic region (GEO) and agricultural technologies like fertilizer usage (F), genetically modified varieties (Bt), and mechanized farming (M) have contributed to the enhanced cotton yield. The importance of single factors influencing cotton yield of China in descending order was as follows: F > Bt > M > GEO > EAT > O > PP > TES > ADT > SSD > D. However, the effects of different climatic and agriculture technological elements on cotton yield are spatially heterogeneous by region, and the combined effects of those elements are higher than those of single elements. The effects of driving factors vary across regional scales. The most significant interaction effects were observed between chemical fertilizer use and other driving factors. Specifically, the interaction between F and TES has the greatest explanatory influence in Northwest China. Our findings provide a reference for the development of more accurate adaptation strategies and management measures in different regions. We recommend that policymakers prioritize measures such as improving climate-resilient cotton varieties, encouraging technological advancements, and implementing policies that support equitable distribution of cultivation.

Keywords: climate change; cotton phenology; technological advancement; minimum temperature; GeoDetector (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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