Variability in Crop Response to Spatiotemporal Variation in Climate in China, 1980–2014

Junjun Cao, Guoyong Leng, Peng Yang, Qingbo Zhou and Wenbin Wu
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Junjun Cao: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Guoyong Leng: Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Peng Yang: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Qingbo Zhou: Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Wenbin Wu: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Land, 2022, vol. 11, issue 8, 1-13

Abstract: As the population increases and climate extremes become more frequent, the pressure on food supply increases. A better understanding of the influence of climate variations on crop yield in China would be of great benefit to global food security. In this study, gridded, daily meteorological data and county-level annual yield data were used to quantify the climate sensitivity of corn, rice, and spring wheat yields, and identify the spatiotemporal variation relationship between climate and yields from 1980 to 2014. The results showed that rice and corn were more sensitive to climate variations than spring wheat, both spatially and temporally. Photosynthetic active radiation (PAR) was found to be beneficial to rice in northeast China and the Yangtze River basin, as well as corn in the south and spring wheat in Xinjiang, but not to rice in the south of the Yangtze River and spring wheat in the southeast coast. The temperature centroid shift was the main driving factor causing the movement of the centroid of the three crops. For every 1 km shift of the temperature centroid, the corn and rice yield centroids moved 0.97 km and 0.34 km, respectively. These findings improve our understanding of the impacts of climate variations on agricultural yields in different regions of China.

Keywords: crop; climate variability; spatiotemporal; centroids; spatial heterogeneity (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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