Spatio-temporal evolution of climate-induced reduction risk for winter wheat in Anhui Pro-vince based on principal component analysis

doi:10.13287/j.1001-9332.202109.016

Abstract

Abstract: Winter wheat is one of the main crops in Anhui Province, to analyze the spatial-temporal variations of climate-induced reduction risk is of great significance to ensure regional food security. Based on the data of winter wheat yield from 1973 to 2014 in 74 districts and counties, nine risk assessment indicators were extracted from annual series of climate-induced reduction rate, and the spatial-temporal variations of climate-induced reduction risk for winter wheat in Anhui was analyzed by using principal component analysis. The results showed that north Anhui, especially the region along Huaihe River, was the higher-risk area for climate-induced yield loss. Results of the barycenter migration model showed that the high value regions of climate-induced reduction rate of winter wheat in Anhui Province had a significant tendency of moving from north to south. In the whole province, climate-induced reduction risk of winter wheat presented a significant interdecadal variation. Furthermore, the number of districts and counties with moderate or more reduction intensity was significantly reducing since the 2000s. Results from S-mode principal component analysis and climate-induced reduction rate series showed that the climate-induced reduction risk for winter wheat in north Anhui had a downward trend and that in southern Anhui had an upward trend. Climate-induced reduction risk of winter wheat in Anhui had notable temporal and spatial variations, the interdecadal fluctuation and north-south regional difference of which should draw our attention.

Key words: winter wheat, Anhui Province, climate-induced reduction risk, principal component analysis

HUANG Jin, CHEN Jin-hua, ZHANG Fang-min. Spatio-temporal evolution of climate-induced reduction risk for winter wheat in Anhui Pro-vince based on principal component analysis[J]. Chinese Journal of Applied Ecology, 2021, 32(9): 3185-3194.

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