Analysis of Spatiotemporal Differences and Dynamic Evolution of Grain Production Resilience Based on Spatial Markov Chains
Improving the resilience of food production is of great significance to ensure food secu-rity and accelerate the construction of an agricultural power.Based on China's provincial panel data from 2005 to 2021,the evaluation index system of grain production resilience was constructed to measure the resilience level.And on this basis,the spatiotemporal dynamic evolution of the grain production was ana-lyzed in depth followed by the trend prediction.The results are as follows:First,the overall level of food production resilience in China showed a year-on-year improvement trend during the study period,al-though the growth rate has slowed down in recent years.Second,there are obvious differences in the re-silience of grain production among provinces,generally displaying a pattern of"being high in the east and low in the west"and the overall gap gradually widens during the study period.The main source of overall differences lies in regional disparities,but since 2017,interregional differences have gradually de-creased,with intra-regional differences becoming the main cause of overall disparities.The problem of unbalanced development between sub-regions is more severe with obvious differences between provinces within the region.Third,there is a significant spatial correlation in the resilience of grain production in China,showing obvious characteristics of high-high and low-low agglomeration,where high-level prov-inces are mostly adjacent to one or more high-level provinces,while low-level provinces are mostly neighboring low-level provinces.Fourth,it is difficult for provinces to achieve a hierarchical leap in the resilience of food production in the short term.However,after the introduction of spatial and geographi-cal factors,the stable state of grain production resilience has a tendency to fluctuate,often exhibiting a Matthew effect where"the strong remain strong and the weak remain weak".
NETL
NSTL
万方数据
维普
