Cropland plays a crucial role in agricultural production,significantly impacting crop yield,quality,and the sustainable development of agricultural ecosystems.This study establishes an evaluation index system to asses...Cropland plays a crucial role in agricultural production,significantly impacting crop yield,quality,and the sustainable development of agricultural ecosystems.This study establishes an evaluation index system to assess cropland quality using panel data from 30 Chinese provinces.The research employs the entropy method to quantify cropland quality,the Dagum Gini coefficient to investigate the sources of disparities in cropland quality and the development quality of its subsystems,and various analytical techniques including Kernel density estimation,Markov chains,and spatial convergence to examine the distribution dynamics and evolutionary trends of cropland quality.The findings reveal a consistent upward trend in overall cropland quality in China over the years,with a relatively low Gini coefficient,indicating minor quality fluctuations.Notably,the inter-regional Gini coefficient is highest between China’s eastern and western regions and lowest between the western and northeastern regions.Moreover,the Gini coefficients show an increasing trend among the eastern-central,eastern-western,easternnortheastern,and central-western regions.Regarding distribution dynamics,the absolute disparities in cropland quality among the eastern,central,and northeastern regions are decreasing but widening in the western region,suggesting a polarization effect among the four major regions,albeit with a tendency towards reduction.The findings from the Markov chain analysis indicate that cropland quality in China tends to be stable,making leapfrog development challenging.From a spatial convergence perspective,theσcoefficient is relatively high for the entire country;however,the western region exhibits a lowerσcoefficient.The consistently significant negativeβvalue indicates the presence of absoluteβconvergence,conditionalβconvergence,spatial absoluteβconvergence,and spatial conditionalβconvergence in the cropland quality index across China and its two major regions,with variations in convergence rates and cycles observed at both national and regional levels.展开更多
基金The National Social Science Fund of China(24BJY163)。
摘要Cropland plays a crucial role in agricultural production,significantly impacting crop yield,quality,and the sustainable development of agricultural ecosystems.This study establishes an evaluation index system to assess cropland quality using panel data from 30 Chinese provinces.The research employs the entropy method to quantify cropland quality,the Dagum Gini coefficient to investigate the sources of disparities in cropland quality and the development quality of its subsystems,and various analytical techniques including Kernel density estimation,Markov chains,and spatial convergence to examine the distribution dynamics and evolutionary trends of cropland quality.The findings reveal a consistent upward trend in overall cropland quality in China over the years,with a relatively low Gini coefficient,indicating minor quality fluctuations.Notably,the inter-regional Gini coefficient is highest between China’s eastern and western regions and lowest between the western and northeastern regions.Moreover,the Gini coefficients show an increasing trend among the eastern-central,eastern-western,easternnortheastern,and central-western regions.Regarding distribution dynamics,the absolute disparities in cropland quality among the eastern,central,and northeastern regions are decreasing but widening in the western region,suggesting a polarization effect among the four major regions,albeit with a tendency towards reduction.The findings from the Markov chain analysis indicate that cropland quality in China tends to be stable,making leapfrog development challenging.From a spatial convergence perspective,theσcoefficient is relatively high for the entire country;however,the western region exhibits a lowerσcoefficient.The consistently significant negativeβvalue indicates the presence of absoluteβconvergence,conditionalβconvergence,spatial absoluteβconvergence,and spatial conditionalβconvergence in the cropland quality index across China and its two major regions,with variations in convergence rates and cycles observed at both national and regional levels.