粮食主产区耕地非粮化空间格局分异及其成因

为摸清粮食主产区耕地非粮化的总体状况，揭示非粮化的空间分异特征及其成因，以徐州市为研究区域，运用空间自相关分析法、冗余分析法与案例分析法，研究粮食主产区非粮化空间分异特征、主导因素及其作用机制。研究表明：徐州市法定耕地内（LF，10.25%）、永久基本农田范围内（BF，7.30%）、两区划定范围内（FF，2.67%）非粮化率呈依次递减态势，城区非粮化率高于远郊；非粮化面积超过500 hm²的乡镇为6个，分布于远郊南部和西北角，但非粮化率则从中心向远郊递减扩散。非粮化率在FF范围内存在2个高-高集聚区，不同于LF和BF，城区周边明显高于其他区域；RDA分析显示社会经济变量解释了91.85%的非粮化面积特征向量的变化，主要驱动因子包含常住人口、农业人口、农业收入、土地流转率、农业机械总动力，其中非农业收入和农业机械劳动力分别是城区与远郊的关键驱动因子。研究表明，粮食主产区非粮化率总体不高，以菜地占用为主，但不同范围、不同区位非粮化率差异明显，必须高度重视并谨慎对待社会经济因素驱动作用。

Spatial pattern differentiation of cultivated land non-grain conversion in major grain-producing areas

This study aimed to explore the overall situation of cultivated land non-grain conversion, revealed the spatial pattern characteristics and its causes of cultivated land non-grain conversion, and provided scientific and technological support for cultivated land protection and food security. Taking Xuzhou City as the study area, we used spatial autocorrelation, redundancy, and case analyses to study the spatial differentiation characteristics, dominant factors, and action mechanism of non-grain production in major grain-producing areas. The results showed that the non-grain rate of legal farmland(LF, 10.25%), basic permanent farmland(BF, 7.30%), and cultivated land in major grain-producing areas(FF, 2.67%) in Xuzhou City decreased successively, and the non-grain conversion rate of the urban area was high and the non-grain conversion area of the suburb was large. Six towns exhibited areas of cultivated land non-grain conversion over 500 hm², distributed in the southern outer suburb and the northwest corner. The rate of non-grain conversion represented a decreasing diffusion from the center to the outer suburb. In the FF range, two high-high clusters could be observed, where the non-grain conversion rate showed a different phenomenon from LF and BF. The phenomenon was that the non-grain conversion rate around the city was obviously higher than that in other areas. The RDA analysis showed that the socio-economic variables could explain 91.85% of the change of the eigenvector of the non-grain area. The main driving factors included resident population, agricultural population, agricultural income, land transfer rate,and total power of agricultural machinery, while the non-agricultural income and agricultural machinery labor were the key driving factors of urban and suburban respectively. In conclusion, the non-grain conversion rate of the main grain-producing areas was not high, and the vegetable land was in a predominant position. However, the non-grain conversion rates showed significant differences in different areas and locations. Therefore, significant importance and attention must be paid to the driving roles of economic and social factors.