首页 | 本学科首页   官方微博 | 高级检索  
     

干旱半干旱区耕地非粮化空间格局及驱动因素
引用本文:常媛媛,刘俊娜,马静,于昊辰,陈浮. 干旱半干旱区耕地非粮化空间格局及驱动因素[J]. 农业资源与环境学报, 2023, 40(2): 333-344
作者姓名:常媛媛  刘俊娜  马静  于昊辰  陈浮
作者单位:中国矿业大学公共管理学院, 江苏 徐州 221116;河海大学公共管理学院, 南京 210098
基金项目:国家科技支撑计划课题(2015BAD06B02);中国国土勘测规划院外协科技项目(2018041);中国矿业大学研究生创新计划项目(2022WLJCRCZL157)
摘    要:为厘清干旱半干旱区耕地非粮化态势,减少非粮化对粮食安全的威胁,本研究利用空间自相关分析法、多元线性回归模型与地理加权回归分析方法,探索非粮化地域分异特征及主要驱动因素。结果表明:2018年干旱半干旱区耕地非粮化面积为8.3×106hm2,非粮化率为38.3%;非粮化率在空间上呈由西向东逐渐递减的分布格局,非粮化面积则呈两边高、中部低的分布特征;土地流转面积是驱动干旱半干旱区非粮化空间格局分异的最重要因子,人均GDP、人均耕地面积和乡村劳动力人数也影响了地域分异特征,但不同地域内各因素作用存在显著的空间异质性。研究表明,非粮化受经济、社会、政策因素影响大,今后应规范土地流转行为,调整惠农补贴并优化资源配套,加大监管的同时谨防“一刀切”,实现农民增收、耕地保护和粮食安全“三协同”。

关 键 词:非粮化  粮食安全  空间自相关  地理加权回归模型  驱动因素
收稿时间:2022-03-23

Spatial pattern and driving factors of non-grain conversion on cultivated land in arid and semi-arid regions
CHANG Yuanyuan,LIU Junn,MA Jing,YU Haochen,CHEN Fu. Spatial pattern and driving factors of non-grain conversion on cultivated land in arid and semi-arid regions[J]. Journal of Agricultural Resources and Environment, 2023, 40(2): 333-344
Authors:CHANG Yuanyuan  LIU Junn  MA Jing  YU Haochen  CHEN Fu
Affiliation:School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China;School of Public Administration, Hohai University, Nanjing 210098, China
Abstract:Non-grain conversion of cultivated land is a serious threat to national food security. Based on spatial autocorrelation analysis, a multiple linear regression model, and geographically weighted regression analysis, this study clarified the overall pattern of cultivated land non-grain conversion in arid and semi-arid areas of China in 2018. The findings reveal regional differentiation characteristics and main driving factors of non-grain conversion. The non-grain area of 63 municipal units in arid and semi-arid areas was 8.3×106 hm2, accounting for 38.3% of the total cultivated land. In arid and semi-arid regions, the non-grain conversion rate of cultivated land decreased gradually from west to east, and the non-grain conversion area was high on both sides and low in the middle. The land circulation area of policy factors were the most important driving factors of the spatial pattern of differentiation. The economic factor of per capita GDP and social factors of per capita arable land resources endowment and rural labor force also influenced regional differentiation of cultivated plants. However, the effects of the various factors displayed significant special heterogeneity in different regions. In the future, it will be necessary to regulate land transfer behavior, adjust agricultural subsidies, optimize agricultural resource matching, and enhance supervision of nongrain production to synergistically increase farmers'' income, protect farmland, and improve food security.
Keywords:non-grain conversion   food security   spatial autocorrelation   geographically weighted regression model   driving factor
点击此处可从《农业资源与环境学报》浏览原始摘要信息
点击此处可从《农业资源与环境学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号