大湾区县域耕地“非粮化”驱动机制与治理路径

    Driving mechanism and governance path of “non-grain”cultivated land at county level in Great Bay Area

    • 摘要: 为探究耕地“非粮化”的形成机制,该研究以大湾区某县级行政区A为研究案例,采用GIS空间信息分析、多项Logistic回归等研究方法,探析耕地“非粮化”时空演变与驱动机制,并提出大湾区某县级行政区A耕地“非粮化”治理路径。结果表明:1)2010—2020年,A区耕地“非粮化”比率稳定在65%左右,其中,微弱损害类占比六至七成。2)以耕地地块为分析单元,探究自然、区位、制度等多因素对耕地“非粮化”利用的影响,对耕地“非粮化”转化贡献排前3的因子分别是耕地质量等级、距镇中心距离、是否位于高标准农田内。3)提出对不同类型耕地非粮化现象采取差异化行政管制措施,制定“监测-评价-预警-调节”的框架流程,对影响因素进行动态管控。因此,耕地“非粮化”现象在大都市郊区应当差异化行政管控,对其影响因素进行动态监测、评价、预警、调节。

       

      Abstract: "Non-grain" cultivated land has dominated national food security in recent years, particularly with the various risk factors in the world. Among them, the moderate "non-grain " cultivated land, especially in the suburbs of metropolitan areas, has promoted the transformation and upgrading of the multi-function of agriculture. However, it is still lacking in the theoretical research and practical experience at the beginning of the "non-grain" cultivated land. In this study, the "non-grain " cultivated land was defined to develop a classification system. Furthermore, the empirical analysis included the GIS spatial information analysis and multiple Logistic regression. The study area was taken as the water town functional area of Dongguan, Guangdong Province, China. The results show that: 1) The information on "non-grain " cultivated land was extracted from the data on land use with the survey and interviewed from 2010 to 2020. The ratio of "non-grain conversion" of cultivated land was stable at about 65%, among which the weakly damage accounted for 60% to 70%, progressive damage for 2%, and serious damage for 30% to 40%. The "non-grain conversion" occurred in five towns. Among them, the weak and progressive damage areas were mostly distributed in Machong Town. Serious damage area was distributed in Daojiao Town. There was a roughly similar spatial distribution of non-grain cultivated land. Only a small number of land types were changed from 2010 to 2015. There was a difference in the spatial distribution of cultivated land and non-grain cultivated land in 2020, 2010, and 2015. 2) Multiple Logistic regression showed that the land area and quality grade of cultivated land shared a positive impact on the "non-grain" cultivated land. There was no statistical significance in the land regularity among the natural factors. In location factors, The distance from the town center and rural residential area exhibited a positive influence on the "non-grain" cultivated land. While the distance from rivers, rural roads, and highways shared a negative influence on the "non-grain" cultivated land. Among the institutional factors, the permanent basic farmland shared a positive impact on the "non-grain conversion" of cultivated land, whereas, there was a negative impact on high-standard farmland. 3) A feasible path was proposed for the differentiated administrative measures on the different types of “non-grain” cultivated land. The framework of "monitoring-evaluation-warning-regulation" was formulated to dynamically control the influencing factors. Therefore, the "non-grain conversion" of cultivated land in the metropolitan suburbs should be under differentiated administrative control. Its driving factors should be dynamically monitored, evaluated, forewarned, and adjusted from the spatial perspectives. The finding can greatly contribute to the "non-food " cultivated land in metropolitan suburbs.

       

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