农户视角耕地集约利用及驱动机制的内生差异研究

DIFFERENTIAL ANALYSIS OF INTENSIVE ARABLE LAND USE AND ITS DRIVING MECHANISM BASED ON THE PERSPECTIVE OF RURAL HOUSEHOLDS

关键词:  农户  耕地利用集约度  能值分析  空间重心  标准差椭圆  驱动机制分析

Key words:  rural households  arable land use intensity  Emergy analysis  spatial barycenter  standard deviation ellipse  driving mechanism

摘要:

目的 基于农户视角，将家庭生计及耕地规模纳入农户观察，探析农户耕地集约利用模式及驱动机制的内生性差异，为针对性农户耕地集约利用政策优化提供依据。方法 文章运用生产要素能值分析法（Emergy Analysis）对农户耕地利用集约度进行测算和对比，结合ArcGIS标准差椭圆和Pearson相关性分析，系统探究农户耕地利用集约度空间分布及驱动机制的差异性。结果 （1）农户间的耕地利用集约度的结构差异主要表现在化肥、机械和劳动力三方面，耕地面积较小的兼业户（占农户总量的64%）耕地利用集约度较高，耕地面积较大的纯农户耕地利用集约度较低；（2）农户间耕地利用集约度在空间上形成积累性差异，其中纯农户耕地利用集约度的西南—东北方向性显著、高值区呈点状分散，而兼业户耕地利用集约度分布的东—西方向性显著、高值区呈带状集聚，在东—西和南—北方向上成“倒U型”趋势分布；（3）纯农户耕地利用集约度更易受自身属性驱动（文化程度、耕地面积和破碎度等），而兼业户耕地利用集约度对当地经济（GDP）、地区农业发展（农业产值、区域复种指数）等区域型外部因子更为敏感。结论 农户间耕地利用集约度及其空间分布异质性显著，其驱动机制具有一定隐含差异，农户耕地利用模式的优化需“因户制宜”合理引导。

Abstract:

Toexplain the differences and driving mechanisms of arable land use intensity among rural households, this paper estimates the arable land use intensity among different rural households. Taking 1704 rural households in Shandong province as an example, the methods of ArcGIS standard deviation ellipse space analysis and Pearson correlation were used to explore the spatial differences and driving factors of the rural households' intensive arable land use pattern. The results were showed as follows.Firstly, the structural differences of cultivated land use intensity among farmers were mainly reflected in three aspects: chemical fertilizer, machinery and labor force. The cultivated land use intensity of part-time households with small cultivated land area (accounting for 64% of the total number of farmers) was higher, and that of pure farmers with large cultivated land area was lower. Secondly, the intensive degree of cultivated land use among farmers had accumulated differences in space. Among them, the southwest northeast direction of the intensive degree of cultivated land use of pure farmers was significant, and the high-value area was scattered in a point shape, while the east-west direction of the intensive degree of cultivated land use of part-time households was significant, and the high-value area was banded, forming an "inverted U-shaped" trend distribution in the east-west and south-north. Finally, the driving mechanisms of farmland use intensity among rural households were implicitly different. Full-time farming rural households were greatly affected by their own attributes, including their educational level, the arable land area and the fragmentation of their farmland. Part-time rural households were more susceptibly affected by regional factors, including per capita GDP, primary industry output value, and regional multi-crop index. In summary, the spatial distribution of cultivated land utilization intensity among rural households is heterogeneous, and the driving mechanism of the utilization of cultivated land also has implicit differences among rural households. In the future management, targeted optimal adjustment of farmland use intensity based on the type of rural households is beneficial for healthy and stable agricultural production.