地理研究 ›› 2012, Vol. 31 ›› Issue (9): 1621-1630.doi: 10.11821/yj2012090008

• 土地资源与利用 • 上一篇    下一篇

耕地集约利用对粮食产量变化影响的定量分析——以江苏省为例

徐国鑫, 金晓斌, 宋佳楠, 周寅康   

  1. 南京大学地理与海洋科学学院, 南京 210093
  • 收稿日期:2011-10-18 修回日期:2012-05-09 出版日期:2012-09-20 发布日期:2012-09-20
  • 通讯作者: 金晓斌(1974- ),男,甘肃兰州人,博士,副教授,主要从事土地资源管理研究。E-mail:jinxb@nju.edu.cn E-mail:jinxb@nju.edu.cn
  • 作者简介:徐国鑫(1988- ),男,江苏盐城人,硕士,主要从事土地资源管理研究。E-mail:gler5@163.com
  • 基金资助:

    国土资源部公益性行业科研专项经费(201011016-8)

The impact of intensive use of agricultural land on grain yields:A case study of Jiangsu Province

XU Guo-xin, JIN Xiao-bin, SONG Jia-nan, ZHOU Yin-kang   

  1. School of Geographical and Oceanographical Sciences, Nanjing University, Nanjing 210093, China
  • Received:2011-10-18 Revised:2012-05-09 Online:2012-09-20 Published:2012-09-20

摘要: 针对粮食生产力影响因素分层结构的特点,构建粮食单产影响因素的多层线性模型,以江苏省为实证案例,定量研究耕地利用集约度及宏观政策因素对粮食单产变化影响及其内在作用机制。研究结果表明:(1)粮食单产的影响因素是多层次的,耕地利用集约度解释了平均粮食单产差异的57.04%,农业政策因素解释了平均粮食单产差异的42.96%;(2)2001~2008年江苏省的粮食单位面积产出总体呈逐年增加的趋势,其中,劳动集约度和资本集约度分别解释了县级平均粮食单产差异的19.50%和5.68%。(3)所选政策变量中,支农支出、科技支出和农业贷款三个变量对市级平均粮食单产具有显著作用。(4)所选政策变量解释了市级粮食单产均值差异的63.21%,市级层次还有36.79%的"背景效应"未得到解释。

关键词: 耕地集约利用度, 粮食单产, 多层线性模型, 江苏省

Abstract: Hierarchical linear models can separate variables of different spatial scales and different management levels,and they explain interactions between explanatory variables.This paper,taking Jiangsu province as a research area,uses hierarchical linear models to analyze the influence and mechanism of agricultural land use intensity and policy factors on grain yields.The results are shown as follows.(1) There are multi-level factors affecting grain productivity per unit area,agricultural land use intensity and policy factors separately explains 57.04% and 42.96% of differences in grain yields.(2) Grain productivity per unit area showed a rising trend from 2001 to 2008 in Jiangsu,of which labor intensity and capital intensity separately explained 19.50% and 5.68% of differences in average grain yield at county level.Land use intensity explained 25.17% of differences in average grain yield at county level,and intensive use of agricultural land is not the most important influencing factor that affects grain productivity,indicating that natural quality of land and land quantity has an increasingly important impact on grain production capacity.(3) Three policy variables-agriculture investment,technology investment and agriculture loans-have significant influence on grain yields.Agriculture investment only explained 11.90% of differences in average grain yields,and agriculture loans and technology investment separately explained 18.25% and 33.06% of differences in average grain yields.(4) All the selected policy variables can only explained 63.21% of differences in average grain yield at municipal level.

Key words: intensity degree of agricultural land use, grain yield, hierarchical linear models, Jiangsu Province