GEOGRAPHICAL RESEARCH ›› 2012, Vol. 31 ›› Issue (9): 1621-1630.doi: 10.11821/yj2012090008

• Earth Surface Processes • Previous Articles     Next Articles

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

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