地理科学进展 ›› 2013, Vol. 32 ›› Issue (8): 1257-1265.doi: 10.11820/dlkxjz.2013.08.009

• 农业地理 • 上一篇    下一篇

1995-2010年山东省粮食单产变化空间分异及均衡增产潜力

柏林川1,2, 武兰芳1, 宋小青1,2   

  1. 1. 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京100101;
    2. 中国科学院大学, 北京100049
  • 收稿日期:2013-01-01 修回日期:2013-04-01 出版日期:2013-08-25 发布日期:2013-08-25
  • 作者简介:柏林川(1987-),男,山东济宁人,硕士研究生,研究方向为区域农业可持续评价管理。E-mail: bolinchuan@yeah.net
  • 基金资助:
    国家科技支撑计划项目(2013BAD05B03)

Spatial difference of grain yield changes during 1995-2010 and balanced potential output to increase in Shandong Province

BAI Linchuan1,2, WU Lanfang1, SONG Xiaoqing1,2   

  1. 1. Key laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2013-01-01 Revised:2013-04-01 Online:2013-08-25 Published:2013-08-25
  • Contact: 武兰芳(1963-),女,山西忻州人,副研究员,硕士生导师,主要从事区域农业可持续评价、农田生态及生产力形成等研究。E-mail: wulf@igsnrr.ac.cn E-mail:wulf@igsnrr.ac.cn

摘要: 以县域为基本空间单元,采用GIS 空间分析和ESDA方法,对山东省1995-2010 年间县域粮食单产空间格局变化进行了分析,在此基础上,结合全国农业生态区划,分析山东省粮食均衡增产潜力。结果表明:① 山东省县域粮食单产水平之间的差异整体上呈现出先增大后减小的趋势。鲁北和鲁西北平原农业生产基础差,单产增长速度最快;鲁西南平原农业生产基础差,单产增长速度较慢;鲁中南丘陵和山东半岛农业生产基础好,单产增长速度较慢;② 县域粮食单产变化的Global Moran's I 值为0.5708,表明单产变化的区域分布并非完全随机,而是表现出明显的空间集聚特征,4 种集聚类型中,“H-H”类型区和“L-L”类型区占主导,“H-H”类型区主要分布在鲁北和鲁西北平原,“L-L”类型区主要分布在鲁西南平原、鲁中南丘陵和山东半岛;③ 全省可划分为4 个一级、9 个二级均衡增产类型区,粮食单产增产潜力鲁北和鲁西北平原>鲁中南丘陵>山东半岛>鲁西南平原;总产量增产潜力约为9.50×106 t,其中鲁中南丘陵>鲁北和鲁西北平原>鲁西南平原>山东半岛。

Abstract: Based on spatial autocorrelation analysis of exploratory spatial data, spatial changes and disparities of grain yield per unit area at county level in Shandong Province during 1995-2010 are discussed by using ArcGIS and GeoDa software, and then the potential increase of grain yield per unit area and total yield at regional scale are accessed. The results show that: (1) During 1995-2010, the difference of grain yield per unit area among counties increased first, and then decreased. Among the counties, the northwestern plain and southwestern plain both had poor conditions initially, but the former increased the most quickly in grain yield per unit area and the latter increased slowly; the central and southern hills and Jiaodong Peninsula both had good conditions initially, but they increased slowly. (2) The global spatial autocorrelation of grain yield per unit area change is significantly positive and Global Moran's I is 0.5708. The changes showed a spatially clustering phenomenon on the whole and the characteristic of spatial clustering of regional high value and low value is significant. The regions with "high-high" and "low-low" correlation are the majority. The regions with "H-H" correlation are mostly located in the northwestern plain, however, the regions with "L-L" correlation are mainly distributed in the other three regions. (3) Shandong Province could be divided into 4 first-grade regions and 9 second-grade regions. The balanced potential output per unit area of the 4 first-grade regions could be sorted in descending order as the northwestern plain, central and southern hills, Jiaodong Peninsula, and southwestern plain. The total potential output of Shandong Province is 9.50×106 tons, and the 4 regions could be sorted as the central and southern hills, northwestern plain, southwestern plain, and Jiaodong Peninsula.