东北粮食主产区耕地生态安全的时空格局及障碍因子——以吉林省为例

Spatial-temporal pattern and obstacle factors of cultivated land ecological security in major grain producing areas of Northeast China: A case study in Jilin Province

针对东北粮食主产区耕地生态安全状况,以吉林省48个县域为研究对象,构建基于PSR-EES模型的耕地生态安全评价指标体系,综合运用改进的TOPSIS模型、马尔可夫链模型、GIS空间分析方法和障碍度模型对1995—2011年吉林省耕地生态安全时空格局以及障碍因子进行分析.结果表明:1995—2011年,吉林省耕地生态安全综合指数呈波动上升趋势,耕地生态安全等级从敏感级提高到一般安全级;各县域耕地生态安全水平存在"俱乐部趋同"现象,且空间分布格局差异趋于扩大,"两极分化"趋势日益显著,敏感级和临界安全级由带状趋于分散分布,一般安全级和比较安全级由分散趋于集中成片分布,安全级分布比较零散,耕地生态安全等级水平不稳定趋势越来越明显;农民人均纯收入、经济密度、环境保护投资总额占GDP比重、机耕程度、工业固体废物综合利用率是影响吉林省耕地生态安全水平的主要障碍因子.

According to the cultivated land ecological security in major grain production areas of Northeast China, this paper selected 48 counties of Jilin Province as the research object. Based on the PSR-EES conceptual framework model, an evaluation index system of cultivated land ecological security was built. By using the improved TOPSIS, Markov chains, GIS spatial analysis and obstacle degree models, the spatial-temporal pattern of cultivated land ecological security and the obstacle factors were analyzed from 1995 to 2011 in Jilin Province. The results indicated that, the composite index of cultivated land ecological security appeared in a rising trend in Jilin Province from 1995 to 2011, and the cultivated land ecological security level changed from being sensitive to being general. There was a pattern of ‘Club Convergence’ in cultivated land ecological security level in each county and the spatial discrepancy tended to become larger. The ‘Polarization’ trend of cultivated land ecological security level was obvious. The distributions of sensitive level and critical security level with ribbon patterns tended to be dispersed, the general security level and relative security levels concentrated, and the distributions of security level scattered. The unstable trend of cultivated land ecological security level was more and more obvious. The main obstacle factors that affected the cultivated land ecological security level in Jilin Province were rural net income per capita, economic density, the proportion of environmental protection investment in GDP, degree of machinery cultivation and the comprehensive utilization rate of industrial solid wastes.