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引用本文:张龙生,李 萍,张建旗.甘肃省生态环境脆弱性及其主要影响因素分析[J].中国农业资源与区划,2013,34(3):55~59
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甘肃省生态环境脆弱性及其主要影响因素分析
张龙生1, 李 萍1, 张建旗2
1.甘肃省生态环境监测监督管理局,兰州 730020/甘肃省林业调查规划院,兰州 730020;2.兰州市园林科学研究所,兰州 730070
摘要:
该文基于土地退化和成因结果表现指标对甘肃省14个市(州)的81个县区(市辖区为一个单 元)的生态脆弱性进行评价研究,结果显示:强度脆弱县3个,高度脆弱县16个,中度脆弱县35个,轻 度脆弱县19个,微度脆弱县8个,甘肃省的经济社会发展水平处于全国后列,而生态脆弱性居全国前列。 运用主成分分析和相关分析的方法,测试分析了甘肃生态脆弱性与降雨量、森林覆盖率、垦殖率、人口密 度、人均GDP等5个主要自然社会经济因子的关系,以期对甘肃省的社会经济可持续发展提供参考。
关键词:  甘肃省 生态脆弱性 影响因素 相关关系
DOI:10.7621/cjarrp.1005-9121.20130309
分类号:
基金项目:基金项目:该文为“甘肃省主体功能区规划”前期研究子课题———“甘肃省生态脆弱性评价研究”的部分内容
ANALYSIS OF ECOLOGICAL VULNERABILITY AND ITS MAJOR INFLUENCING FACTORS IN GANSU PROVINCE
Zhang Longsheng1, Li Ping1, Zhang Jianqi2
1.Ecological Environment Supervision and Administration Bureau of Gansu Province, Lanzhou 730020, China/Forestry Inventory and Planning Institute of Gansu Province, Lanzhou 730020, China;2.Lanzhou Institute of landscape science, Lanzhou 730020, China
Abstract:
In this paper, ecological vulnerability was evaluated based on land degradation and the results of per- formance index of eighty-one counties(city area as a unit) in fourteen cities of Gansu province. The assessment results showed that there were three counties with highly severe ecological vulnerability, sixteen counties with severe ecological vulnerability, thirty-five counties with moderate ecological vulnerability, nineteen counties with slight ecological vulnerability and eight counties with very slight ecological vulnerability. In the nationwide, the social and economic development level in Gansu province was low, but at a high level in the ecological vulnerability. Principal component analysis and correlation analysis methods were used to test the relationship between ecological vulnera- bility in Gansu and the factors of natural social and economic, such as rainfall, the forest coverage rate, cultivate breed rate, population density, per capita GDP, for providing reference to the sustainable development of social e- conomy in Gansu province.
Key words:  Gansu province  ecological vulnerability  influence factors  correlation
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