基于景观格局的矿区生态脆弱性评价——以吉林省辽源市为例

生态学杂志

基于景观格局的矿区生态脆弱性评价——以吉林省辽源市为例

吴健生¹,宗敏丽^1**,彭建²

（¹城市人居环境科学与技术重点实验室，北京大学深圳研究生院城市规划与设计学院，广东深圳 518055； ²地表过程分析与模拟教育部重点实验室，北京大学城市与环境学院，北京 100871）

出版日期:2012-12-10 发布日期:2012-12-10

Assessment of mining area’s ecological vulnerability based on landscape pattern: A case study of Liaoyuan, Jilin Province of Northeast China.

WU Jian-sheng¹, ZONG Min-li^1**, PENG Jian^2

(¹ Key Laboratory for Environmental and Urban Sciences, School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong, China; ² Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China)

Online:2012-12-10 Published:2012-12-10

摘要/Abstract

摘要：

矿区自然生态系统脆弱性研究不仅对生态资源及生态环境有重要作用，还对资源合理利用及实现区域可持续发展有指导意义。在分析生态脆弱性概念与评价方法的基础上，依循“压力状态响应”评估框架，基于景观格局指数，从自然生态系统压力度、敏感性、恢复力3方面出发构建矿区自然生态系统脆弱性评价指标体系。以辽源市为例，对其进行系统分析与评价。结果表明：各类自然生态系统类型中，辽源市草地的脆弱性最高、林地最低；33个乡镇中，杨木林镇生态脆弱性最高、东丰县县城最低；从4个区县来看，脆弱性大小为龙山区>西安区>东丰县>东辽县；用地分布格局，自然生态环境，采矿、居民点等人为干扰，是影响生态脆弱性空间分异的主要原因。

Abstract: The vulnerability assessment of natural ecosystems in mining areas is of significance in resources management, environmental protection, and regional sustainable development. Based on the analyses of the concepts of ecological vulnerability and the related assessment models, and following the ‘pressurestatusresponse’ (PSR) assessment framework, an assessment indices system was put forward to quantify the vulnerability of natural ecosystems in mining areas from the aspects of human pressure, ecosystem sensitivity, and ecological resilience, with the application of landscape metrics. Taking the Liaoyuan City of Jilin Province as a case, the results showed that among the various types of natural ecosystems, grassland had the highest ecological vulnerability, while forestland had the lowest one. In all the 33 towns, Yangmulin Town had the highest ecological vulnerability, while Dongfeng County town had the lowest one. In the four districts and counties of Liaoyuan, Longshan District had the highest ecological vulnerability, with the Xi’an District, Dongfeng County, and Dongliao County in a descending sequence. The main factors affecting the spatial differentiation of the ecological vulnerability were land use pattern, natural ecological environment, and human disturbances such as mining and settlement.

吴健生1,宗敏丽1**,彭建2. 基于景观格局的矿区生态脆弱性评价——以吉林省辽源市为例[J]. 生态学杂志.

WU Jian-sheng1, ZONG Min-li1**, PENG Jian2. Assessment of mining area’s ecological vulnerability based on landscape pattern: A case study of Liaoyuan, Jilin Province of Northeast China.[J]. cje.