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将矿区数据纳入生态安全格局识别:以郴州为例

Integrating mining district data into ecological security pattern identification: a case study of Chenzhou.

作者信息

Hui Jiawei, Cheng Yongsheng

机构信息

School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China.

Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha, 410083, China.

出版信息

Sci Rep. 2025 May 6;15(1):15800. doi: 10.1038/s41598-025-00883-w.

Abstract

Resource-intensive cities face significant ecological challenges due to mining activities, which degrade landscapes, pollute ecosystems, and disrupt ecological security patterns. This study proposes a process for identifying ecological security patterns (ESP) in mining cities, integrating landscape risk assessment, remote sensing ecological quality evaluation, and mining district spatial data. We introduce the ecological source index (ECSI) to identify ecological sources in Chenzhou and construct an ecological resistance surface (ERS) by incorporating mining district locations. Using circuit theory, we map key ecological corridors and nodes, establishing the ecological security framework for Chenzhou. Our findings show 2,903 km² of primary ecological sources, 1,735 km² of secondary ES, and 2,124 km² of tertiary ES, along with 90 ecological corridors (1,183.66 km), 22 inactive corridors (983.37 km), 3 major river corridors, 68 pinch points, and 80 barriers. The ecological sources are organized in a "dominant source with multiple subsidiary cores" structure, connected by a "three horizontal and four vertical" corridor network. Ecological sources are primarily located in the east, while corridors, pinch points, and barriers are concentrated in the west. Barriers are mainly urban areas, mining zones, and farmland, while pinch points occur in narrow corridor sections, especially near towns and mining areas. Mining activities cause localized shifts and fragmentation of ecological corridors. We propose recommendations for mining management, such as implementing strict mining approval processes, constructing artificial ecological corridors, and expanding ecological channel boundaries in pinch point clusters. These findings provide essential guidance for ecological restoration and sustainable development in resource-dependent cities.

摘要

资源密集型城市因采矿活动面临重大生态挑战,这些活动会破坏地貌、污染生态系统并扰乱生态安全格局。本研究提出了一种在矿业城市识别生态安全格局(ESP)的方法,该方法整合了景观风险评估、遥感生态质量评价和矿区空间数据。我们引入生态源指数(ECSI)来识别郴州的生态源,并通过纳入矿区位置构建生态阻力面(ERS)。利用电路理论,我们绘制了关键生态廊道和节点,建立了郴州的生态安全框架。我们的研究结果表明,主要生态源面积为2903平方公里,次要生态源面积为1735平方公里,三级生态源面积为2124平方公里,还有90条生态廊道(1183.66公里)、22条非活跃廊道(983.37公里)、3条主要河流廊道、68个瓶颈点和80个障碍点。生态源呈“一主多副核”结构分布,由“三横四纵”廊道网络相连。生态源主要位于东部,而廊道、瓶颈点和障碍点集中在西部。障碍点主要是城市地区、矿区和农田,瓶颈点出现在狭窄的廊道段,尤其是靠近城镇和矿区的地方。采矿活动导致生态廊道局部转移和破碎化。我们提出了采矿管理建议,如实施严格的采矿审批程序、建设人工生态廊道以及在瓶颈点集群扩大生态通道边界。这些研究结果为资源依赖型城市的生态修复和可持续发展提供了重要指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b9b/12056199/d74ebc0afcb3/41598_2025_883_Fig1_HTML.jpg

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