Abstract:

[Objective] Rare earth resources are strategically important for national economic development, technological innovation, and industrial security. Due to its abundant reserves, diverse mineral types, and long history of exploitation, Ganzhou City in Jiangxi Province has become one of China’s most important rare earth production bases. However, decades of intensive mining have caused severe ecological degradation, including vegetation destruction, soil erosion, landscape fragmentation, biodiversity loss, and deterioration of ecosystem functions. In recent years, ecological restoration has become a major objective in the sustainable management of mining areas. Nevertheless, ecological restoration in rare earth mining areas continues to face several major challenges. Existing restoration efforts are often implemented at the scale of individual mines or engineering projects, resulting in fragmented restoration actions and insufficient consideration of regional ecological processes. Furthermore, interactions between subsurface mining disturbances and aboveground ecosystems are frequently overlooked, leading to a disconnect between restoration measures and ecosystem functioning. In addition, key ecological nodes that maintain landscape connectivity and integrity have not been systematically identified, limiting the effectiveness of restoration planning and ecological management. Therefore, the scientific identification of ecological source areas and restoration priorities is an essential prerequisite for coordinated ecological restoration and sustainable development in rare earth mining areas. The construction of ecological security patterns has been widely recognized as an effective approach for enhancing ecosystem resilience, maintaining ecological processes, and guiding ecological restoration at the regional scale. By integrating ecological source identification, resistance-surface construction, ecological corridor extraction, and key-node identification, ecological security patterns can effectively reduce habitat fragmentation, improve landscape connectivity, and enhance ecological network stability. This approach provides a scientific basis for optimizing restoration strategies and balancing ecological conservation with economic development. However, studies focusing specifically on ecological security pattern construction in rare earth mining areas remain limited, particularly those integrating ecological sensitivity assessment, restoration priority identification, and ecological network optimization. [Methods] This study focused on rare earth mining areas of Ganzhou City, Jiangxi Province. An integrated framework combining ecological sensitivity analysis, landscape connectivity assessment, cluster analysis, the minimum cumulative resistance (MCR) model, and circuit theory was developed to identify ecological source areas, determine restoration priorities, and construct an ecological security pattern for the mining region. First, ecological sensitivity was assessed using multiple environmental factors associated with ecological vulnerability and disturbance risk. Landscape connectivity indicators were then incorporated to identify ecologically important source areas that play critical roles in maintaining regional ecological processes. Subsequently, cluster analysis was employed to classify the mining areas according to their ecological sensitivity and degradation status, thereby facilitating the systematic identification of restoration priorities. Finally, the MCR model and circuit theory were integrated to delineate ecological corridors, identify key ecological nodes, and construct a comprehensive ecological security network for the mining areas. [Results] The rare earth mining areas were generally characterized by high ecological sensitivity. Specifically, 42.5% of the study area was classified as having extremely high or high ecological sensitivity, indicating substantial ecological vulnerability and strong ecological constraints. By contrast, only 26.4% of the study area was classified as having low ecological sensitivity or as being non-sensitive, suggesting that ecologically stable areas were relatively limited. Ecological restoration and conservation should therefore be prioritized across most of the mining areas. Cluster analysis identified four types of mining areas with distinct ecological characteristics. Types 1 and 2 exhibited high ecological sensitivity and severe ecological degradation. These areas were characterized by fragile ecological conditions, poor landscape connectivity, and urgent restoration needs. They should therefore be designated as priority areas for ecological restoration and ecological security enhancement. Restoration measures in these areas should focus on vegetation reconstruction, soil and water conservation, habitat restoration, and improvements in ecological corridor connectivity. By contrast, Types 3 and 4 had relatively sound ecological foundations and lower ecological sensitivity. Management in these areas should emphasize ecological protection, risk prevention, ecosystem maintenance, and long-term monitoring rather than large-scale restoration interventions. By integrating of ecological sensitivity and landscape connectivity analyses, 45 ecological source areas were identified within the mining region. These source areas represent critical ecological patches that support biodiversity conservation and maintain regional ecosystem functions. In addition, 112 ecological corridors were delineated using the MCR model and circuit theory. These corridors provide important pathways for species migration, energy transfer, and ecological flows. Based on the spatial configuration of ecological sources, corridors, and key nodes, a regional ecological security pattern characterized by “one core, three patches, two corridors, three zones, and four screens” was proposed. This pattern comprises one primary conservation core, three secondary ecological buffer patches, two major ecological corridors, three differentiated functional zones, and four mountain-range ecological screens. The resulting ecological security framework provides a systematic spatial strategy for coordinating ecological conservation and restoration across the mining region. This study also developed a novel integrated framework combining cluster analysis with ecological security pattern construction. Compared with conventional restoration studies that focus exclusively on ecological sensitivity or ecological network analysis, the proposed framework enables more accurate identification of restoration priorities and more targeted allocation of restoration resources. On this basis, a hierarchical “source-corridor-node” restoration strategy was proposed. Ecological source areas should be strictly protected as core habitats, ecological corridors should be optimized to improve ecological flow, and key nodes should be prioritized to enhance network stability. Meanwhile, differentiated management strategies were developed for the three ecological zones to ensure that restoration and conservation measures are tailored to local ecological conditions and restoration needs. [Conclusion] This study provides an integrated methodology for ecological security pattern construction and restoration planning in mining areas. By moving beyond the conventional focus on individual mines and adopting a regional ecological network perspective, the proposed framework contributes to a more holistic understanding of ecological restoration in areas affected by intensive mining. The findings have important theoretical and practical implications for coordinating ecological conservation, ecological security enhancement, and restoration in rare earth mining areas. Moreover, the methodology developed in this study may provide a valuable reference for ecological restoration planning and ecological security management in other mining regions facing similar environmental challenges worldwide.

Key words: rare earth ore, ecological sensitivity, cluster analysis, ecological security pattern, ecological restoration

摘要：

【目的】赣州稀土矿因储量规模庞大、矿种类型完备而快速发展，但在生态修复过程中暴露出修复碎片化、地下－地上系统割裂及矿区安全节点识别缺失等问题。科学识别稀土矿区生态源地，明确修复优先级，是推动矿区生态修复的重要基础。构建矿区生态安全格局，有助于降低生态斑块破碎化程度、提升景观连通性并识别关键性节点，可作为保障赣州稀土矿区生态可持续性的有效举措。【方法】以江西省赣州市稀土矿区为研究区，集成生态敏感性和景观连通性识别生态源地，运用聚类分析系统评估矿区敏感特征、明确修复优先级，并结合最小累积阻力模型和电路理论构建矿区生态安全格局。【结果】1）矿区整体生态敏感性以高敏感为主，42.5%的矿区处于极高－高敏感等级，26.4%的矿区处于低－不敏感等级。2）第1、2类矿区生态敏感且受损严重，为生态恢复的重点区域；第3、4类矿区生态基底较好，应以防控与维持为主。3）共识别出矿区生态源地45个、生态廊道112条，提出“一核三片两廊三区四屏”的赣州稀土矿区生态安全格局构建策略。4）构建“聚类－生态安全格局”双模式，精准识别矿区修复优先级，提出“源地－廊道－节点”分级修复与三区差异化管控策略。【结论】研究结果提供了一种整体构建矿区生态安全与生态修复的方法，超越单一矿山尺度，对于在密集采矿区实现生态安全保护与矿区修复的平衡具有重要意义。

关键词: 稀土矿, 生态敏感性, 聚类分析, 生态安全格局, 生态修复