受采矿作业影响的昆虫-植物相互作用分析：一种图挖掘方法
Analysis of Insect-Plant Interactions Affected by Mining Operations, A Graph Mining Approach
AI总结：
该研究针对采矿活动对生态系统的危害问题，采用网络科学的图挖掘方法分析苏格兰北部受采矿影响的昆虫-植物互作网络，开展关键物种识别、群落划分、次生灭绝预测等研究，为相关生态保护提供支撑。
摘要：
生态联结的衰退预示着物种的潜在灭绝，这可归因于各类干扰与改变。物种间相互联结的减少反映出它们对变化的脆弱性。例如，某些依赖与有限数量物种、甚至特定物种的专属相互作用的昆虫和植物，一旦失去这些关键联结就会面临灭绝风险。当前，采矿活动对自然生态系统造成了严重危害，带来了各类不利环境影响。本研究中，我们运用网络科学技术以图结构分析生态系统，旨在保护苏格兰北部受采矿作业影响的生态系统。研究内容包括识别网络中最重要的成员、建立网络内群落的识别标准并对其进行比较与评估、使用模型预测物种从网络中移除时发生的次生灭绝，以及评估网络的受损程度。本研究的创新点在于运用网络科学方法探究与昆虫-植物相互作用相关的生物学数据。
英文摘要：
The decline in ecological connections signifies the potential extinction of species, which can be attributed to disruptions and alterations. The decrease in interconnections among species reflects their susceptibility to changes. For example, certain insects and plants that rely on exclusive interactions with a limited number of species, or even a specific species, face the risk of extinction if they lose these crucial connections. Currently, mining activities pose significant harm to natural ecosystems, resulting in various adverse environmental impacts. In this study, we utilized network science techniques to analyze the ecosystem in a graph-based structure, aiming to conserve the ecosystem affected by mining operations in the northern region of Scotland. The research encompasses identifying the most vital members of the network, establishing criteria for identifying communities within the network, comparing, and evaluating them, using models to predict secondary extinctions that occur when a species is removed from the network, and assessing the extent of network damage. Our study's novelty is utilizing network science approaches to investigate the biological data related to interactions between insects and plants.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
