Key Laboratory of Geological Hazards on Three Gorges Reservoir Area, Ministry of Education, China Three Gorges University, Yichang, China.
Hubei Key Laboratory of Disaster Prevention and Mitigation, China Three Gorges University, Yichang, China.
PeerJ. 2024 Sep 5;12:e18033. doi: 10.7717/peerj.18033. eCollection 2024.
Scientific assessment of soil quality is the foundation of sustainable vegetation eco-restoration in engineering disturbed areas. This study aimed to find a qualitative and comprehensive method for assessing soil quality after vegetation eco-restoration in engineering disturbed areas. Sixteen soil indicators were used at six vegetation eco-restoration sites as the potential soil indicators. A minimum data set (MDS) and revised minimum data set (RMDS) were determined by principal component analysis. Six soil quality indices (SQIs) of varying scoring functions based on different data sets were employed in this study. Significant positive correlations were observed among all six SQIs, indicating that the effects of different vegetation eco-restoration measures on soil quality could be quantified by all six SQIs. The SQI values of the vegetation concrete eco-restoration slope (VC), frame beam filling soil slope (FB), thick layer base material spraying slope (TB), and external-soil spray seeding slope (SS) were all significantly higher than the SQI value of the abandoned slag slope (AS). It is noteworthy that the SQIs of the VC and TB sites were also significantly higher than the SQI of the natural forest (NF) site. These results indicate that the application of artificial remediation measures can significantly improve the soil quality of the disturbed area at the Xiangjiaba hydropower station. The results of this study also indicate that the SQI-NLRM method is a practical and accurate quantitative tool for soil quality assessment and is recommended for evaluating soil quality under various vegetation eco-restoration techniques in disturbance areas at the Xiangjiaba hydropower station and in other areas with similar habitat characteristics.
科学评估土壤质量是工程扰动区植被生态恢复可持续性的基础。本研究旨在寻找一种定性和综合的方法,以评估工程扰动区植被生态恢复后的土壤质量。在六个植被生态恢复点选择了 16 个土壤指标作为潜在的土壤指标。利用主成分分析确定最小数据集(MDS)和修订最小数据集(RMDS)。本研究采用了基于不同数据集的六种不同评分函数的土壤质量指数(SQI)。所有六个 SQI 之间均呈显著正相关,表明不同植被生态恢复措施对土壤质量的影响可通过所有六个 SQI 来量化。植被混凝土生态恢复边坡(VC)、框架梁填土边坡(FB)、厚层基材喷播边坡(TB)和客土喷播边坡(SS)的 SQI 值均显著高于废弃渣边坡(AS)的 SQI 值。值得注意的是,VC 和 TB 点的 SQI 值也显著高于自然森林(NF)点的 SQI 值。这些结果表明,人工修复措施的应用可以显著提高向家坝水电站扰动区的土壤质量。本研究结果还表明,SQI-NLRM 方法是一种实用且准确的土壤质量评估定量工具,建议在向家坝水电站及其他具有类似生境特征的扰动区采用各种植被生态恢复技术时,使用该方法评估土壤质量。