作者
Jun Liu,Shiwen Zhang,Enwei Li,Yafei Zhu,Huizhen Cai,Shasha Xia,Chunfang Kong
摘要
In view of the strong acidity and high heavy metal contents of the soil, the low vegetation cover, and strong soil erosion caused by mining activities, the reasonable determination of the cubic restoration mode is the key to determining the good or bad ecological restoration effects on mining wasteland. In this study, based on field experiments, a combined cubic ecological restoration scheme for soil improvement-vegetation reconstruction was constructed. Using analysis of variance, a regression model, and the Mantel test, the differences in soil properties and the biodiversity were analyzed under different restoration schemes, the entropy-weighted-TOPSIS method was used to optimize the best ecological restoration model. The results revealed that compared with the pre-restoration state, the restoration significantly increased the soil pH (p < 0.05) by 4.07-5.73, regulated the strong acidic environment of the soil, increased the organic matter content by 5.35-11.21 times, and improved the soil fertility. The available contents of Pb and Cd were reduced by 67.15-75.58 % and 64.15-88.68 %, respectively compared with the background values. Biodiversity improved significantly, and the available content of Cd was an important factor in the biodiversity recovery. The evaluation of the effect of the restoration scheme showed that the combination of mixed soil amendments of rice husks and chicken manure (10 kg/m2), bacterial fertilizer (1.8 kg/m2), biochar (1.3 kg/m2), lime (8.3 kg/m2), and soil conditioner (1.0 kg/m2) and tolerant plants (Pinus elliottii, Lagerstroemia indica, and Plantago asiatica) are the optimal cubic ecological restoration scheme for the study area, with a plant survival rate of > 90 %, eight families and 10 species of plants, and a coverage rate of 100 %. These research results provide a scientific basis and technical support for reasonable artificial intervention in ecological restoration of mining waste sites in Nanling, northern Guangdong.