Combination of artificial zeolite and microbial fertilizer to improve mining soils in an arid area of Inner Mongolia, China

• Published in: Journal of arid land 2023-09, Vol.15 (9), p.1067-1083
• Main Authors: Li, Wenye, Zhang, Jianfeng, Song, Shuangshuang, Liang, Yao, Sun, Baoping, Wu, Yi, Mao, Xiao, Lin, Yachao
• Format: Article
• Language: English
• Subjects: Abundance; Actinomycetes; Alfalfa; Bacteria; Biomass; Earth and Environmental Science; Fertilizers; Fungi; Geography; Microorganisms; Nitrogen; Organic matter; Organic phosphorus; Organic soils; Phosphorus; Physical Geography; Plant Ecology; Plant species; Potassium; Redundancy; Research Article; Restoration; Soil; Soil improvement; Soil nutrients; Soil organic matter; Soils; Substrates; Sustainable Development; Zeolites
• ISSN: 1674-6767; 2194-7783
• DOI: 10.1007/s40333-023-0028-1

Restoration of mining soils is important to the vegetation and environment. This study aimed to explore the variations in soil nutrient contents, microbial abundance, and biomass under different gradients of substrate amendments in mining soils to select effective measures. Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region, China. Contents of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), microbial biomass carbon/microbial biomass nitrogen (MBC/MBN) ratio, biomass, and bacteria, fungi, and actinomycetes abundance were assessed in Agropyron cristatum L. Gaertn., Elymus dahuricus Turcz., and Medicago sativa L. soils with artificial zeolite (AZ) and microbial fertilizer (MF) applied at T0 (0 g/kg), T1 (5 g/kg), T2 (10 g/kg), and T3 (20 g/kg). Redundancy analysis (RDA) and technique for order preference by similarity to ideal solution (TOPSIS) were used to identify the main factors controlling the variation of biomass. Results showed that chemical indices and microbial content of restored soils were far greater than those of control. The application of AZ significantly increases SOM, AN, and AP by 20.27%, 23.61%, and 40.43%, respectively. AZ significantly increased bacteria, fungi, and actinomycetes abundance by 0.63, 3.12, and 1.93 times of control, respectively. RDA indicated that AN, MBC/MBN ratio, and SOM were dominant predictors for biomass across samples with AZ application, explaining 87.6% of the biomass variance. SOM, MBC/MBN ratio, and AK were dominant predictors with MF application, explaining 82.9% of the biomass variance. TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils. AZ and MF application at T2 concentration in the mining soils with M. sativa was found to be the most appropriate measure.