LI Peng, QI Shi, ZHANG Lin, HU Jun, TANG Ying, LU Jinsheng, WANG Xiangyu, LAI Jinlin, LIAO Ruien, ZHANG Dai, and ZHANG Yan
[Objective] This study is aimed at comprehensively evaluating the soil quality of different vegetation restoration types in the mountainous areas of Beijing, and further identifying the key factors affecting soil quality, so as to provide data support for vegetation restoration and reconstruction in the region. [Methods] The study utilized various vegetation types, including Platycladus orientalis pure forest, Pinus tabulaeformis pure forest, P. orientalis-P. tabulaeformis mixed forest, P. orientalis coniferous and broadleaved mixed forest, P. tabulaeformis coniferous and broadleaved mixed forest, deciduous broad-leaved mixed forest, and non-forest land (CK), with similar stand conditions, as research objects. Fourteen soil physical and chemical indicators were measured to establish the total data set (TDS) for evaluating soil quality. Principal component analysis (PCA) and Pearson correlation analysis were employed to determine the minimum data set (MDS) for soil quality evaluation. Two scoring methods, linear (L) and non-linear (NL), were used to calculate the soil quality index (SQI) and a general linear model (GLM) was employed to identify key factors influencing soil quality. [Results] The bulk density and sand content decreased, while the content of soil nutrients such as organic matter, total nitrogen, total potassium, available nitrogen, and available potassium increased after the vegetation restoration compared with the non-forest land. The screened MDS indicators for soil quality evaluation in the study area were total nitrogen (TN), sand content, total potassium (TK), pH, and available water capacity (AWC). Under the four methods (SQI-LT, SQI-NLT, SQI-LM, and SQI-NLM), the SQI values of different vegetation restoration types were ranked as deciduous broadleaf mixed forest > P. orientalis coniferous and broadleaved mixed forest > P. tabulaeformis pure forest > P. tabulaeformis coniferous and broadleaved mixed forest > P. orientalis-P. tabulaeformis mixed forest > P. orientalis pure forest > non-forest land, and the soil quality significantly improved after vegetation restoration. The soil quality evaluation method of SQI-NLM exhibited better applicability in the mountainous areas of Beijing. Compared with non-forested land, the SQI-NLM of other vegetation restoration types improved by 64%, 48%, 45%, 36%, 33% and 27%, respectively. The GLM model accounted for 85.24% of the total variation in the soil quality index, with vegetation type explaining the largest proportion of the soil quality index (45.09%). [Conclusion] The selection of suitable vegetation restoration types is crucial for improving regional soil quality. In future vegetation restoration efforts, priority should be given to broad-leaved species in tree species selection. Additionally, the choice of silvicultural configuration should depend on the tree species, such as introducing native broad-leaved species into Platycladus orientalis pure forest to form a Platycladus orientalis coniferous and broadleaved mixed forest, or selecting Pinus tabulaeformis pure forest as the optimal silvicultural model.