2.4 Statistical analysis
Statistical analyses were conducted using SPSS 25.0 (SPSS Inc., USA). Two-way ANOVA was employed to evaluate the effects of slope gradients (i.e., 0º-1.5º, 1.5º-3º, 3º-5º, >5º), slope positions (i.e., top, middle, and bottom parts of the slope) on soil physicochemical and biological properties. Differences at the significance level of p < 0.05 were considered statistically significant. Alpha diversity indexes, including Shannon index, Chao1, Simpson, and abundance-based coverage estimate (ACE), were calculated in QIIME1. Tukey’s HSD test computed alpha index comparison in the R Project (version 3.4.1). The expected sequences were classified into organisms by a naive Bayesian model employing the RDP classifier (version 2.2) based on the SILVA database (version 132) and ITS2 database (version update_2015), with the confidence threshold values ranging from 0.8 to 1 (Nilsson et al. 2019). The abundance statistics of each taxonomy were visualized using Krona (version 2.6). Nonmetric multidimensional scaling (NMDS) base of Bray-Curtis distances analysis was performed using the ‘vegan’ package to visualize microbial community composition. A permutational multivariate ANOVA (PERMANOVA) test was calculated (plotted in R ggplot2) and used to test the effect of slope gradient and slope position on microbial community composition. Redundancy analysis (RDA) performed was adopted to explore the relationships between the composition of bacterial and fungal communities and soil environmental factors.