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.