2.6 | Statistical analysis
All statistical analyses were conducted in R 4.0.2 (R Core Team, 2020).
We used microbial OTU richness as an index of microbial diversity. A
t-test was used to evaluate the differences in microbial richness
between rhizosphere and non-rhizosphere. Differences in microbial
community composition between the two regions were evaluated using
permutational multivariate analysis of variance (PERMANOVA) with the
function “adonis” in the package “vegan” with 999 permutations
(Oksanen et al., 2020), and visualized by the principal coordinate
analysis (PCoA). One-way ANOVA followed by Tukey-Test was used to assess
the effects of grazing intensity on microbial richness,
composition
(i.e., the relative abundance of main microbial taxa), biotic variables
(shoot biomass, root biomass, root total carbon, and root total nitrogen
of C. songorica ), and abiotic variables (concentrations of total
carbon, nitrogen, and phosphorus, concentrations of available nitrogen
and phosphorus, soil pH and soil moisture). Prior to analyses,
Shapiro-Wilks was used for normal distribution evaluation, while
Bartlett’s test for homogeneity of the data. The dissimilarity in
microbial community composition was determined by the Bray-Curtis
distance among treatments, performed with the “vegdist” function in
package “vegan” (Oksanen et al., 2020).
A Mantel test was used to evaluate how changes in microbial community
diversity or composition are related to biotic and abiotic variables by
the “mantel test” function in the package “vegan”, and visualized by
the package “linkET” (Huang et al., 2021). The multicollinearity of
variables was assessed based on variance inflation factors (VIF), and
those with a VIF value less than 10 were regarded as variables with low
collinearity. The relative importance of variables in affecting
microbial richness and composition was evaluated with the package of
“rdacca.hp” (Lai et al., 2021).