2.6 Statistical analysis
Statistical analyses were performed using the SPSS 22.0 software package
for Windows (SPSS Inc., Chicago, IL, USA). All statistical tests
performed in this study were considered significant at P< 0.05. The effects of different treatments on soil properties
and microbial richness indices were calculated using one-way analysis of
variance (ANOVA) with Tukey’s multiple comparison test. Normal
distribution and homogeneity of variance were verified using the
Bartlett’s and Dunnett’ tests. We used Pearson’s correlation coefficient
analyses to determine whether there was significant correlation between
soil properties with fungal relative abundance and diversity indices.
A principal component analysis (PCA) was performed on the first 20
dominant fungal genera (the relative abundance of the major 20 dominant
fungal genera reached 98%) and used to visualize in composition and
structure of the fungal communities among the four treatments. The
correlation of multiple variations between soil properties and community
composition was shown by a redundancy analysis (RDA) using CANOCO 5.0
[27]. The manual forward-selection procedure was used in the RDA to
determine significance of environmental variables (P < 0.05)
using a Monte Carlo test with 499 permutations. The relationship between
N2O emission and microbial abundance was further
validated by regression analysis.