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.