2.5 Statistical analyses
Significant differences of treatments on soil physicochemical properties, microbial biomass and alpha diversity indices for microbial communities were detected by One-way analysis-of-variance (ANOVA) followed by a least significant difference (LSD) multiple comparison using SPSS version 17.0 (SPSS Inc., Chicago, IL, United States). Meanwhile, in order to visually display significant differences of different treatments on soil physicochemical properties and microbial biomass, we classified thirteen treatments to five treatments for further One-way analysis: CK, C(C-N0), C-N(C-N1, C-N2, C-N3), C-M (C-M1-N0, C-M2-N0), C-M-N(C-M1-N1,C-M1-N2,C-M1-N3; C-M2-N1,C-M2-N2,C-M2-N3). Univariate analysis of general linear model (GLM) was used to analyze the interaction of incubation time and treatments. Heatmaps were generated using Omicsmart, a dynamic real-time interactive online platform for data analysis(http://www.omicsmart.com). Alpha diversity indexes (including Chao1, Shannon and Simpson) were calculated using QIIME software. According to a Bray-Curtis similarity matrix, principal coordinates analysis (PCoA) was conducted to analyze the overall differences in microbial communities structures among different treatments. In addition, redundancy analysis (RDA) was aimed to assess the effects of soil physicochemical properties and microbial biomass on bacterial and fungal community composition at phylum level and to extract key soil properties driving the variability in bacterial and fungal community composition after addition of amendments.
Results