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