2.6 Statistical analysis
The normality and homogeneity of variances of the dataset in this study
had been verified. The differences between three groups regarding soil
physical, chemical properties and microbial α-diversity indices had been
obtained by one-way analysis of variance (ANOVA). While group means had
been subjected to Duncan’s test at p <0.05 using a DPS (Data
Processing System) v.7.05. The concentrations of 18 soil metals among
three sampling groups were shown by heatmap, generated by R software
v.3.5.1 through the heatmap package. Principal Co-ordinates Analysis
(PCoA) of soil microbial community based on ASVs level, analysis of
similarities (ANOSIM), and variance partitioning analysis (VPA) for
microbial community composition among groups were all using the vegan
package in R software v.3.5.1.
A network analysis was conducted to reveal the relationship between
bacterial and fungal taxa (relative abundance > 0.1%),
soil metals, and physicochemical properties. We calculated the pairwise
Spearman’s correlation coefficients (p <0.05) using psych
package in R software v.3.5.1 and visualized the network using Gephi
software v.0.9.2. Each node represented one microbial taxon or soil
parameter. Red lines and blue lines represented strong positive and
negative correlations, respectively. The destruction resistance of the
network was generated using R software v.3.5.1 through randomly removing
the nodes and calculating the natural connectivity and network degree
values.
The direct or indirect effects of total petroleum hydrocarbons on soil
parameters, bacterial and fungal diversity, and community compositions
were generated through conducting the Spearman correlation or Mantel
test between matrices (p <0.05).