Statistical analysis
The difference in soil properties and ammonia oxidizers abundances was
assessed by one-way variance analysis (ANOVA) using SPSS Statistics 20
(IBM, USA). Pearson correlation analyses evaluated the relationships
among soil N pools, N transformation rates, and microbial parameters.
Differences at p < 0.05 based on the least significant
differences (LSD) test were statistically significant. All statistical
tests were performed using R v.3.5.3 (R Core Team, 2019). Principal
component analysis (PCA) in the R package ‘vegan’ (Oksanen et al. 2016)
was used to assess ammonia-oxidizer community composition differences
across the different treatments. The microbial co-occurrence network was
inferred from the Sparse Correlations for Compositional data (SParCC)
correlation matrix constructed with the WGCNA package (Langfelder and
Horvath, 2012). The nodes in the network represent OTUs, while the edges
connecting these nodes represent correlations between OTUs. Network
properties were calculated with the “igraph” R package, and we
generated network images with Gephi (http://gephi.github.io/) and
Cytoscape (http://www.cytoscape.org/).