Statistical analyses
Effects of plant richness and soil moisture content on soil bacterial
and fungal community compositions were examined using the distance-based
redundancy analysis (db-RDA). Microbial OTU composition data were
Hellinger transformed, and Bray-Curtis dissimilarity was used to measure
community distance. Plant richness and log-transformed soil moisture
content (the average values of mesocosms over the phase I) were used as
explanatory variables. The db-RDAs were performed in R using
“capscale” function in package “vegan” (Oksanen et al. 2019).
To evaluate effects of plant species richness and soil moisture
treatments on plant and soil variables in Phase I (i.e., soil bacterial
and fungal diversity, the OTU richness and relative abundance of AMF and
fungal pathogens, community biomass, BE, CE and SE), we performed
general linear mixed-effect models using the “lme” function in R
package “nlme”. Plant species richness (log-transformed) and soil
moisture treatments in Phase I were included as fixed factors. Separate
regression analyses were then performed to test whether there were
linear relationships between plant species richness and these response
variables in each soil moisture treatment. Plant community compositions
were used as random factor in the models mentioned above.
To test effects of plant species richness, soil moisture treatments from
Phases I and II on plant variables of Phase II (i.e., plant community
biomass, BE, CE and SE), we performed general linear mixed-effect
models. Plant species richness, soil moisture treatments from Phases I
and II were included as fixed factors, and plant community compositions
and mesocosms that provided soil inoculums were used as the random
factors. Plant species richness was log-transformed. The between-group
comparisons were performed using the Tukey’s HSD tests. All analyses
were conducted in R (R development core team 2020).