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).