as implemented in the package and compared the explanatory power of the model with ‘ecodist’ and without the addition of plant community dissimilarity as a predictor variable. In these models, each soil variable was transformed using log or inverse transformations where necessary to approximate a normal distribution, and they were standardized prior to calculating Euclidian distances. MRM was implemented with rank (i.e. Spearman) correlations, and the models “best” containing only soil variables were derived by first including all soil variables and using backwards elimination until all predictors explained significant levels of variation in the response dissimilarities. Results and Discussion The effect of plant species identity on soil communities Overall, the mesocosm soils contained expectedly diverse communities (Fig. S1A). Soil fungal communities were primarily composed of [43% of internal transcribed spacer (ITS) Ascomycota sequence reads, on average], (31%), and (21%); bacterial Basidiomycota Mucoromycota communities were primarily composed of (31% of 16S rRNA gene reads, on Acidobacteria average), (20%), and (16%); protistan communities were Proteobacteria Verrucomicrobia primarily composed of (26%), (25%), (22%), and Rhizaria Amoebozoa Alveolata Stramenopiles (16%); and metazoan communities were primarily composed of (33%), Nematoda Arthropoda (28%), and (15%; Fig. S1B). The structure of these communities was similar to those Annelida found in other temperate grasslands (Leff et al., 2015; Bates et al., 2013; Wu et al., 2011). Plant species identity explained differences in the overall composition of soil fungal (R2 = 0.33; < 0.001), bacterial (R2 = 0.27; = 0.02), protistan (R2 = 0.32; < 0.001), and P P P metazoan (R2 = 0.31; < 0.001) communities (Fig. 1A). Further, these plant species effects P
as implemented in the ‘ecodist’ package and compared the explanatory power of the model with and without the addition of plant community dissimilarity as a predictor variable. In these models, each soil variable was transformed using log or inverse transformations where necessary to approximate a normal distribution, and they were standardized prior to calculating Euclidian distances. MRM was implemented with rank (i.e. Spearman) correlations, and the “best” models containing only soil variables were derived by first including all soil variables and using backwards elimination until all predictors explained significant levels of variation in the response dissimilarities. Results and Discussion The effect of plant species identity on soil communities Overall, the mesocosm soils contained expectedly diverse communities (Fig. S1A). Soil fungal communities were primarily composed of Ascomycota [43% of internal transcribed spacer (ITS) sequence reads, on average], Basidiomycota (31%), and Mucoromycota (21%); bacterial communities were primarily composed of Acidobacteria (31% of 16S rRNA gene reads, on average), Proteobacteria (20%), and Verrucomicrobia (16%); protistan communities were primarily composed of Rhizaria (26%), Amoebozoa (25%), Alveolata (22%), and Stramenopiles (16%); and metazoan communities were primarily composed of Nematoda (33%), Arthropoda (28%), and Annelida (15%; Fig. S1B). The structure of these communities was similar to those found in other temperate grasslands (Leff et al., 2015; Bates et al., 2013; Wu et al., 2011). Plant species identity explained differences in the overall composition of soil fungal (R2 = 0.33; P < 0.001), bacterial (R2 = 0.27; P = 0.02), protistan (R2 = 0.32; P < 0.001), and metazoan (R2 = 0.31; P < 0.001) communities (Fig. 1A). Further, these plant species effects
UK_grassland_ms_2018_01_14_ISME_rev2.docx