Figure 1. The relationships of bacterial operational taxonomic unit richness (A) and phylogenetic diversity (B) with aridity index based on 97% sequence.

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Figure 1. The relationships of bacterial operational taxonomic unit richness (A) and phylogenetic diversity (B) with aridity index based on 97% sequence identity. The communities were randomly sampled at the 173,260 sequences level. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Figure 2. Non-metric multidimensional scaling (NMDS) ordination of microbial community composition from 54 sites across the transect. The compositional variation is represented with Bray–Curtis distance matrix based on the abundance of OTUs. The two dominant environmental gradients associated with ordination are represented: red lines represent the gradient of aridity index; the sizes of circles indicate the values of pH. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Figure 3. Canonical correspondence analysis (CCA) of the bacterial communities with site abbreviation. Model ANOVA test: *P < 0.05, **P < 0.01, ***P < 0.001. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Figure 4. Relationships between the log of geographic distance, log of environmental distance and bacterial community similarity estimated by the Bray–Curtis index. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Figure 5. Variation partition analysis of the effects of geographic distance and environmental variables on bacterial community structure. Significance (P) was determined by an ANOVA-like permutation test in CCA. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Figure 6. Cluster analysis of bacterial communities based on Bray–Curtis distance matrix. The analysis was performed using vegan package in R. From: Scale-dependent effects of climate and geographic distance on bacterial diversity patterns across northern China's grasslands FEMS Microbiol Ecol. 2015;91(12). doi:10.1093/femsec/fiv133 FEMS Microbiol Ecol | © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com