Fig. 5

Drivers of the proportion (A) and richness (B) of topsoil ARGs globally. A and B include structural equation models assessing the direct and indirect effects of environmental factors on the proportion and richness of ARGs. The proportion of ARGs was determined as the average standardized relative abundance of 285 individual ARGs. We grouped the different categories of predictors (climate, soil properties, vegetation, and MGEs) in the same box for graphical simplicity (these boxes do not represent latent variables). Variables within these boxes are allowed to covary, with the exception of elevation and spatial dissimilarity, which constituted our degree of freedom. Numbers adjacent to arrows are indicative of the effect size of the relationship. Only significant effects (P < 0.05) are plotted. Supplementary Tables 4–5 show the full SEM. F, forests; G, grasslands; S, shrublands. MAT, mean annual temperature. PSEA, precipitation seasonality. TSEA, temperature seasonality. There was a nonsignificant deviation of the data from the model (χ² = 0.10, df = 1; P = 0.75; RMSEA P = 0.93; bootstrap P = 0.71). C includes selected scatter and boxplots showing the regression between environmental factors and soil ARGs. Red lines are Loess regressions. MGEs includes both richness and proportions. Y-axis in C is shown in log scale. Units and acronyms are available in Supplementary Table 3