Fig. 3: Global maps and environmental drivers of the relative richness of diazotrophs.
From: Anthropogenic climate change may reduce global diazotroph diversity
a Relative richness of terrestrial diazotrophs across the world. Sixty-three covariates (resampled resolution of 0.05°) were used in the final random forest model prediction (training dataset with 10-fold cross-validation R2 = 0.558, testing set with R2 = 0.519; Supplementary Fig. 3). Pixels with missing values for covariates are indicated by blanks. b Latitudinal variation in the relative richness of diazotrophs. The y-axis represents relative richness, and the colour represents the density of the pixels with close relative richness. c Relative importance of environmental covariates in the random forest model. The names of the environmental covariates are given in abbreviated form (Supplementary Table 2). d Importance of individual environmental covariates in the random forest model. The top three indices are the mean annual precipitation (bio_12), soil pH (phh2o), and aridity index (ai). IncNodePurity, or increase in node purity, is measured by the sum of squared residuals and represents the effect of each variable on the heterogeneity of observations at each node of the classification tree, thus reflecting the importance of the variables. Source data are provided as a Source Data file.
