Fig. 2: Importance of explanatory variables identified through machine learning models.

The relative importance of the top 15 (of 39) explanatory variables in predicting speciation rate in 1000 XGBoost bootstrap replicates is plotted for complex models with maximum tree-depth of three a, versus simple models with maximum tree-depth of one b, with model precision indicated by R². The vertical dashed line indicates the threshold of predicting speciation rate by chance expectation alone. Upper and lower importance quantiles (25% and 75%) estimated from 1000 model bootstraps are indicated with black horizontal bars. When interactions are accounted for, the relative importance of several variables shifts, and the R² is improved.