TABLE 2.
Top 10 environmental predictors contributing to the optimal model, in order of highest contribution to lowest.
| Variable name | Contribution (%) | Permutation importance |
|---|---|---|
| Mean temperature of wettest quarter (BIO8) | 41.26 | 8.83 |
| Soil field capacity (fc_gNATSGO) | 23.13 | 20.76 |
| Average precipitation in month 09 (prec_09) | 7.50 | 4.44 |
| Average precipitation in month 01 (prec_01) | 4.90 | 19.73 |
| Sum of months with a mean temperature over 5°C × Number of days (growingDegDays5) | 4.85 | 1.91 |
| Elevation | 3.67 | 16.91 |
| Average solar radiation in month 04 (prec_04) | 3.56 | 1.96 |
| Mean monthly potential evapotranspiration of the driest quarter (PETDriestQuarter) | 2.21 | 2.68 |
| Terrain roughness index (tri) | 2.15 | 3.55 |
| Soil available water capacity (awc_gNATSGO) | 1.74 | 2.83 |
Note: Percent contribution is the increase in regularized gain, per every iteration of developing the optimal model, converted to percentage. Permutation importance measures the decrease in AUCtrain by permuting values of the training points in each variable after the model has been generated and converted to percentage (Phillips, 2017).