Table 1. Variable weightings indicating the importance in final boosted regression tree models for tracking and observer data.
Bathymetry and temperature were reliably the two most important predictors in modeling habitat. Bold numbers highlight the three most important factors for each model. NA, not applicable.
| Observer | Tracking | ||||
| Swordfish | Blue shark | Blue shark | Leatherback | Sea lion | |
| Bottom depth | 32.9 | 47.2 | 15.6 | 14.6 | 49.1 |
| SST mean | 18.0 | 8.0 | 49.3 | 34.7 | 14.3 |
| SSHa | 10.3 | 8.2 | 4.7 | 11.2 | 5.4 |
| Chl-a | 7.9 | 2.7 | 11.0 | 8.9 | 12.2 |
| y-wind | 5.7 | 3.7 | 4.4 | 6.1 | 1.9 |
| Lunar phase | 5.5 | 3.5 | NA | NA | NA |
| Bottom roughness | 5.4 | 5.5 | 4.2 | 11.4 | 3.0 |
| SST SD | 5.3 | 6.7 | 3.2 | 5.1 | 2.8 |
| SSHa SD | 5.1 | 10.2 | 4.3 | NA | 6.0 |
| EKE | 3.9 | 4.4 | 3.4 | 6.1 | 5.3 |