Table 3 Important predictors included in final models and percent variance explained for each fuel response variable. Predictor variables are ordered by importance, and normalized predictor variable importance scores (MIR) ranging from 1 (most important) to zero (least important) are given in parentheses after each predictor variable. See Table 2 for predictor variable definitions
From: Multitemporal lidar captures heterogeneity in fuel loads and consumption on the Kaibab Plateau
Response variable | Important predictors | Var. Exp. (%) |
|---|---|---|
Available canopy fuel | P10.gt2 (1), SKE.gt2 (0.6), D03 (0.6), P50.gt2 (0.5), KUR.gt2 (0.4), D00 (0.4), D02.lt2 (0.3), SSINA (0.3) | 50 |
1- to 1000-h fuels | DEM (1), P05.gt2 (1), D01 (0.6), D00.lt2 (0.6), NPF (0.3) | 39 |
Litter and duff | DEM (1), YSF (0.6), NPF (0.4), D06 (0.3), D03 (0.3), D00 (0.2), | 59 |
Total surface fuel | DEM (1), D03.lt2 (0.6), D02.lt2 (0.5), P90.lt2 (0.5), P10.gt2 (0.5), YSF (0.3), NPF (0.2) | 48 |