Fig. 5

Zero/one inflated beta regression models for each of the eight individual burn severity metrics with RdNBR (mean composite method) as the predictor variable. In the first column, the no reburn shows model prediction values for non-reburns, while the reburn (1st fire not stand replacing) represents reburns where the first fire was non-stand replacing and the reburn (1st fire stand replacing) represents reburns where the first fire was stand replacing (A, C, E, G, I, K, M, O, Q). The polygon around each line shows 95% confidence around mean predicted values from bootstrapping. Gray dots are the raw data points from the 299 sampled plots. The second column contains AUC values for each of the eight regression models across five thresholds of burn severity (which were created as dichotomization thresholds to produce ROC curves). Overall AUC values represent overall average across five thresholds (B, D, F, H, J, L, N, P, R)