Table 2 A sample of the models tested to predict three-year post-fire mortality of sugar pine using pre-fire variables. All models were mixed effects logistic regression models in which the random effect was plot. Fixed effects varied by model and included raking treatment (Treat), pre-fire blister rust infection status (InfStatus), pre-fire beetle activity (BeetAct), pre-fire tree vigor (Vigor), burn unit (BurnUnit), average litter depth (Avg.Litter), average duff depth (Avg.Duff), average forest floor fuel depth (Avg.Fuel), dbh, and slope. The model in bold was selected as the final model based on AIC. Log L is the Log likelihood value, K is the number of parameters, and AIC is the Akaike Information Criterion score for each model.

From: The Effects of Raking on Sugar Pine Mortality following Prescribed Fire in Sequoia and Kings Canyon National Parks, California, USA