MODELING TREE MORTALITY FOLLOWING WILDFIRE IN PINUS-PONDEROSA FORESTSIN THE CENTRAL SIERRA-NEVADA OF CALIFORNIA

We modeled tree mortality occurring two years following wildfire in Pi nus ponderosa forests using data from 1275 trees in 25 stands burned d uring the 1987 Stanislaus Complex fires. We used logistic regression a nalysis to develop models relating the probability of wildfire-induced mortality with tree size and fire severity for Pinus ponderosa, Caloc edrus decurrens, Quercus chrysolepis, and Q. kelloggii. One set of mod els predicts mortality probability as a function of DBH and height of stem-bark char, a second set of models uses relative char height (heig ht of stem-bark char as a proportion of tree height) as the predictor. Probability of mortality increased with increasing height of stem-bar k char and decreased with increasing tree DBH and height. Analysis of receiver operating characteristic (ROC) curves indicated that both set s of models perform well for all species, with 83 to 96 percent concor dance between predicted probabilities and observed outcomes. The model s can be used to predict die probability of post-wildfire mortality of four tree species common in Pinus ponderosa forests in the central Si erra Nevada of California.