Predicting mortality for five California conifers following wildfire

Abstract

Fire injury was characterized and survival monitored for 5677 trees >25 cm DBH from five wildfires in California that occurred between 2000 and 2004. Logistic regression models for predicting the probability of mortality 5-years after fire were developed for incense cedar ( Calocedrus decurrens (Torr.) Florin), white fir ( Abies concolor (Gord. & Glend.) Lindl. ex Hildebr.), sugar pine ( Pinus lambertiana Douglas), Jeffrey pine ( P. jeffreyi Balf.), and ponderosa pine ( P. ponderosa C. Lawson). Differences in crown injury variables were also compared for Jeffrey and ponderosa pine. Most mortality (70–88% depending on species) occurred within 2 years post-wildfire and had stabilized by year 3. Crown length and crown volume injury variables predicted tree mortality equally well; however, the variables were not interchangeable. Crown injury and cambium kill rating was significant in predicting mortality in all models. DBH was only a significant predictor of mortality for white fir and the combined ponderosa and Jeffrey pine models developed from the McNally Fire; these models all predicted increasing mortality with increasing tree size. Red turpentine beetle ( Dendroctonus valens) was a significant predictor variable for sugar pine, ponderosa pine, and Jeffrey pine; ambrosia beetle ( Trypodendron and Gnathotrichus spp.) was a significant predictor variable for white fir. The mortality models and post-fire tree survival characteristics provide improved prediction of 5-year post-wildfire tree mortality for several California conifers. The models confirm the overall importance of crown injury in predicting post-fire mortality compared to other injury variables for all species. Additional variables such as cambium kill, bark beetles, and tree size improved model accuracies, but likely not enough to justify the added expense of data collection.