Responses of oaks and tanoaks to the sudden oak death pathogen after 8 y of monitoring in two coastal California forests

Sudden oak death, caused by Phytophthora ramorum, is widely established in mesic forests of coastal central and northern California. In 2000, we placed 18 plots in two Marin County sites to monitor disease progression in coast live oaks (Quercus agrifolia), California black oaks (Q. kelloggii), and tanoaks (Lithocarpus densiflorus), the species that are most consistently killed by the pathogen in these areas. Through early 2008, the numbers of newly infected trees increased for all species. The infection rate for trees that were asymptomatic in 2000 was 5.0% y−1 for coast live oaks, 4.1% y−1 for black oaks and 10.0% y−1 for tanoaks. Mortality rates were 3.1% y−1 for coast live oaks, 2.4% y−1 for black oaks, and 5.4% y−1 for tanoaks. Mortality not attributed to P. ramorum was 0.54% y−1 for coast live oaks, and 0.75% y−1 for tanoaks. Weibull survival models of trees that were asymptomatic in 2000 provided overall median survival times of 13.7 y for coast live oaks, 13.8 y for black oaks, and 8.8 y for tanoaks. Survival of infected (bleeding) trees declined to 9.7 y for coast live oaks, 6.2 y for black oaks, and 5.8 y for tanoaks. Ambrosia beetle attacks on bleeding trees further reduced modeled survival times by 65–80%, reaffirming the earlier finding that beetle attacks on bleeding cankers considerably reduce survival. Across all plots, the modeled time for 90% of trees that were asymptomatic in 2000 to become infected is 36.5 y for coast live oaks and 15.4 y for tanoaks. There was a trend toward higher infection rates as tree diameter increased. Greater than 90% of living coast live oaks that failed during the study had extensive beetle tunneling at the site of the break. Disease intensity in coast live oaks at the plot level was positively associated with bay laurel (Umbellularia californica) basal area and negatively associated with Pacific madrone (Arbutus menziesii) basal area. This study demonstrates the use of survival modeling to characterize the effects of epidemic disease on different species and to project the future of forests infected with tree pathogens.