Pre-impact forest composition and ongoing tree mortality associated with sudden oak death in the Big Sur region; California

Mixed-evergreen forests of central coastal California are being severely impacted by the recently introduced plant pathogen, Phytophthora ramorum. We collected forest plot data using a multi-scale sampling design to characterize pre-infestation forest composition and ongoing tree mortality along environmental and time-since-fire gradients. Vegetation pattern was described using trend surface analysis, spatial autocorrelation analysis and redundancy analysis. Species-environment associations were modeled using non-parametric multiplicative regression (NPMR). Tanoak (Lithocarpusdensiflorus) mortality was analyzed with respect to environmental and biotic factors using trend surface analysis and multivariate regression. Mixed-evergreen forest occurs throughout the Big Sur region but is most widespread in the north, on north facing slopes, at mid-elevations near the coast. Relative basal area of the dominant tree species changes fairly predictably from north to south and from coast to interior in relation to mapped patterns of precipitation, temperature factors and soil characteristics. Most dominant tree species sprout vigorously after fire. The forests experience a mixed-fire regime in this region ranging from low severity understory burns to high severity crown fires, with the latter increasing above the marine inversion layer and at more interior locations. Ceanothus spp. can dominate mixed-evergreen sites for several decades after severe fires. All of the dominant broadleaf evergreen tree species are hosts of P. ramorum, although not all will die from infection. Tanoak mortality decreases from northwest to southeast and is significantly correlated with climate, especially growing degree days and mean annual precipitation, and with basal area of the foliar host bay laurel (Umbellularia californica) in a 0.5–1 ha neighborhood. Adaptive management of mixed-evergreen forest to mitigate P. ramorum impacts in the region will need to consider large local and regional variation in forest composition and the potentially strong interactions between climate, fire, forest composition and disease severity.