Disequilibrium of fire-prone forests sets the stage for a rapid decline in conifer dominance during the 21stcentury

As trees are long-lived organisms, the impacts of climate change on forest communities may not be apparent on the time scale of years to decades. While lagged responses to environmental change are common in forested systems, potential for abrupt transitions under climate change may occur in environments where alternative vegetation states are influenced by disturbances, such as fire. The Klamath mountains (northern California and southwest Oregon, USA) are currently dominated by carbon rich and hyper-diverse temperate conifer forests, but climate change could disrupt the mechanisms promoting forest stability– regeneration and fire tolerance— via shifts in the fire regime in conjunction with lower fitness of conifers under a hotter climate. Understanding how this landscape will respond to near-term climate change (before 2100) is critical for predicting potential climate change feedbacks and to developing sound forest conservation and management plans. Using a landscape simulation model, we estimate that 1/3 of the Klamath could transition from conifer forest to shrub/hardwood chaparral, triggered by an enhanced fire activity coupled with lower post-fire conifer establishment. Such shifts were more prevalent under higher climate change forcing (RCP 8.5) but were also simulated under the climate of 1950-2000, reflecting the joint influences of early warming trends and historical forest legacies. Our results demonstrate that there is a large potential for loss of conifer forest dominance—and associated carbon stocks and biodiversity- in the Klamath before the end of the century, and that some losses would likely occur even without the influence of climate change. Thus, in the Klamath and other forested landscapes subject to similar feedback dynamics, major ecosystem shifts should be expected when climate change disrupts key stabilizing feedbacks that maintain the dominance of long-lived, slowly regenerating trees.