Abstract How future pathogens will interact with climate change to affect forests is unknown. While specific predictions of complex interactions may be unreliable, exploring a gradient of disturbance severity and management can be informative. We simulated forests in Acadia National Park (ANP) in Maine, USA, under climate change. Rather than simulate known pathogens, we explored black swan disturbances—that is, unknown pathogens having large consequences. Specifically, we simulated a low and high severity pathogen affecting the dominant species in ANP (red spruce Picea rubens ) along with a drought scenario affecting all species. We coupled these disturbances with management under the resist–accept–direct (RAD) framework: resist management included planting red spruce as a replacement, accept included continuing ANP business‐as‐usual management, and direct included planting novel climate adapted species. Under the black swan disturbances, spruce declined relative to the severity of the disturbance. Resist management resulted in moderate resistance to the loss of red spruce when disturbance severity was low, but had little effect when disturbances were more severe. The direct management resulted in the greatest increase in total biomass. However, this represented the greatest shift in species composition and shifts in the current management approach. Exploring black swan disturbances within the RAD management framework provided a useful intensity gradient of plausible management scenarios. There is huge uncertainty in the structure and function of future forests in ANP. While our results suggest ANP forests will be resilient to climate change, interacting disturbances may result in declines in specific species. In considering these threats, this research provides an assessment of a gradient of management responses.
Duveneck et al. (Fri,) studied this question.