We jointly assessed the effects of both climate and forest change using the process-based simulation model iLand, asking: How do understory plant communities respond to 21st-century change in a topographically complex mountain landscape, representing a hotspot of plant species richness? Nearly all species persisted in the landscape in 2050, but on average 8% of the species pool was lost by the end of the century. By 2100, landscape mean species richness and understory cover declined (−13% and −8%, respectively), warm-adapted species increasingly dominated plant communities (i.e., thermophilization, +12%), and plot-level turnover was high (62%). Subalpine forests experienced the greatest richness declines (−16%), most thermophilization (+17%), and highest turnover (67%), resulting in plant community homogenization across elevation zones. Climate rather than forest change was the dominant driver of understory responses. The magnitude of unabated 21st-century change is likely to erode plant diversity in a species richness hotspot, calling for stronger conservation and climate mitigation efforts.

Following short-interval versus long-interval fires, live tree stem density was an order of magnitude lower, density of aspen increased, dead woody biomass was reduced by half, and recovery of live biomass and canopy fuels was delayed for at least 30 years. Our results suggest differences in tree regeneration following short-interval versus long-interval fires will be especially pronounced where serotiny was high historically. Propagule limitation will also interact with short-interval fires to diminish tree regeneration but lessen subsequent burn severity. Amplifying driver interactions are likely to threaten forest resilience under expected trajectories of future fire.

Young postfire forests had abundant, densely packed canopy fuels, and both young and mature forests had similar canopy fuel loads and coarse wood biomass. Under similar weather conditions, young and mature forests burned at similar severity. Overall, fuels were weak predictors of burn severity and, surprisingly, better predicted severity under extreme rather than moderate fire weather.