As 21st-century climate and fire activity depart from historical baselines, effects on

forests are uncertain. Forest managers need to predict and monitor forest recovery and fuel

accumulation to anticipate future fire behavior and plan appropriate management activities. We

explored how interactions between climate and fire affected post-fire recovery of subalpine

forests, which were historically resilient to infrequent (100-300 year) severe fire, in Greater

Yellowstone (Northern Rocky Mountains, United States). We sampled paired short- (< 30 year)

and long- (> 125 year) interval post-fire plots last burned between 1988 and 2018 to address two

questions: (1) How do short-interval fire, climate, and other factors (topography, distance to live

edge) interact to affect post-fire forest recovery? (2) How do forest biomass and fuels vary

following short- versus long-interval severe fires? Additionally, a low-cost unpersonned aerial

system (i.e., drone) was flown in a subset of post-fire plots to assess: (3) How do different

methods of drone data collection affect derived measurements of forest structure and detection of

standing dead snags? Mean post-fire stem density was an order of magnitude lower following

short- versus long-interval fires (3,240 versus 28,741 stems ha-1 , respectively). Differences

between paired plots increased with greater climate water deficit normal (𝜌 = 0.67) and were

amplified at longer distances to live forest edge. Unlike conifers, density of aspen (Populus

tremuloides), a deciduous resprouter, increased with short- versus long-interval fire (mean 384

versus 62 stems ha-1 , respectively). Live biomass and canopy fuels remained low nearly 30 years

after short-interval fire, in contrast to rapid recovery after long-interval fire, suggesting that

future burn severity may be reduced for several decades following reburns. Short-interval plots

also had half as much dead woody biomass compared to long-interval plots (60 versus 121 Mg

ha-1 ), primarily due to the absence of large snags. Measurements derived from drone imagery

underestimated tree density in young, dense, post-fire plots but characterized snag and tree

height well. The conventional built-in red, green, and blue light sensor outperformed a separate

sensor that detected near-infrared reflectance, and ground control points did not improve output

accuracy. Overall, our results suggest that a trifecta of short-interval fire, large patch size, and

arid post-fire climate could threaten subalpine forest resilience but also reduce future burn

severity. These findings could help forest managers prioritize opportunities for management

activities or identify areas where forest transitions may be most likely. Identifying reburn

locations may be valuable for planning fire suppression activities or identifying potential

firefighter access or escape routes. Low cost and standardized approaches make drones a

promising technology for collecting forest inventory data.