Abstract. Climate change and increased fire are eroding the
resilience of boreal forests. This is problematic because boreal vegetation
and the cold soils underneath store approximately 30 % of all terrestrial
carbon. Society urgently needs projections of where, when, and why boreal
forests are likely to change. Permafrost (i.e., subsurface material that
remains frozen for at least 2 consecutive years) and the thick
soil-surface organic layers (SOLs) that insulate permafrost are important
controls of boreal forest dynamics and carbon cycling. However, both are
rarely included in process-based vegetation models used to simulate future
ecosystem trajectories. To address this challenge, we developed a
computationally efficient permafrost and SOL module named the Permafrost and
Organic LayEr module for Forest Models (POLE-FM) that operates at fine
spatial (1 ha) and temporal (daily) resolutions. The module mechanistically
simulates daily changes in depth to permafrost, annual SOL accumulation, and
their complex effects on boreal forest structure and functions. We coupled
the module to an established forest landscape model, iLand, and benchmarked
the model in interior Alaska at spatial scales of stands (1 ha) to
landscapes (61 000 ha) and over temporal scales of days to centuries. The
coupled model generated intra- and inter-annual patterns of snow
accumulation and active layer depth (portion of soil column that thaws
throughout the year) generally consistent with independent observations in
17 instrumented forest stands. The model also represented the distribution
of near-surface permafrost presence in a topographically complex landscape.
We simulated 39.3 % of forested area in the landscape as underlain by
permafrost, compared to the estimated 33.4 % from the benchmarking
product. We further determined that the model could accurately simulate moss
biomass, SOL accumulation, fire activity, tree species composition, and
stand structure at the landscape scale. Modular and flexible representations
of key biophysical processes that underpin 21st-century ecological
change are an essential next step in vegetation simulation to reduce
uncertainty in future projections and to support innovative environmental
decision-making. We show that coupling a new permafrost and SOL module to an
existing forest landscape model increases the model's utility for projecting
forest futures at high latitudes. Process-based models that represent
relevant dynamics will catalyze opportunities to address previously
intractable questions about boreal forest resilience, biogeochemical
cycling, and feedbacks to regional and global climate.