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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.

The boreal zone of Alaska is dominated by interactions between disturbances, vegetation, and soils. These interactions are likely to change in the future through increasing permafrost thaw, more frequent and intense wildfires, and vegetation change from drought and competition. We utilize an individual tree-based vegetation model, the University of Virginia Forest Model Enhanced (UVAFME), to estimate current and future forest conditions across sites within interior Alaska. We updated UVAFME for application within interior Alaska, including improved simulation of permafrost dynamics, litter decay, nutrient dynamics, fire mortality, and postfire regrowth. Following these updates, UVAFME output on species-specific biomass and stem density was comparable to inventory measurements at various forest types within interior Alaska. We then simulated forest response to climate change at specific inventory locations and across the Tanana Valley River Basin on a 2 × 2 km2 grid. We derived projected temperature and precipitation from a five-model average taken from the CMIP5 archive under the RCP 4.5 and 8.5 scenarios. Results suggest that climate change and the concomitant impacts on wildfire and permafrost dynamics will result in overall decreases in biomass (particularly for spruce (Picea spp.)) within the interior Tanana Valley, despite increases in quaking aspen (Populus tremuloides) biomass, and a resulting shift towards higher deciduous fraction. Simulation results also predict increases in biomass at cold, wet locations and at high elevations, and decreases in biomass in dry locations, under both moderate (RCP 4.5) and extreme (RCP 8.5) climate change scenarios. These simulations demonstrate that a highly detailed, species interactive model can be used across a large region within Alaska to investigate interactions between vegetation, climate, wildfire, and permafrost. The vegetation changes predicted here have the capacity to feed back to broader scale climate-forest interactions in the North American boreal forest, a region which contributes significantly to the global carbon and energy budgets.

Mean annual temperatures in the western United States have increased in the last few decades, and during the 21st century, it is predicted that this warming trend will continue. In the subalpine zone of the Rocky Mountains, this warming is also predicted to increase the frequency and severity of spruce beetle outbreaks. Climate change itself may also affect vegetation within the Rocky Mountains, potentially leading to shifts in species compositions. These forests are a crucial part of the US’s carbon budget, thus it is important to analyze how climate change and bark beetles in conjunction will affect the biomass and species composition of vegetation in the subalpine zone. UVAFME is an individual-based gap model that simulates the biomass and species composition of a forested landscape through time. UVAFME is first calibrated and parameterized to the southern Rocky Mountain landscape using data on species composition, climate, and site conditions. Species-specific parameter inputs for the 11 major Rocky Mountain species are derived from the scientific literature. The model is then quantitatively and qualitatively validated at two Rocky Mountain sites in Wyoming and Colorado. Results show that UVAFME accurately simulates the vegetation dynamics along an elevation gradient. UVAFME output on size structure (stems ha-1 size class-1) and species-specific biomass (tonnes C ha-1) is comparable to forest inventory data at those locations. A climate sensitivity test is performed in which temperature is first increased linearly by 2°C over 100 years, stabilized for 200 years, cooled back to present climate values over 100 years, and again stabilized for 200 years. This test was conducted to determine what effect elevated temperatures may have on vegetation zonation, and how lasting the changes may be. Results show that elevated temperatures within the southern Rocky Mountains may lead to persistent decreases in biomass and changes in forest composition as species migrate upslope. Without the effect of disturbances, long-term output from the subalpine zone at the southern WY site shows periodic behavior between Engelmann spruce and subalpine fir, indicating that periodicities in forested ecosystems may be more common than previously thought. UVAFME is then updated with a spruce beetle subroutine created for this study that calculates the probability for beetle infestation of each tree on a plot. This probability is based on site characteristics, such as mean spruce size and plot-level basal area; climate factors, such as temperature; and individual tree characteristics, such as tree size, stress level, and proximity to other infested trees. To determine the net effect of both climate and beetle infestation on subalpine vegetation, UVAFME is then run with multiple scenarios that combine beetle infestation with current or altered climate at sites across the Wyoming and Colorado Rocky Mountains. Climate change projections are from the NCAR Community Earth System Model output for the A1B and A2 IPCC scenarios. These results are compared among the different scenarios. Output from these tests show that the combination of spruce beetle infestations and increasing temperatures will cause a greater loss of Engelmann spruce biomass than either climate change or beetle infestation alone. The combination of spruce beetles and climate change additionally results in a further increase in the dominance of lower elevation species, such as lodgepole pine, ponderosa pine, and Douglas-fir. These results are an important step in understanding the possible futures for the vegetation of the subalpine zone in the Rocky Mountains.

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