The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

• Published in: Geoscientific Model Development 2023-04, Vol.16 (7), p.2011-2036
• Main Authors: Hansen, Winslow D, Foster, Adrianna, Gaglioti, Benjamin, Seidl, Rupert, Rammer, Werner
• Format: Article
• Language: English
• Subjects: Accumulation; Active layer; Analysis; Biogeochemical cycles; Boreal forests; Carbon cycle; Climate change; Climate models; Climatic changes; Cold storage; Community composition; Decision making; Dynamics; Energy; Environment models; Forest ecosystems; Forests; Global climate; Heat conductivity; Landscape; Modelling; Modular structures; Modules; Organic soils; Permafrost; Plant species; Resilience; Simulation; Snow accumulation; Soil; Soil columns; Soil layers; Soils; Species composition; Stand structure; Taiga; Thaws; Trends; Vegetation
• ISSN: 1991-9603; 1991-959X; 1991-962X; 1991-9603; 1991-962X
• DOI: 10.5194/gmd-16-2011-2023

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 a