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

• Published in: Geoscientific Model Development
• Main Authors: W. D. Hansen, A. Foster, B. Gaglioti, R. Seidl, W. Rammer
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2023
• Subjects: Geology; QE1-996.5; permafrost; Alaska
• Online Access: https://doi.org/10.5194/gmd-16-2011-2023; https://doaj.org/article/53aad86a241240f4b1b4a6250b03b9ba

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 ...