Data and code associated with: The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

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 most likely to change. Permafrost (i.e., subsurface material that remains frozen for at least two 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 the process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a new computationally efficient permafrost and SOL module 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 could generate intra- and inter-annual patterns of snow accumulation and depth to permafrost consistent with independent observations in 17 instrumented forest stands. The model was also skilled at representing the distribution near-surface permafrost presence in a topographically complex landscape. We simulated 34.6% of forested area in the landscape as underlain by permafrost; nearly identical to the estimate of 33.4% of forested area 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.

File list:
Cary_metadata_Hansen_permafrost_SHARE_2022.docx:  complete metadata for all files, including data tables and definitions for all variables.
analysis scripts.zip: R analysis scripts for processing outputs (total of 6 R Markdown files).
executable and source code.zip:  The QT library and iLand executable used in simulations. Also includes source code for iLand version used in simulations (total of 3 files: ilandc_07-28-2022.exe, iland_07-28-2022.exe, src_28.07.2022.zip ).
geospatial data.zip: contains Aspect_repr.tif, an aspect raster for simulated landscape. This product is used in permafrost_SOL-depth_script-1_09-30-2022.Rmd. Permafrost_bore.hole_project.zip: Project directory for recreating stand level simulations of snow depth and permafrost active layer depth. Zip file includes all inputs, project file, and the sqlite databases of outputs.
tables.zip: contains 6 data tables including 342_JFSP_sitedata.txt,  landscape_stand-structure-RSN-validation.txt, SOL_coarse_wood_carbon.txt, 398_2004burns_seedlings.txt, landscape_structure-CAFI-validation.txt, bore.hole.snow.depth.txt, Daily_soil-temp.txt, and AK_CA_Soil_Profile_Synthesis.csv. See Cary_metadata_Hansen_permafrost_SHARE_2022.docx for complete metadata.  
CPCRW_sm_project.zip: Project directory for recreating landscape level simulations of permafrost distribution, stand structure, and fire regime including inputs, project file, and sqlite databases of outputs.

摘要：气候变化与火灾的增加正在侵蚀北方森林的恢复力。此现象颇具挑战性，因为北方植被及其下方的寒冷土壤储存了大约30%的陆地碳。社会迫切需要预测北方森林最有可能发生变化的地点、时间和原因。永久冻土（即连续两年以上保持冻结的地下物质）以及隔热永久冻土的厚土壤表面有机层（SOLs）是北方森林动态和碳循环的重要控制因素。然而，这两个因素很少被纳入用于模拟未来生态系统轨迹的过程型植被模型中。为了应对这一挑战，我们开发了一个新的计算效率高的永久冻土和SOL模块，该模块以精细的空间分辨率（1公顷）和每日时间分辨率运行。该模块从机制上模拟了永久冻土深度每日变化、年度SOL积累及其对北方森林结构和功能的复杂影响。我们将该模块与现有的森林景观模型iLand耦合，并在阿拉斯加内陆以林分（1公顷）至景观（61,000公顷）的尺度，以及从日到世纪的时序尺度上进行了模型校准。耦合模型能够生成与17个仪器林分独立观测一致的年度和年内雪积累及永久冻土深度的模式。该模型在表征复杂地形景观中近地表永久冻土分布方面也表现出色。我们模拟了景观中34.6%的森林面积下有永久冻土；与基准产品中33.4%的森林面积估计几乎相同。我们进一步确定，该模型能够准确模拟景观尺度的苔藓生物量、SOL积累、火灾活动、树种组成和林分结构。在植被模拟中，构建21世纪生态变化的根本生物物理过程的模块化和灵活性表征是减少未来预测不确定性和支持创新环境决策的关键步骤。我们表明，将新的永久冻土和SOL模块与现有的森林景观模型耦合，提高了模型在高纬度地区预测森林未来的实用性。能够表征相关动态的过程型模型将催化解决关于北方森林恢复力、生物地球化学循环以及区域和全球气候反馈等先前难以解决的问题的机会。