Data and code associated with: A permafrost and soil-surface organic layer module for simulating high-latitude forests with process-based vegetation models.

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.<br> <strong>File list:</strong><br> <strong>Cary_metadata_Hansen_permafrost_SHARE_2022.docx: </strong> complete metadata for all files, including data tables and definitions for all variables.<br> <strong>analysis scripts.zip:</strong> R analysis scripts for processing outputs (total of 6 R Markdown files).<br> <strong>executable and source code.zip: </strong>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 ).<br> <strong>geospatial data.zip:</strong> contains Aspect_repr.tif, an aspect raster for simulated landscape. This product is used in permafrost_SOL-depth_script-1_09-30-2022.Rmd. <strong>Permafrost_bore.hole_project.zip: </strong>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.<br> <strong>tables.zip:</strong> 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 <em>Cary_metadata_Hansen_permafrost_SHARE_2022.docx</em> for complete metadata. <br> <strong>CPCRW_sm_project.zip:</strong> Project directory for recreating landscape level simulations of permafrost distribution, stand structure, and fire regime including inputs, project file, and sqlite databases of outputs.<br>

**摘要：** 气候变化与野火频发正在削弱北方针叶林（boreal forests）的恢复力。这一状况亟需关注，因为北方植被及其下方的寒冷土壤储存了全球约30%的陆地碳储量。社会亟需能够预测北方森林最易发生变化的区域、时间及驱动因素的相关研究。永久冻土（permafrost，即连续两年及以上处于冻结状态的地下物质）以及起到隔热作用的厚层土壤表层有机层（soil-surface organic layers, SOLs）是调控北方森林动态与碳循环的关键因子，但在用于模拟未来生态系统轨迹的基于过程的植被模型中，这两者却鲜有被纳入考量。
为应对这一挑战，我们开发了一款计算效率优异的新型永久冻土与SOL模块，该模块可在精细的空间（1公顷）与时间（日）分辨率下运行。该模块以机制化方式模拟永久冻土埋藏深度的日变化、SOL的年累积过程，以及二者对北方森林结构与功能的复杂影响。
我们将该模块耦合至已成熟的森林景观模型iLand，并在阿拉斯加内陆地区以林分（1公顷）至景观（61000公顷）的空间尺度，以及日至世纪的时间尺度对模型进行了基准测试。耦合后的模型能够生成与17个布设观测仪器的林分的独立观测结果相符的积雪累积与永久冻土埋藏深度的年内及年际变化模式。该模型还能够精准表征地形复杂景观中近地表永久冻土的分布状况。我们模拟得出该景观中34.6%的森林区域受永久冻土支撑，这与基准数据集得出的33.4%森林区域占比几乎一致。
我们进一步证实，该模型能够在景观尺度上精准模拟苔藓生物量、SOL累积、野火活动、树木物种组成以及林分结构。为降低未来预测的不确定性并支撑创新性环境决策，对支撑21世纪生态变化的关键生物物理过程进行模块化且灵活的表征，是植被模拟领域至关重要的下一步研究方向。我们的研究表明，将新型永久冻土与SOL模块耦合至现有森林景观模型，可提升该模型在高纬度地区预测森林未来动态的实用性。能够表征相关动态过程的基于机制的模型，将为解决此前难以解答的北方森林恢复力、生物地球化学循环以及对区域及全球气候的反馈等问题提供新的契机。

**文件列表：**
1. **Cary_metadata_Hansen_permafrost_SHARE_2022.docx**：涵盖所有文件的完整元数据，包括所有数据表与变量定义。
2. **analysis scripts.zip**：用于处理模型输出的R分析脚本（共6个R Markdown文件）。
3. **executable and source code.zip**：本研究模拟中使用的QT库与iLand可执行文件，同时包含本次模拟所用iLand版本的源代码（共3个文件：ilandc_07-28-2022.exe、iland_07-28-2022.exe、src_28.07.2022.zip）。
4. **geospatial data.zip**：包含坡向栅格文件Aspect_repr.tif，该文件将用于permafrost_SOL-depth_script-1_09-30-2022.Rmd脚本中。
5. **Permafrost_bore.hole_project.zip**：用于复现林分尺度积雪深度与永久冻土活动层深度模拟的项目目录，压缩包包含所有输入文件、项目文件以及输出结果的sqlite数据库。
6. **tables.zip**：包含6个数据表，涵盖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以及AK_CA_Soil_Profile_Synthesis.csv。完整元数据请参见《Cary_metadata_Hansen_permafrost_SHARE_2022.docx》。
7. **CPCRW_sm_project.zip**：用于复现永久冻土分布、林分结构与火况的景观尺度模拟的项目目录，包含所有输入文件、项目文件以及输出结果的sqlite数据库。