Thom Dominik, Rammer Werner, Albrich Katharina, Braziunas Kristin H, Dobor Laura, Dollinger Christina, Hansen Winslow D, Harvey Brian J, Hlásny Tomáš, Hoecker Tyler J, Honkaniemi Juha, Keeton William S, Kobayashi Yuta, Kruszka Sofia Saenz, Mori Akira, Morris Jenna E, Peters-Collaer Stephen, Ratajczak Zak, Simensen Trond, Storms Ilié, Suzuki Kureha F, Taylor Anthony R, Turner Monica G, Willis Susan, Seidl Rupert
Ecosystem Dynamics and Forest Management Group, School of Life Sciences, Technical University of Munich, Hans‑Carl‑Von‑Carlowitz‑Platz 2, 85354 Freising, Germany.
Gund Institute for Environment, University of Vermont, 617 Main Street, Burlington, VT 05405, USA.
Data Brief. 2024 Jun 26;55:110662. doi: 10.1016/j.dib.2024.110662. eCollection 2024 Aug.
Understanding the impacts of changing climate and disturbance regimes on forest ecosystems is greatly aided by the use of process-based models. Such models simulate processes based on first principles of ecology, which requires parameterization. Parameterization is an important step in model development and application, defining the characteristics of trees and their responses to the environment, i.e., their traits. For species-specific models, parameterization is usually done at the level of individual species. Parameterization is indispensable for accurately modeling demographic processes, including growth, mortality, and regeneration of trees, along with their intra- and inter-specific interactions. As it is time-demanding to compile the parameters required to simulate forest ecosystems in complex models, simulations are often restricted to the most common tree species, genera, or plant-functional types. Yet, as tree species composition might change in the future, it is important to account for a broad range of species and their individual responses to drivers of change explicitly in simulations. Thus, species-specific parameterization is a critical task for making accurate projections about future forest trajectories, yet species parameters often remain poorly documented in simulation studies. We compiled and harmonized all existing tree species parameters available for the individual-based forest landscape and disturbance model (iLand). Since its first publication in 2012, iLand has been applied in 50 peer-reviewed publications across three continents throughout the Northern Hemisphere (i.e., Europe, North America, and Asia). The model operates at individual-tree level and simulates ecosystem processes at multiple spatial scales, making it a capable process-based model for studying forest change. However, the extensive number of processes and their interactions as well as the wide range of spatio-temporal scales considered in iLand require intensive parameterization, with tree species characterized by 66 unique parameters in the model. The database presented here includes parameters for 150 temperate and boreal tree species and provenances (i.e., regional variations). Excluding missing values, the database includes a total of 9,249 individual parameter entries. In addition, we provide parameters for the individual susceptibility of tree species to wind disturbance (five parameters) for a subset of 104 tree species and provenances (498 parameter entries). To guide further model parameterization efforts, we provide an estimate of uncertainty for each species based on how thoroughly simulations with the respective parameters were evaluated against independent data. Our dataset aids the future parameterization and application of iLand, and sets a new standard in documenting parameters used in process-based forest simulations. This dataset will support model application in previously unstudied areas and can facilitate the investigation of new tree species being introduced to well-studied systems (e.g., simulating assisted migration in the context of rapid climate change). Given that many process-based models rely on similar underlying processes our harmonized parameter set will be of relevance beyond the iLand community. Our work could catalyze further research into improving the parameterization of process-based forest models, increasing the robustness of projections of climate change impacts and adaptation strategies.
基于过程的模型极大地有助于理解气候变化和干扰格局对森林生态系统的影响。此类模型基于生态学的第一原理模拟过程,这需要进行参数化。参数化是模型开发和应用中的重要一步,它定义了树木的特征及其对环境的响应,即它们的性状。对于特定物种的模型,参数化通常在单个物种层面进行。参数化对于准确模拟树木的生长、死亡和更新等种群动态过程以及它们的种内和种间相互作用是必不可少的。由于在复杂模型中编译模拟森林生态系统所需的参数耗时较长,模拟通常仅限于最常见的树种、属或植物功能类型。然而,由于未来树种组成可能会发生变化,在模拟中明确考虑广泛的物种及其对变化驱动因素的个体响应非常重要。因此,特定物种的参数化是对未来森林轨迹做出准确预测的关键任务,但物种参数在模拟研究中往往记录不完善。我们整理并统一了可用于基于个体的森林景观和干扰模型(iLand)的所有现有树种参数。自2012年首次发布以来,iLand已在北半球三大洲(即欧洲、北美和亚洲)的50篇同行评审出版物中得到应用。该模型在单株树水平上运行,并在多个空间尺度上模拟生态系统过程,使其成为研究森林变化的一个有能力的基于过程的模型。然而,iLand中大量的过程及其相互作用以及所考虑的广泛时空尺度需要密集的参数化,该模型中树种的特征是有66个独特的参数。这里展示的数据库包括150种温带和寒带树种及其种源(即区域变异)的参数。排除缺失值后,数据库总共包含9249个个体参数条目。此外,我们为104个树种及其种源的子集(498个参数条目)提供了树种对风干扰的个体敏感性参数(五个参数)。为了指导进一步的模型参数化工作,我们根据使用相应参数的模拟与独立数据进行评估的彻底程度,对每个物种的不确定性进行了估计。我们的数据集有助于iLand未来的参数化和应用,并为记录基于过程的森林模拟中使用的参数设定了新的标准。这个数据集将支持在以前未研究过的地区应用模型,并有助于研究引入到已充分研究系统中的新树种(例如,在快速气候变化的背景下模拟辅助迁移)。鉴于许多基于过程的模型依赖于相似的基础过程,我们统一的参数集将超出iLand社区具有相关性。我们的工作可以促进进一步研究,以改进基于过程的森林模型的参数化,提高气候变化影响预测和适应策略的稳健性。