Simulating wind disturbance impacts on forest landscapes: Tree-level heterogeneity matters
Simulating wind disturbance impacts on forest landscapes: Tree-level heterogeneity matters
复制标题
模拟风扰动对森林景观的影响：树级异质性很重要
DOI：
10.1016/j.envsoft.2013.09.018
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
K. Blennow
中科院分区：
文献类型：
--
作者：
R. Seidl;W. Rammer;K. Blennow
风是欧洲森林生态系统中最有害的干扰因素。近年来，大陆尺度的扰动频率和严重程度一直在增加，这一趋势预计将在未来人为气候变化下继续下去。因此，干扰管理对森林的可持续管理越来越重要，需要有工具来评估管理替代办法和气候变化对干扰风险和生态系统服务的影响。在这里，我们提出了一个基于过程的模型，风干扰对森林生态系统的影响，集成到动态景观模拟模型iLand。该模型在单个树的水平上运行，并迭代地模拟风扰动事件，即，在风暴过程中动态地解释森林结构的变化和新产生的边缘。在这方面，考虑了逆风间隙大小和邻近树木的局部遮蔽，并区分了根拔和茎断裂的临界风速。因此，模拟的扰动大小、模式和严重程度是模型的紧急属性。我们评估了新的模拟工具对卫星衍生的数据的影响，风暴古德龙（2005年1月）在瑞典中南部的1391公顷的森林景观。无论是整体损害的百分比（观察：21.7%，模拟：21.4%），以及空间损害模式的比较显示良好的对应关系之间的观测和预测（预测精度：60.4%），如果考虑到完整的卫星衍生的结构和空间异质性的景观。忽视林分条件的林分内异质性，即，许多林分水平风险模型的最新技术水平导致对模拟损害的相当大的低估，支持树水平复杂性对于评估和模拟大规模干扰很重要的观点。敏感性分析进一步表明，风速和土壤冻结的变化可能对扰动面积和斑块大小产生巨大影响。这里介绍的模型是开源的。它可用于研究不同造林系统和未来气候对风风险的影响，以及量化风干扰对生态系统服务（如碳固存）的影响。因此，它有助于提高我们在生态系统管理中应对不断变化的干扰机制的能力。
Wind is the most detrimental disturbance agent in Europe's forest ecosystems. In recent years, disturbance frequency and severity have been increasing at continental scale, a trend that is expected to continue under future anthropogenic climate change. Disturbance management is thus increasingly important for sustainable stewardship of forests, and requires tools to evaluate the effects of management alternatives and climatic changes on disturbance risk and ecosystem services. We here present a process-based model of wind disturbance impacts on forest ecosystems, integrated into the dynamic landscape simulation model iLand. The model operates at the level of individual trees and simulates wind disturbance events iteratively, i.e., dynamically accounting for changes in forest structure and newly created edges during the course of a storm. Both upwind gap size and local shelter from neighboring trees are considered in this regard, and critical wind speeds for uprooting and stem breakage are distinguished. The simulated disturbance size, pattern, and severity are thus emergent properties of the model. We evaluated the new simulation tool against satellite-derived data on the impact of the storm Gudrun (January 2005) on a 1391 ha forest landscape in south central Sweden. Both the overall damage percentage (observation: 21.7%, simulation: 21.4%) as well as the comparison of spatial damage patterns showed good correspondence between observations and predictions (prediction accuracy: 60.4%) if the full satellite-derived structural and spatial heterogeneity of the landscape was taken into account. Neglecting within-stand heterogeneity in forest conditions, i.e., the state-of-the-art in many stand-level risk models, resulted in a considerable underestimation of simulated damage, supporting the notion that tree-level complexity matters for assessing and modeling large-scale disturbances. A sensitivity analysis further showed that changes in wind speed and soil freezing could have potentially large impacts on disturbed area and patch size. The model presented here is available as open source. It can be used to study the effects of different silvicultural systems and future climates on wind risk, as well as to quantify the impacts of wind disturbance on ecosystem services such as carbon sequestration. It thus contributes to improving our capacity to address changing disturbance regimes in ecosystem management.