State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, PR China.
J Environ Manage. 2013 Jan 30;115:42-52. doi: 10.1016/j.jenvman.2012.11.004. Epub 2012 Dec 12.
Fuel treatment is assumed to be a primary tactic to mitigate intense and damaging wildfires. However, how to place treatment units across a landscape and assess its effectiveness is difficult for landscape-scale fuel management planning. In this study, we used a spatially explicit simulation model (LANDIS) to conduct wildfire risk assessments and optimize the placement of fuel treatments at the landscape scale. We first calculated a baseline burn probability map from empirical data (fuel, topography, weather, and fire ignition and size data) to assess fire risk. We then prioritized landscape-scale fuel treatment based on maps of burn probability and fuel loads (calculated from the interactions among tree composition, stand age, and disturbance history), and compared their effects on reducing fire risk. The burn probability map described the likelihood of burning on a given location; the fuel load map described the probability that a high fuel load will accumulate on a given location. Fuel treatment based on the burn probability map specified that stands with high burn probability be treated first, while fuel treatment based on the fuel load map specified that stands with high fuel loads be treated first. Our results indicated that fuel treatment based on burn probability greatly reduced the burned area and number of fires of different intensities. Fuel treatment based on burn probability also produced more dispersed and smaller high-risk fire patches and therefore can improve efficiency of subsequent fire suppression. The strength of our approach is that more model components (e.g., succession, fuel, and harvest) can be linked into LANDIS to map the spatially explicit wildfire risk and its dynamics to fuel management, vegetation dynamics, and harvesting.
燃料处理被认为是减轻强烈和破坏性野火的主要策略。然而，如何在景观尺度上布置处理单元并评估其效果对于景观尺度的燃料管理规划来说是困难的。在本研究中，我们使用了一个空间显式模拟模型（LANDIS）来进行野火风险评估和优化景观尺度上的燃料处理布置。我们首先从经验数据（燃料、地形、天气以及火灾点火和规模数据）中计算出一个基线燃烧概率图，以评估火灾风险。然后，我们根据燃烧概率图和燃料负荷图（从树木组成、林分年龄和干扰历史之间的相互作用计算得出）对景观尺度的燃料处理进行优先排序，并比较它们对降低火灾风险的影响。燃烧概率图描述了给定位置燃烧的可能性；燃料负荷图描述了给定位置上高燃料负荷累积的可能性。基于燃烧概率图的燃料处理指定具有高燃烧概率的林分应首先进行处理，而基于燃料负荷图的燃料处理指定具有高燃料负荷的林分应首先进行处理。我们的结果表明，基于燃烧概率的燃料处理大大减少了不同强度火灾的燃烧面积和火灾数量。基于燃烧概率的燃料处理还产生了更多分散和更小的高风险火灾斑块，因此可以提高后续火灾扑救的效率。我们方法的优势在于可以将更多的模型组件（例如，演替、燃料和收获）链接到 LANDIS 中，以绘制空间显式野火风险及其动态，以进行燃料管理、植被动态和收获。
