Doctoral Dissertation Research: Using Neutral Models to Evaluate the Effect of Topography on Landscape Patterns of Fire Severity: A Case Study of Lassen Volcanic National Park

博士论文研究：利用中性模型评估地形对火灾严重程度景观格局的影响：以拉森火山国家公园为例

• 批准号: 0928705
• 负责人: Alan Taylor
• 金额: $ 1.2万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928705&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Using; Neutral

Fire has become an increasingly important disturbance to understand due to recent increases in fire size and severity, along with growing human habitation in rural areas. Causes of spatial variation in fire severity across landscapes include daily weather conditions, fire suppression and fuel build up, other past management action, and climate. Fire severity patch location could be stochastic, or fixed in space by topographic influences. However, quantifying the effect of topography on observed patterns of fire severity patches is difficult because fires are stochastic events burning through dynamic and heterogeneous fuel, weather, and historic management conditions. Neutral simulation models will allow this research to hold these confounding factors constant to assess the interaction of topography on predicted fire intensity. This research will address the following questions, using Lassen Volcanic National Park as a case study: 1) What is the distribution of forest surface and canopy fuels and how are those fuels related to the underlying biophysical landscape? 2) What is the effect of topography on fire intensity for a landscape of homogenous fuels burning under constant weather conditions? 3) Do observed patterns of high intensity fire match either the hypothetical neutral model results or the results from fire simulation of real landscape conditions using mapped surface and canopy fuels? Canopy fuels will be mapped by combining field measurements with topographic information and remotely sensed Landsat data within a classification and regression tree model to predict canopy fuel loads across the landscape. A neutral model approach to fire behavior modeling will compare hypothetical landscapes with both real landscapes and historical data on fire severity to assess the strength of topographic controls on fire intensity and the usefulness of this novel approach.The results of this study will address the role of topography in creating heterogeneity in vegetation community structure and composition across the landscape through its influence on fire intensity. Furthermore, this research will evaluate the impacts of fire suppression on changing the landscape location of high intensity fire-created patches. Some types of vegetation, especially in Lassen Volcanic National Park, but also in other locations throughout California and the US west, require high severity fire that has been vigorously suppressed. Using neutral models to assess the potential for high severity fire to create heterogeneity on the landscape will help both resource managers and fire fighters to make better decisions regarding wildfires, Wildfire Use, prescribed fire, and other fuel treatments in highly altered forests. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.

由于近年来火灾规模和严重程度的增加，以及农村地区人类居住的增加，火灾已经成为越来越重要的干扰因素。不同景观的火灾严重程度的空间差异包括日常天气条件、灭火和燃料积累、其他过去的管理行动和气候。火灾严重性斑块的位置可能是随机的，或受地形影响在空间上固定。然而，量化地形对火灾严重程度斑块观测模式的影响是困难的，因为火灾是通过动态和异质燃料、天气和历史管理条件燃烧的随机事件。中性模拟模型将允许本研究保持这些混杂因素不变，以评估地形对预测火灾强度的相互作用。本研究将以拉森火山国家公园为例，解决以下问题：1)森林表面和树冠燃料的分布是什么？这些燃料与潜在的生物物理景观有何关系？2)对于在恒定天气条件下均质燃料燃烧的景观，地形对火灾强度的影响是什么？3)观察到的高强度火灾模式是否与假设的中性模型结果或使用映射的地表和树冠燃料对真实景观条件进行火灾模拟的结果相匹配？在分类和回归树模型中，将现场测量与地形信息和遥感Landsat数据相结合，绘制树冠燃料图，以预测整个景观的树冠燃料负荷。火灾行为建模的中性模型方法将比较假设景观与真实景观和火灾严重程度的历史数据，以评估地形控制对火灾强度的强度和这种新方法的实用性。本研究的结果将通过其对火灾强度的影响来解决地形在整个景观中产生植被群落结构和组成异质性的作用。此外，本研究将评估灭火对改变高强度火灾斑块景观位置的影响。某些类型的植被，特别是拉森火山国家公园的植被，以及加州和美国西部的其他地区的植被，需要高强度的火灾，这些火灾已经被大力扑灭。使用中性模型来评估高严重性火灾在景观上造成异质性的可能性，将有助于资源管理者和消防员在高度改变的森林中就野火、野火使用、规定火灾和其他燃料处理做出更好的决策。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。