CNH-Ex: Coupling Burning Practices, Vegetation Cover Change, and Fire Regimes to Determine Fire-Emission Dynamics

该项目的重点是改进对地球上燃烧最频繁和最广泛的地区--非洲稀树草原--的排放量的估计。稀树草原大火排放大量温室气体和气溶胶颗粒。虽然越来越多的人认识到这些火灾在全球碳循环中发挥着重要作用，但对其排放量的准确估计很少，而且西非是该大陆最活跃的火灾地区，因此没有人对其排放量进行准确估计。这一跨学科研究项目将开发排放动态模型，通过将火灾制度的变化与土地利用和土地覆盖模式的变化联系起来，确定排放如何随时间变化。对稀树草原排放量的现有估计包含高度的不确定性，因为它们是基于对复杂地貌的非常广泛的概括。为了改进排放估算，调查人员将使用一种新的方法，根据纵火者的实际燃烧实践开发一个模型。在现有数据库的基础上，他们将开发一个系统，根据消防用户的定义对稀树草原植被类型进行分类，并将这一分类方案与从卫星图像得出的消防地图联系起来。这些数据将与包括二氧化碳、一氧化碳和甲烷在内的关键温室气体排放的现场测量相结合。这些数据将被分析，并与土地利用和覆盖变化的数据相结合，以开发一个排放如何随时间变化的模型。这些分析的结果将产生对严重燃烧的西非稀树草原排放量的第一批准确估计之一，这些估计将被用来量化现有排放估计中的误差来源。该项目将提供一种建立在非洲消防用户做法基础上的新排放模式，以及第一批基于非洲土地利用和土地覆盖变化的消防制度动态模式之一。项目结果将用于预测非洲大陆火灾排放的变化，新模型产生的结果将为那些试图改进全球火灾排放模型的人提供有价值和准确的数据。该项目将通过披露与全球规模排放模型中高度不确定相关的领域，并提出改进方法，提供急需的关于火灾制度的地方尺度信息。政府间气候变化专门委员会要求排放估计数包括对不确定性的评估。这个项目将提供这样的估计。该项目将通过促进研究生研究来加强研究能力。它将促进美国和非洲研究人员之间的合作关系。调查人员将帮助举办“火灾研讨会”，在研究区域传播成果，目的是改善目前因缺乏数据而受阻的地方和区域火灾管理工作。这些研讨会将提供一个论坛，探讨向研究区域以外地区的当地居民传播科学信息的更有效方式。该项目得到了美国自然与人类耦合系统动力学(CNH)计划的支持。

This project focuses on improving estimates of emissions from the most frequently and widely burned areas on Earth, the savanna in Africa. Savanna fires emit large quantities of greenhouse gases and aerosol particles. While it is increasing recognized that these fires play an important role in the global carbon cycle, there are few accurate estimates of their emissions and none from West Africa which is that continent's most active fire region. This interdisciplinary research project will develop a model of emission dynamics to determine how emissions change over time by linking changes in the fire regimes to changes in land-use and land-cover patterns. Available estimates of emissions from savannas contain high levels of uncertainty, because they have been based on very broad generalizations of complex landscapes. To improve emissions estimates, the investigators will use a new approach to develop a model based on the actual burning practices of people who set fires. Building on an existing database, they will develop a system to classify savanna vegetation types as defined by fire users and link this classification scheme to fire maps derived from satellite imagery. These data will be combined with field-based measurements of emissions of key greenhouse gases including carbon dioxide, carbon monoxide, and methane. These data will be analyzed and combined with data on changes in land use and cover to develop a model of how emissions change over time. The results of these analyses will produce one of the first accurate estimates of emissions from the heavily burned West African savanna, which will be used to quantify the sources of error in existing emissions estimates. This project will provide a new model of emissions built on the practices of African fire users as well as one of the first models of fire regime dynamics based on land-use and land-cover changes in Africa. Project results will be used to predict changes in fire emissions from the African continent, with the new models producing results that will provide valuable and accurate data for those attempting to improve global models of emissions from fire. The project will yield much-needed local-scale information regarding fire regimes by disclosing those areas associated with high uncertainties in the global-scale models of emissions and by suggesting ways to improve them. The Intergovernmental Panel on Climate Change requires that emissions estimates include an assessment of uncertainties. This project will provide such an estimate. The project will strengthen research capacities by facilitating graduate research. It will facilitate collaborative relationships between U.S. and African researchers. The investigators will help conduct "fire seminars" to disseminate results in the study region with the goal of improving local and regional fire management efforts that are currently hampered by a lack of data. The seminars will provide a forum to explore more effective ways of disseminating scientific information to local residents in regions far beyond the study area. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.