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

这个项目的重点是改进对地球上最频繁和最广泛被烧毁的地区，即非洲大草原的排放量的估计。热带稀树草原的大火释放出大量的温室气体和气溶胶颗粒。虽然人们越来越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，而西非是非洲大陆火灾最活跃的地区。这个跨学科研究项目将发展一个排放动态模型，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。现有的热带稀树大草原排放估计具有高度的不确定性，因为它们是基于对复杂景观的非常广泛的概括。为了改进排放估算，调查人员将采用一种新方法，根据放火人的实际燃烧行为开发一个模型。在现有数据库的基础上，他们将开发一个系统，根据火灾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卫星图像生成的火灾地图联系起来。这些数据将与主要温室气体（包括二氧化碳、一氧化碳和甲烷）的实地排放测量相结合。将对这些数据进行分析，并将其与土地利用和覆盖变化的数据结合起来，以建立一个关于排放如何随时间变化的模型。这些分析的结果将产生对西非严重燃烧的热带稀树大草原的排放量的首批准确估计之一，这些估计将用于量化现有排放估计的误差来源。这个项目将提供一个基于非洲火灾使用者实践的新的排放模型，以及基于非洲土地利用和土地覆盖变化的第一个火灾动态模型之一。项目结果将用于预测非洲大陆的火灾排放变化，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。该项目将通过披露全球尺度排放模型中与高度不确定性相关的区域并提出改进方法，从而获得关于火灾制度的急需的地方尺度信息。政府间气候变化专门委员会要求排放估算包括对不确定性的评估。这个项目将提供这样一个估计。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。调查人员将协助举办“火灾研讨会”，在研究区域传播结果，目的是改善目前因缺乏数据而受到阻碍的地方和区域火灾管理工作。这些研讨会将提供一个论坛，探讨向远远超出研究范围的地区的当地居民传播科学信息的更有效方法。本项目由美国国家科学基金会自然与人类系统耦合动力学（CNH）项目资助。

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.