Field plot measurements from the 2017-2020 FASMEE Rx fires
收藏agdatacommons.nal.usda.gov2024-11-23 更新2025-01-22 收录
下载链接:
https://agdatacommons.nal.usda.gov/articles/dataset/Field_plot_measurements_from_the_2017-2020_FASMEE_Rx_fires/27010789/1
下载链接
链接失效反馈官方服务:
资源简介:
This is a database of fuels (i.e., vegetation) characteristics measured before (pre-fire) and after (post-fire) a series of prescribed fires, from 2017 to 2020, on the Richfield Ranger District of the Fishlake National Forest in central Utah. A total of five prescribed burns were conducted during this period. These were stand-replacing burns in forests dominated by subalpine fir. Their purpose was to remove the coniferous overstory and promote regeneration of quaking aspen. The Blackline burns were implemented to mitigate fuels adjacent to, and in the likely downwind direction from, the Manning Creek prescribed burn unit, to reduce the chance of an escape. Burn units were generally on the order of 50-500 hectares and ignited with a heli-torch. Pre- and post-fire estimates of biomass for aboveground fuels were collected for each stratum to characterize.
Data include measurements taken pre- and post-fire (October 2016 - July 2021). The total number of plots per prescribed burn were as follows: fall 2017 (n = 6), fall 2018 (n = 10), spring 2019 (n = 40), fall 2019 (n = 25), and fall 2020 (n = 60). This package includes fuel data for each fuel stratum including: downed woody debris, standing vegetation, and overstory. Surface fuel data presented in two forms: 1) raw field data and 2) estimated biomass derived from the field data. Overstory data includes: diameter, tree status, height and canopy characteristics. Fuel moisture data (only in 2018, 2019, and 2021) includes: slow drying fuels (collected 1-2 days prior to the burns within the burn unit) and quick drying fuels (collected during the burn at a proxy location outside of the burn unit).The Fire and Smoke Model Evaluation Experiment (FASMEE) is a nationwide, multi-agency effort that is advancing fire and smoke science and modeling capabilities. Information from this effort will help land managers in several ways that include: 1) increasing the use of managed fire, 2) improving firefighting strategies, 3) enhancing smoke forecasts, and 4) better assessments of carbon stores and fire-climate interactions.
FASMEE provides unparalleled opportunities to brin thanks excavation point g together new technology and the next generation of fire researchers in the largest coordinated fire research project to date. The fuels information contained in this data publication provides pre-and post-fire characterization of representative fuel beds within each burn unit and estimates of biomass consumption. These data were utilized by participating research groups to develop or evaluate models including fuel consumption, fire behavior, fuels mapping, emissions, and smoke dispersion.For more information about this study and these data, see McCarley et al. (2024).
These data were published on 08/20/2024. On 11/04/2024, we discovered that two data files had a few incorrect plot numbers and a few data entries were duplicated. These corrections have been made and the Process Steps below provides specific details.
本数据集记录了2017年至2020年间,位于犹他州中部鱼湖国家森林Richfield Ranger District内的一系列预定火烧前后(即火灾前和火灾后)植被(即燃料)特性的数据库。在此期间,共进行了五次预定火烧。这些火烧旨在清除以亚高山冷杉为主的森林的针叶树冠层,以促进颤杨的再生。Blackline火烧旨在减轻Manning Creek预定火烧单元周边及可能顺风方向燃料的负荷,以降低火灾逃逸的风险。火烧单元面积通常在50至500公顷之间,并使用直升机火焰喷射器点燃。对于每个层次,收集了火灾前后地上燃料的生物量估计值,以表征其特征。数据包括2016年10月至2021年7月火灾前后进行的测量。每次预定火烧的样地总数如下:2017年秋季(n=6)、2018年秋季(n=10)、2019年春季(n=40)、2019年秋季(n=25)和2020年秋季(n=60)。本数据包包括每个燃料层的燃料数据,包括:倒木、立木植被和树冠层。地表燃料数据以两种形式呈现:1)原始野外数据和2)从野外数据估计的生物量。树冠层数据包括:树干直径、树木状态、树高和树冠特征。燃料含水量数据(仅在2018年、2019年和2021年)包括:慢速干燥燃料(在火烧单元内火烧前1-2天收集)和快速干燥燃料(在火烧单元外一个代理地点收集)。火与烟雾模型评估实验(FASMEE)是一个全国性的、多机构参与的协作项目,旨在推进火灾和烟雾科学及建模能力。该项目的信息将有助于土地管理者以多种方式提高管理水平,包括:1)增加管理火烧的使用,2)改进灭火策略,3)提升烟雾预报,以及4)更精准地评估碳储存和火灾-气候相互作用。FASMEE为将新技术与新一代火灾研究人员汇聚到迄今为止最大规模的协调火灾研究项目中提供了无与伦比的机会。本数据出版物中包含的燃料信息提供了每个火烧单元内代表性燃料床火灾前后特征描述和生物量消耗估计。这些数据被参与的研究团队用于开发或评估包括燃料消耗、火灾行为、燃料制图、排放和烟雾扩散等模型。有关本研究和这些数据的更多信息,请参阅McCarley等(2024)。这些数据于2024年8月20日发布。2024年11月4日,我们发现两个数据文件存在一些错误的样地编号和几条数据条目重复。这些更正已经完成,以下“处理步骤”提供了具体细节。
提供机构:
agdatacommons.nal.usda.gov



