RAPID: Critical Wildfire Monitoring Utilizing the National Ecological Observatory Network Mobile Deployment Platform with Edge-computing Cyberinfrastructure

野火的频率和强度很可能在美国西部山区的森林中增加，该地区正在经历世纪以来最严重的干旱。该RAPID项目将利用国家生态观测网络（氖）的移动的部署平台（MDP）以及高性能计算资源，以便在野火活动期间和之后立即进行响应和实时的数据驱动土壤样本收集。这种快速反应对于研究人员表征火灾干扰期间和之后土壤微生物群落结构和碳代谢能力的变化至关重要。所获得的信息将用于模拟野火和气候变化的影响，并帮助指导林地管理。该项目将在氖MDP沿着现场边缘计算资源上安装配备边缘智能传感器网络“SAGE”的热成像摄像机，以指导在火灾暴露的森林及其附近进行手动观察采样的位置。将研究不同土壤温度范围内的土壤微生物群，以检查它们在热传感指导下的异质性。 宏基因组DNA序列分析将用于研究野火后立即发生的土壤微生物组功能特征，并确定变化对碳循环和封存的影响。 结果将测试真实的时间数据采集是否可以有效地指导传感器放置和人类观察采样期间和紧随干扰，并测试氖平台和SAGE网络基础设施的耦合能力，以支持实时警报时，基于边缘和人工智能（AI）的算法检测到异常条件（例如额外的烟雾）。这将是氖MDP与SAGE网络工具的首次使用，代表了科学家和管理人员更好地了解气候变化、干旱和野火干扰的影响的迫切进步。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Wildfire frequency and intensity are highly likely to increase in forests of the U.S. Intermountain West, a region that is experiencing the worst drought in over a century. This RAPID project will utilize the Mobile Deployment Platform (MDP) of the National Ecological Observatory Network (NEON) coupled with high-performance computing resources to enable responsive and real-time, data-driven soil sample collection during and immediately following wildfire activity. This rapid response is vital to enable researchers to characterize changes in soil microbial community structure and carbon metabolizing ability during and following fire disturbance. The information obtained will be used for modelling the impact of wildfire and climate change, and to help guide forest land management. The project will mount thermal imaging cameras equipped with the edge-enabled, intelligent sensor network known as "SAGE" on the NEON MDP along with in-situ edge computing resources to guide location of manual observational sampling in and adjacent to fire-exposed forest. Soil microbiota across a range of soil temperatures will be studied to examine their heterogeneity guided by thermal sensing. Metagenomoic DNA sequence analysis will be used to study soil microbiome functional traits in the immediate aftermath of wildfire, and determine the impacts of shifts on carbon cycling and sequestration. The results will test whether real time data acquisition can effectively guide sensor placement and human observational sampling during and immediately following disturbance and test the coupled ability of the NEON platform and SAGE cyber-infrastructure to support real-time alerts when edge-based and artificial intelligence (AI)-enabled algorithms detect anomalous conditions (e.g. additional smoke plumes). This will be the first such use of the NEON MDP with SAGE cyber tools, and represents an urgent advance to enable scientists and managers to better understand the impacts of climate change, drought and wildfire disturbances.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.