MRA: Resolving the multi-scale drivers of tree mortality from field and remote sensing data on co-located ForestGEO-NEON sites

全球树木死亡率呈上升趋势。然而，人们对死亡的模式和原因了解甚少。由于森林是陆地生物多样性的关键地点，并对陆地碳储存作出重大贡献，因此更好地了解树木死亡率非常重要。森林可以通过树木死亡迅速失去生物量和碳，但通常只能通过生长缓慢地获得碳。因此，了解树木死亡的原因将有助于更好地了解碳循环。像火灾或虫害爆发这样的大干扰可以一次杀死许多树木，但大多数树木不会死于大干扰。相比之下，大多数树木都是独自死去的，多年来缓慢死亡，原因并不总是显而易见的。这项工作的目标是确定树木每年死亡的速度，最重要的是，原因是什么。将利用这些数据工具来更好地探测树木死亡率和森林动态的未来趋势。这些信息将传达给森林管理者、决策者和其他利益相关者。该项目的数据和产品将广泛传播并整合到4-12年级的教育模块中。该项目还将让本科生研究人员参与研究的各个方面，包括将他们介绍给国家和国际研究网络的参与者。来自两个国家研究网络的数据将结合起来回答有关树木如何、在哪里以及为什么死亡的问题。研究人员将对史密森学会的ForestGEO网络（https://forestgeo.si.edu/）的5个大面积森林研究地块上的数万棵树木进行年度死亡率调查。所有这些ForestGEO站点都位于国家生态观测网（NEON）站点（https://www.neonscience.org/）上，这些站点定期收集包括航空遥感在内的一系列生态数据。来自ForestGEO地块的详细地面真实数据将与在每个站点收集的高分辨率高光谱和基于激光雷达无人机的遥感数据相结合。这些数据将用于模拟与树木死亡有关的原因和因素。利用NEON遥感数据，将树木死亡率模型升级到NEON域。激光雷达和图像将用于识别森林中表明树木死亡的结构变化。然后，模型将使用美国宇航局收集的卫星数据进一步扩大规模，以估算更大范围内的死亡率。这些数据收集工作的结果将促进对树木死亡率、森林变化速度和陆地碳储量动态的理解。该项目将通过确定树木死亡模式如何从单个树木扩展到整个景观，帮助推进宏观系统生物学。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

Tree mortality is on the rise globally. However, patterns and causes of mortality are poorly understood. Because forests are key locations for terrestrial biodiversity and contribute significantly to terrestrial carbon storage, a better understanding of tree mortality is important. A forest can lose biomass, and thus carbon, quickly through tree death, but typically gain carbon only slowly through growth. Thus, understanding the causes of tree mortality will contribute to a better understanding of carbon cycling. Big disturbances like fires or insect outbreaks can kill many trees at once, but most trees do not die from big disturbances. In contrast, most trees die alone, slowly over years for reasons that are not always obvious. The goal of this work is to determine the rate at which trees are dying annually, and most importantly for what reasons. Using these data tools to better detect future trends in tree mortality and forest dynamics will be built. This information will be conveyed to forest managers, policy makers, and other stakeholders. The data and products from this project will be broadly disseminated and integrated within grade 4-12 education modules. The project will also engage undergraduate researchers in all aspects of the research including introducing them to participants of national and international research networks. Data from two national research networks will be combined to answer questions regarding how, where, and why trees are dying. The researchers will perform annual mortality surveys on tens of thousands of trees at five large-area forest research plots that are part of the Smithsonian Institution’s ForestGEO network (https://forestgeo.si.edu/). All these ForestGEO plots are located on National Ecological Observation Network (NEON) sites (https://www.neonscience.org/) where a suite of ecological data, including air-borne remote sensing, is collected on a regular schedule. Detailed ground-truth data from the ForestGEO plots will be combined with high-resolution hyperspectral and lidar drone-based remote sensing data collected at each site. These data will be used to model causes and factors associated with tree mortality. Using NEON remote sensing data, the model of tree mortality will be upscaled to the NEON domain. Lidar and imagery will be used to identify structural changes in forests that indicate tree death. Models will then be up-scaled further using satellite data collected by NASA to make mortality estimates across the larger landscape. The results of these data collection efforts will advance understanding of tree mortality, the pace of forest change, and the dynamics of terrestrial carbon storage. The project will help advance macrosystems biology by pinpointing how the patterns of tree mortality scale from an individual tree to the entire landscape.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.