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

树木死亡率在全球范围内呈上升趋势。然而，人们对死亡模式和原因知之甚少。由于森林是陆地生物多样性的关键位置，并对陆地碳储存做出重大贡献，因此更好地了解树木死亡是重要的。通过树木死亡，森林可以迅速失去生物量，从而失去碳，但通常情况下，通过生长获得碳的速度很慢。因此，了解树木死亡的原因将有助于更好地理解碳循环。像火灾或虫害爆发这样的大干扰可以同时杀死许多树，但大多数树不会因为大干扰而死亡。相比之下，大多数树木会独自死亡，随着时间的推移会慢慢死亡，原因并不总是很明显。这项工作的目标是确定树木每年的死亡速度，以及最重要的是什么原因。将利用这些数据工具更好地检测树木死亡和森林动态的未来趋势。这一信息将传达给森林管理者、政策制定者和其他利益攸关方。该项目的数据和产品将广泛传播，并纳入4-12年级的教育单元。该项目还将使本科生研究人员参与研究的所有方面，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被结合起来，以回答有关树木如何、在哪里以及为什么死亡的问题。研究人员将在史密森学会森林地理网络(https://forestgeo.si.edu/).)的五个大面积森林研究地块上对数万棵树进行年度死亡调查所有这些ForestGeo地块都位于国家生态观测网络(NEON)站点(https://www.neonscience.org/))上，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地点收集的高分辨率高光谱和激光雷达无人机遥感数据结合起来。这些数据将被用来模拟与树木死亡相关的原因和因素。利用霓虹灯遥感数据，树木死亡模型将升级到霓虹灯领域。激光雷达和图像将被用来识别森林中表明树木死亡的结构变化。然后，将使用NASA收集的卫星数据进一步放大模型，以对更大范围内的死亡率进行估计。这些数据收集工作的结果将促进对树木死亡、森林变化速度和陆地碳储存动态的了解。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来帮助推进大系统生物学。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.