EAR-PF: Mapping Belowground Processes Using Remotely Measured Foliar Chemistry

凯瑟琳博士D.查德威克已被授予NSF博士后奖学金，在斯坦福大学和劳伦斯伯克利国家实验室开展研究和教育计划。Chadwick博士将在最近发展的基于空气的叶片化学测量（叶片化学）的基础上，开发远程绘制土壤有机碳和养分分布图的方法。这一方法将对那些需要为科学或管理问题确定地下碳和养分储存清单的人感兴趣。该项目产生的数据集可用于测试土壤碳储量和周转模型，并有助于开发大尺度陆地表面模型的方法。教育活动将侧重于指导两名本科生从事与调查有关的研究项目。目前还没有地球物理、地球化学或遥感方法可以在大的空间尺度上绘制地下土壤碳或营养成分的地图，这要求大多数研究依赖于点采样和密集的表征方法，并结合不确定的空间外推。利用地面测量远程评估土壤碳和关键养分储量的能力将允许对土壤碳储量及其与景观位置、岩性、土壤湿度、外观和其他远程可测量参数的关系进行空间明确的估计。此外，在植被的遥感特征和地下特性之间建立联系，将打开一个窗口，了解临界区过程的空间分布以及它们如何在目前无法研究的空间尺度上相互作用。

Dr. Katherine D. Chadwick has been granted an NSF EAR Postdoctoral Fellowship to carry out research and education plans at Stanford University and Lawrence Berkeley National Laboratory. Building on recent developments of airborne-based measurements of the chemistry of leaves (foliar chemistry), Dr. Chadwick will develop the methodology to remotely map soil organic carbon and nutrient profiles. This methodology will be of interest to those that need to determine inventories of subsurface carbon and nutrient stocks for scientific or management questions. The datasets derived from this project could be used to test models of soil carbon stocks and turnover and help to develop methodology for large-scale land surface models. The education activities will focus on mentoring two undergraduate students in research projects related to the investigation. No geophysical, geochemical, or remote sensing approaches currently exist that can map below ground soil carbon or nutrient composition over large spatial scales, requiring most studies to rely on point sampling and intensive characterization methods combined with uncertain spatial extrapolations. The ability to remotely assess soil carbon and key nutrient stocks using above ground measures will allow for spatially explicit estimates of soil carbon inventories and their relationship to landscape position, lithology, soil moisture, aspect, and other remotely measurable parameters. In addition, building a link between remotely detectable characteristics of vegetation and subsurface properties will open a window into the spatial distribution of critical zone processes and how they interact over spatial scales currently not feasible to study.