Collaborative Research: How roots, regolith, rock and climate interact over decades to centuries - the R3-C Frontier

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。这个项目将研究气候、基岩的物理和化学特征以及植被的作用如何相互作用，控制地球表面水和碳的运动和储存。这些过程反过来又通过改变诸如水和二氧化碳等温室气体浓度等重要因素来影响气候。人类活动可以改变这些途径，这项研究将能够预测对地球表面环境可能产生的影响。为了实现这一目标，需要综合现有数据集，收集新数据，并在水科学、地球化学、土壤科学、地球物理、生态学和地球系统建模等领域培训人员。该项目将包括来自七所大学的28名本科生、4名研究生和3名博士后学者，共同探索植物根系和基岩的相互作用如何调节陆地和大气之间的水和碳运动。该项目还将培训45名教育工作者在课堂上开发基于发现的学习方法，其成果将在可用的网络平台上公开。这个项目将调查基岩在什么时候以及在多大程度上比树根对水和碳通量的控制更大。采用跨学科的方法，结合新的数据收集、数据采集、机器学习和数值模拟，本研究将确定基岩和裂缝分布控制优先流动路径发展的机制。它还将研究地下和大气之间耦合的深度、程度和时间，以及它对水储存和通量的影响。该项目将探索植物根系如何与基岩相互作用，从而形成地下结构、相关的碳储存和蒸腾速率。方法将包括三维地球物理调查和结构土壤孔隙分析，以确定地下变化的发生以及它们如何控制根系吸水。全球原位和遥感数据将通过机器学习集成，以在更大范围内识别地下结构的紧急模式。该项目将利用现有数据集，并从美国国家科学基金会关键区域集群网络（CZCNs）、国家生态观测网络（NEON）和长期生态研究（LTER）项目中收集新数据。最终的结果将是一个水文-生物地球化学联系的综合框架，以预测气候条件和地下结构如何调节水文流动和碳循环。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。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project will examine how the interaction of climate, the physical and chemical characteristics of the bedrock, and the action of vegetation, control the movement and storage of water and carbon on Earth’s surface. These processes in turn influence climate by altering important factors such as greenhouse gas concentrations like H2O and CO2. Human activities can change these pathways, and this research will enable the forecasting of the possible impacts upon the Earth-surface environment. To achieve this goal requires synthesizing existing datasets, collecting new data, and training teams of people in the fields of water science, geochemistry, soil science, geophysics, ecology, and Earth system modeling. The project will include 28 undergraduate students, four graduate students, and three postdoctoral scholars across seven universities to collectively explore how the interaction of plant roots and bedrock regulate water and carbon movement between the land and atmosphere. The project will also train 45 educators to develop discovery-based learning approaches in their classes, the products of which will be publicly accessible on available web platforms.This project will investigate when and to what degree bedrock exerts more control than roots on water and carbon fluxes. Using an interdisciplinary approach that incorporates new data collection, data harvesting, machine learning, and numerical modeling, this research will determine the mechanisms by which bedrock and fracture distributions govern the development of preferential flow paths. It will also examine depth, degree, and timing of coupling between the subsurface and atmosphere and its impact on water storage and fluxes. The project will explore how plant roots interact with bedrock to shape the subsurface structure, associated carbon storage, and transpiration rates. Methods will include 3D geophysical surveys and structural soil pore analyses to determine the occurrence of changes in the subsurface and how they govern root water uptake. Global in situ and remotely sensed data will be integrated via machine learning to discern emergent patterns in subsurface structure on larger scales. The project will leverage existing datasets and collect new data from the NSF Critical Zone Cluster Networks (CZCNs), National Ecological Observatory Network (NEON), and Long-Term Ecological Research (LTER) programs. The ultimate outcome will be a comprehensive framework of hydro-biogeochemical linkages to forecast how climatic conditions and subsurface structure regulate hydrological flow and the carbon cycle.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.