Collaborative Research: MSB-ENSA: Leveraging NEON to Build a Predictive Cross-scale Theory of Ecosystem Transpiration

合作研究：MSB-ENSA：利用 NEON 构建生态系统蒸腾的预测性跨尺度理论

基本信息

批准号：
1802885
负责人：
Stephen Good
金额：
$ 93.34万
依托单位：
Oregon State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2023-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1802885&HistoricalAwards=false
关键词：
Collaborative Research MSB ENSA Leveraging

项目摘要

Water is a critical resource that sustains continental ecosystems. Land plants play a critical role in the cycling of water between the continents and atmosphere by extracting water from soils and groundwater and releasing it to the atmosphere as they grow. Existing data suggest that this process, transpiration, accounts for more than half of the global transfer of water from the continents to the atmosphere. Surprisingly little is known about how much water is transpired, how different types of plants and ecosystems govern transpiration, and how properties of ecosystems are shaped by transpiration. This award supports an interdisciplinary group of ecologists, Earth and atmospheric scientists, and engineers to make estimates of plant transpiration across the United States for the first time and use these data to develop models and improve predictions of future plant water use. The team will develop new techniques and datasets benefitting the scientific community and conduct interdisciplinary graduate student training to prepare diverse, next-generation scientists to tackle ecological and data science challenges.The project team will work with a wide range of data products produced by the National Ecological Observatory Network, with a primary emphasis on stable isotope ratios of water vapor and carbon dioxide. Isotope ratios provide an integrated measure of physical processes controlling gas exchange between plant leaves and the atmosphere. The suite of sensors deployed by the Network across the USA provides the first standardized dataset enabling isotope-based estimation of transpiration across a diverse range of continental ecosystems. The project team will develop new calibration procedures and data products from the Network's sensor data and distribute these for use by the broader research community. These data will be integrated with other data collected by the Network and information from field campaigns by the project team, using analysis at a range of spatial scales from individual plots to continental scales to determine how ecosystem structure and plant regulation of gas exchange control transpiration. This knowledge will be integrated into and used to test models for plant water use that reflect the underlying distribution of functional traits and structural properties within the study ecosystem. The models will be used to examine the potential sensitivities of transpiration and ecosystem water use. During the course of its work, the project will develop and disseminate new measurement and data analysis approaches and datasets of broad use to researchers, and will support a graduate short course in spatial sciences.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.

水是维持大陆生态系统的重要资源。陆地植物在大陆和大气之间的水循环中发挥着至关重要的作用，它们从土壤和地下水中提取水分，并在生长过程中将其释放到大气中。现有数据表明，这一过程（蒸腾作用）占全球从大陆到大气的水转移量的一半以上。令人惊讶的是，人们对蒸腾了多少水、不同类型的植物和生态系统如何控制蒸腾作用以及蒸腾作用如何影响生态系统的特性知之甚少。该奖项支持由生态学家、地球和大气科学家以及工程师组成的跨学科小组首次对美国各地的植物蒸腾进行估计，并利用这些数据开发模型并改进对未来植物用水的预测。该团队将开发造福科学界的新技术和数据集，并进行跨学科研究生培训，以培养多样化的下一代科学家来应对生态和数据科学挑战。该项目团队将使用国家自然科学基金委员会生产的各种数据产品。生态观测站网络，主要侧重于水蒸气和二氧化碳的稳定同位素比率。同位素比提供了控制植物叶子和大气之间气体交换的物理过程的综合测量。该网络在美国各地部署的传感器套件提供了第一个标准化数据集，能够基于同位素估计不同大陆生态系统的蒸腾作用。该项目团队将根据网络的传感器数据开发新的校准程序和数据产品，并将其分发给更广泛的研究界使用。这些数据将与网络收集的其他数据以及项目团队实地活动的信息相结合，利用从单个地块到大陆尺度的一系列空间尺度的分析，以确定生态系统结构和植物对气体交换的调节如何控制蒸腾。这些知识将被整合到并用于测试植物用水模型，该模型反映了研究生态系统内功能性状和结构特性的基本分布。这些模型将用于检查蒸腾作用和生态系统用水的潜在敏感性。在其工作过程中，该项目将开发和传播新的测量和数据分析方法以及对研究人员广泛使用的数据集，并将支持空间科学研究生短期课程。该奖项反映了 NSF 的法定使命，并被认为是值得的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来提供支持。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

The National Ecological Observation Network Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) Dataset

DOI：
10.4211/hs.e74edc35d45441579d51286ea01b519f
发表时间：
2022-01-01
期刊：
HydroShare
影响因子：
0
作者：
Finkenbiner, C.
通讯作者：
Finkenbiner, C.

Measuring, Monitoring, and Modeling Ecosystem Cycling

生态系统循环的测量、监控和建模

DOI：
10.1029/2020eo147717
发表时间：
2020
期刊：
Eos
影响因子：
0
作者：
Hawkins, Linnia;Kumar, Jitendra;Luo, Xiangzhong;Sihi, Debjani;Zhou, Sha
通讯作者：
Zhou, Sha

Direct partitioning of eddy-covariance water and carbon dioxide fluxes into ground and plant components

将涡相关水和二氧化碳通量直接分配到地面和植物成分中

DOI：
10.1016/j.agrformet.2021.108790
发表时间：
2022
期刊：
Agricultural and Forest Meteorology
影响因子：
6.2
作者：
Zahn, Einara;Bou-Zeid, Elie;Good, Stephen P.;Katul, Gabriel G.;Thomas, Christoph K.;Ghannam, Khaled;Smith, James A.;Chamecki, Marcelo;Dias, Nelson L.;Fuentes, Jose D.
通讯作者：
Fuentes, Jose D.

Carbon uptake by Douglas-fir is more sensitive to increased temperature and vapor pressure deficit than reduced rainfall in the western Cascade Mountains, Oregon, USA

美国俄勒冈州喀斯喀特山脉西部地区，花旗松吸收的碳对温度升高和蒸气压不足的影响比降雨量减少更敏感