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

• 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

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。陆地植物在陆地和大气之间的水循环中发挥着关键作用，它们从土壤和地下水中提取水分，并在生长时将其释放到大气中。现有数据表明，蒸腾作用占全球从大陆到大气的水转移的一半以上。令人惊讶的是，人们对蒸发了多少水，不同类型的植物和生态系统如何控制蒸腾作用，以及生态系统的特性如何通过蒸腾作用形成知之甚少。该奖项支持生态学家，地球和大气科学家以及工程师的跨学科小组首次对美国各地的植物蒸腾进行估计，并使用这些数据来开发模型并改进未来植物用水的预测。该团队将开发有利于科学界的新技术和数据集，并开展跨学科的研究生培训，为多样化的下一代科学家应对生态和数据科学挑战做好准备。该项目团队将使用国家生态观测网络生产的广泛数据产品，主要侧重于水蒸气和二氧化碳的稳定同位素比率。同位素比率提供了控制植物叶片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，能够对各种大陆生态系统的蒸腾进行基于同位素的估计。该项目小组将利用该网络的传感器数据开发新的校准程序和数据产品，并分发给更广泛的研究界使用。这些数据将与该网络收集的其他数据和项目小组从实地活动中获得的信息相结合，利用从个别地块到大陆尺度的各种空间尺度的分析，以确定生态系统结构和植物气体交换调节如何控制蒸腾作用。这些知识将被整合到并用于测试植物水分利用模型，这些模型反映了研究生态系统内功能特性和结构特性的潜在分布。这些模型将用于研究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和数据集的广泛使用的研究人员，并将支持研究生短期课程在空间科学。该奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的知识价值和更广泛的影响审查标准。

项目成果

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.

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
• 作者: Hawkins, Linnia;Kumar, Jitendra;Luo, Xiangzhong;Sihi, Debjani;Zhou, Sha
• 通讯作者: Zhou, Sha

Calibration Strategies for Detecting Macroscale Patterns in NEON Atmospheric Carbon Isotope Observations

• DOI: 10.1029/2020jg005862
• 发表时间: 2021-03-01
• 期刊: JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
• 影响因子: 3.7
• 作者: Fiorella, Richard P.;Good, Stephen P.;Bowen, Gabriel J.
• 通讯作者: Bowen, Gabriel J.

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

• DOI: 10.1016/j.agrformet.2022.109267
• 发表时间: 2023
• 期刊: Agricultural and Forest Meteorology
• 影响因子: 6.2
• 作者: Jarecke, Karla M.;Hawkins, Linnia R.;Bladon, Kevin D.;Wondzell, Steven M.
• 通讯作者: Wondzell, Steven M.

Comparing Model Representations of Physiological Limits on Transpiration at a Semi‐Arid Ponderosa Pine Site

• DOI: 10.1029/2021ms002927
• 发表时间: 2022-01
• 期刊: Journal of Advances in Modeling Earth Systems
• 影响因子: 6.8
• 作者: L. Hawkins;Maoya Bassouni;W. Anderegg;M. Venturas;S. Good;H. Kwon;C. Hanson;R. Fiorella;G. Bowen;C. Still