CAREER: A cross-scale, data-efficient approach to understanding plant hydraulic regulation using optimization and maximum entropy

职业：一种跨尺度、数据高效的方法，利用优化和最大熵来理解工厂水力调节

• 批准号: 2045610
• 负责人: Xue Feng
• 金额: $ 67.63万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045610&HistoricalAwards=false
• 关键词: CAREER; cross; scale; data; efficient

Plants affect water, carbon, and energy cycles by using water and carbon dioxide (CO2) to photosynthesize and grow. CO2 enters plants through small openings on leaves, called stomata, while water is taken up by roots in the ground and transported to the leaves by plants’ vascular systems. How efficiently the plant stomata and vascular systems work to supply water and CO2 to the plant – through a process called plant hydraulic regulation – depends on a range of environmental conditions (e.g., dryness in the soil and in the air) and plant characteristics. This project will use the mathematical optimization of plant performance to understand how hydraulic regulation impacts stomatal openings (at the leaf scale), carbon use and storage (at the whole-plant scale), and the spatial distribution of plant types (at the ecosystem scale) over different timescales of environmental variation. New insight into how plants cope with variation in environmental conditions can be used to more accurately incorporate plant hydraulic regulation into modeling frameworks, which would allow more accurate predictions of global water, carbon, and energy cycles. Additionally, this project aims to promote systems thinking in the general public and in middle school, undergraduate, and graduate students. The project plans to develop and implement interactive exhibits at the Bell Museum and classes at the University of Minnesota that integrate Earth system science and environmental engineering, both using the context of plant water use in variable environments.This project uses optimization and maximum entropy to improve the understanding and prediction of plant hydraulic regulation at the leaf, plant, and ecosystem scales. At the leaf level, optimal stomatal conductance will be derived such that it maximizes cumulative carbon assimilation over a season, subject to competition and carryover costs. At the whole-plant level, optimal plant carbon allocation will be derived such that it maximizes cumulative net carbon gain over multiple years, subject to legacy effects of drought. At the ecosystem level, the composition of plant hydraulic traits will be derived such that it maximizes the information entropy of the resulting trait distribution, representing the most likely trait configuration under environmental constraints. The educational products from this project will include an interactive makerspace exhibit and summer camp module for middle school students at the Bell Museum, as well as new course modules for undergraduate and graduate students to adopt interdisciplinary practices for environmental engineering and complex environmental systems.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.

植物通过利用水和二氧化碳（CO2）进行光合作用和生长来影响水、碳和能量循环。二氧化碳通过叶片上的小孔（称为气孔）进入植物，而水分则被地下的根吸收，并通过植物的脉管系统输送到叶片。植物气孔和维管系统如何有效地工作以通过称为植物水力调节的过程向植物供应水和CO2取决于一系列环境条件（例如，土壤和空气中的干燥度）和植物特性。该项目将使用植物性能的数学优化来了解水力调节如何影响气孔开口（在叶片尺度上），碳的使用和储存（在整个植物尺度上）以及植物类型的空间分布（在生态系统尺度上）在不同的环境变化时间尺度上。对植物如何科普环境条件变化的新见解可以用于更准确地将植物水力调节纳入建模框架，这将允许更准确地预测全球水，碳和能量循环。此外，该项目旨在促进公众和中学生，本科生和研究生的系统思维。该项目计划在贝尔博物馆和明尼苏达大学的课程中开发和实施互动展览，将地球系统科学和环境工程结合起来，两者都使用植物在可变环境中的水分使用背景。该项目使用优化和最大熵来提高对叶片，植物和生态系统尺度上植物水力调节的理解和预测。在叶的水平上，最佳气孔导度将被导出，使其在一个季节内最大限度地累积碳同化，受竞争和结转成本。在整个植物一级，将得出最佳植物碳分配，使其在多年内最大限度地增加累积净碳收益，但须考虑干旱的遗留影响。在生态系统水平上，植物水力性状的组成将被导出，使得其最大化所得到的性状分布的信息熵，表示在环境约束下最可能的性状配置。该项目的教育产品将包括贝尔博物馆的互动创客空间展览和中学生夏令营模块，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值进行评估来支持和更广泛的影响审查标准。

项目成果

Plant hydraulic transport controls transpiration sensitivity to soil water stress

• DOI: 10.5194/hess-25-4259-2021
• 发表时间: 2021
• 期刊: Hydrology and Earth System Sciences
• 影响因子: 6.3
• 作者: Brandon P. Sloan;S. Thompson;Xue Feng

Consistent responses of vegetation gas exchange to elevated atmospheric CO 2 emerge from heuristic and optimization models

启发式和优化模型得出植被气体交换对大气 CO 2 升高的一致响应

• DOI: 10.5194/bg-19-4387-2022
• 发表时间: 2022
• 期刊: Biogeosciences
• 影响因子: 4.9
• 作者: Manzoni, Stefano;Fatichi, Simone;Feng, Xue;Katul, Gabriel G.;Way, Danielle;Vico, Giulia
• 通讯作者: Vico, Giulia

Robust inference of ecosystem soil water stress from eddy covariance data

• DOI: 10.1016/j.agrformet.2023.109744
• 发表时间: 2023-12
• 期刊: Agricultural and Forest Meteorology
• 影响因子: 6.2
• 作者: Brandon P. Sloan;Xue Feng

Instantaneous stomatal optimization results in suboptimal carbon gain due to legacy effects

由于遗留效应，瞬时气孔优化导致碳增益不理想

• DOI: 10.1111/pce.14427
• 发表时间: 2022
• 期刊: Cell & Environment
• 作者: Feng, Xue;Lu, Yaojie;Jiang, Mingkai;Katul, Gabriel;Manzoni, Stefano;Mrad, Assaad;Vico, Giulia
• 通讯作者: Vico, Giulia

Intra‐Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data

• DOI: 10.1029/2021jg006777
• 发表时间: 2022-05
• 期刊: Journal of Geophysical Research: Biogeosciences
• 作者: Yaojie Lu;Brandon P. Sloan;S. Thompson;A. Konings;G. Bohrer;A. Matheny;Xue Feng