MSA: Dynamics of Chlorophyll Fluorescence and Its Relationship with Photosynthesis from Leaf to Continent: Theory Meets Data

光合作用是植物利用太阳能将二氧化碳和水转化为糖和氧气的过程。光合作用可以在单个叶片中直接观察到，但不能在整个植物、地区、大陆或全球范围内观察到。这种无能阻碍了对未来粮食生产和地球气候变化的预测。太阳诱导叶绿素荧光（SIF）的测量是卫星和地面观测的最新突破。SIF可以让我们在更大的尺度上估计光合作用。该项目将研究如何将SIF测量的光合作用从叶片应用到大陆水平。这些结果将使利用叶片光合作用的知识来支持陆地生态系统未来光合作用二氧化碳吸收能力的预测成为可能。正在进行和即将进行的卫星任务已经在进行SIF测量。这些测量可以更好地估算碳源和碳汇，从而为减缓和适应气候变化提供信息，并有助于预测未来的粮食生产。本研究的总体目标是开发一个跨尺度的分析框架，建立在光合作用光反应的机制模型之上。为了实现这一目标，将执行三个任务：1)通过建立一个包含康奈尔植物园和Musgrave研究农场各种物种和环境条件下光反应的关键植物生物物理和生化参数（例如，非光化学猝灭；开放光系统II反应中心的分数）的数据库，开发和验证SIF和光合作用的叶片级理论建模框架；2)将理论光反应模型与冠层辐射传输模型相结合，了解不同生态区域国家生态观测站（NEON）站点sif -光合动态的驱动因子；3)利用美国国家大气研究中心（NCAR）社区土地模型（CLM）实施的分析框架，约束美国相邻地区的光合作用估算和变化。开发的数据库将在该项目的生命周期之后永久存储，并可由整个科学界访问和扩展。所开发的理论模型将首次分解隐藏在传统使用的光利用效率概念中的复杂性。该项目将充分利用NEON的机载观测平台数据集来阐明叶黄素循环如何影响SIF，这在之前还没有与SIF一起进行过探索。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。

Photosynthesis is the process by which plants use the sun's energy to convert carbon dioxide (CO2) and water into sugar and oxygen. Photosynthesis can be directly observed in single leaves but not for whole plants, regions, continents, or the globe. This inability hinders the prediction of future food production and how Earth's climate may change. Measurement of Solar-Induced chlorophyll Fluorescence (SIF) is a recent breakthrough in satellite and ground-based observation. SIF may allow us to estimate photosynthesis for larger scales. This project will study how photosynthesis measured by SIF can be applied from the leaf to continental levels. The results will enable using knowledge of leaf-level photosynthesis to support prediction of the future capacity of photosynthetic CO2 uptake by terrestrial ecosystems. SIF measurements are already underway from ongoing and upcoming satellite missions. These measurements may allow better estimates of carbon sources and sinks, which can inform climate change mitigation and adaptation and help predict future food production.The overall goal of this research is to develop a cross-scale analytical framework, built upon the mechanistic models of light reactions of photosynthesis. To achieve this goal, three tasks will be performed: 1) develop and validate a leaf-level theoretical modeling framework for SIF and photosynthesis by building a database with key plant biophysical and biochemical parameters (e.g., non-photochemical quenching; fraction of open photosystem II reaction centers) of light reactions across a wide range of species and environmental conditions at Cornell Botanic Garden and Musgrave Research Farm; 2) integrate theoretical light reaction models with canopy radiative transfer models to understand the driving factors for SIF-photosynthetic dynamics across the National Ecological Observatory Network (NEON) sites across wide ecoregions; 3) constrain photosynthesis estimates and variability across conterminous US using the analytical framework implemented into the National Center for Atmospheric Research (NCAR) Community Land Model (CLM). The database developed will be permanently stored beyond the lifespan of this project and accessible and expandable by the science community at large. The theoretical models developed will, for the first time, decompose the complexities hidden in the traditionally used Light Use Efficiency concept. This project will fully utilize NEON's Airborne Observation Platform datasets to clarify how the xanthophyll cycle affects SIF, which has not yet been explored in conjunction with SIF before.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.