Collaborative Research: Direct determination and model analysis of elemental stoichiometry of phytoplankton in the Oregon Coast

合作研究：俄勒冈海岸浮游植物元素化学计量的直接测定和模型分析

• 批准号: 2048373
• 负责人: Curtis Deutsch
• 金额: $ 47.18万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048373&HistoricalAwards=false
• 关键词: Collaborative; Research; Direct; determination; model

The ratio of carbon:nitrogen:phosphorus (C:N:P) in marine organic matter is used to study biochemical cycling of nutrients in the ocean. The cycling of nutrients is a process thought to be controlled by phytoplankton. Despite variability in individual measurements of the C:N:P in various parts of the ocean, the global plankton C:N:P averages out to a relatively constant value through ecosystem processes. What the important processes are and how the average ratio of these elements is maintained in the ocean has only been examined in modeling exercises. However, the assumption of a constant ratio of C:N:P in phytoplankton is most likely violated in real life, leading to uncertainties in model outputs. Laboratory experiments have shown that there is a large range of possible C:N:P ratios in phytoplankton, but no direct measurements of naturally growing phytoplankton in the ocean have been made to support the laboratory findings. In addition, no current models of phytoplankton cell biology have been tested with field data to determine if is possible to predict changes in the C:N:P ratio given environmental conditions. Through a direct measure of phytoplankton this study will examine the spatial variability in C:N:P across the Oregon coastal upwelling system to the nutrient-poor waters offshore. Using laboratory techniques, researchers will selectively remove phytoplankton from the suspended particles and apply newly-developed, high-sensitivity analyses to determine phytoplankton specific C:N:P. Through a direct measure of phytoplankton we will examine how environmental conditions affect C:N:P in the sampling region. This C:N:P data will be incorporated into a model that predicts C:N:P in phytoplankton under a range of environmental conditions. Success in this endeavor will provide a predictive model for the phytoplankton C:N:P and eliminate the need to make assumptions about a fixed C:N:P in phytoplankton. Results from the proposed research will be used in undergraduate and graduate teaching. Also, relevant science will be disseminated to underrepresented and underserved audiences, through collaboration with The Science & Math Investigative Learning Experiences Program (The SMILE Program) of Oregon State University (OSU). This proposal will support the development of two teacher training workshops that give teachers hands-on experiments that can be used in their classrooms. The proposed research will provide training for a graduate student and several undergraduate students. We have been successful in recruiting under-represented students and will continue the practice. Given the reliance on biogeochemical models to both predict and hindcast ocean productivity and in turn, model reliance on C:N:P assumptions, it is critically important to determine the drivers of phytoplankton C:N:P variability and the extent to which the stoichiometry is flexible in natural oceanic systems. By combining field efforts and numerical modeling we propose to 1) measure and describe the variability in phytoplankton specific C:N:P across a large gradient in nutrient availability (Oregon Coast to offshore), 2) combine observations with a mechanistic phytoplankton model to attribute the role of environmental factors and community composition in generating the observed plankton stoichiometric variability, 3) evaluate the contribution of phytoplankton C:N:P to that of marine particles, and 4) include a mechanistic representation of phytoplankton stoichiometry in a high-resolution regional ocean model (ROMS) to interpret observations and explore their regional implications. Success in this endeavor will provide the oceanographic community with phytoplankton specific C:N:P data that will allow us to test and improve phytoplankton physiology based ecosystem models, improving the predictive capability of biogeochemical cycles, and ecosystem responses to future climate change.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.

碳的比率：氮：海洋有机物中的磷（C：N：P）用于研究海洋营养素的生化循环。养分的循环是一个被浮游植物控制的过程。尽管在海洋各个部分的C：N：P的单个测量值上有差异，但通过生态系统过程，全球浮游生物C：N：P平均具有相对恒定的价值。重要的过程是什么以及如何在海洋中维持这些元素的平均比率，仅在建模练习中进行了研究。然而，浮游植物中C n：p的恒定比率的假设很可能在现实生活中违反，从而导致模型输出的不确定性。实验室实验表明，浮游植物中可能存在大量可能的C：N：P比，但是没有直接测量海洋中天然生长的浮游植物来支持实验室发现。此外，没有对浮游植物细胞生物学的当前模型进行测试，以确定是否有可能预测C：N：P比给定环境条件的变化。 通过直接衡量浮游植物的量度，这项研究将检查俄勒冈州沿海上升流入系统的C：N：P的空间变异性到靠近养分贫困的水域。使用实验室技术，研究人员将选择性地从悬浮的颗粒中删除浮游植物，并应用新开发的高灵敏分析以确定浮游植物特异性C：N：n：p。通过直接测量浮游植物，我们将研究采样区域中环境条件如何影响C：N：P。该C：N：P数据将纳入一个模型，该模型在一系列环境条件下预测浮游植物中的C：N：P。在这项工作中的成功将为浮游植物C：n：p提供一个预测模型，并消除了植物浮游生物中关于固定的C：N：P的需要。拟议研究的结果将用于本科和研究生教学。此外，相关科学将通过与俄勒冈州立大学（OSU）的科学与数学研究经验计划（The Smile the Smile计划）合作，将相关的科学传播到代表性不足和服务不足的受众。该建议将支持开发两个教师培训研讨会，这些讲习班为教师提供了可以在课堂上使用的实验。拟议的研究将为研究生和几名本科生提供培训。我们已经成功地招募了代表性不足的学生，并将继续练习。 鉴于对生物地球化学模型既预测和后播海洋生产率又依赖于C：n：p假设的模型依赖性，因此确定浮游植物的驱动因素C：n：p变异性以及在天然海洋系统中静态计数器的灵活程度非常重要。通过结合现场努力和数值模型，我们建议1）测量并描述浮游植物特异性C：N：P的可变性，跨营养可用性（俄勒冈州沿海到近海），2）将观察结果与机械植物学模型的作用，将观察结果结合起来，以将环境因素和社区组成的作用归因于构成的作用。浮游植物C：n：p to to of海洋颗粒的P）在高分辨率的区域海洋模型（ROMS）中包括浮游植物化学计量的机械表示，以解释观察结果并探索其区域意义。在这项工作中的成功将为海洋学社区提供特定于浮游植物的c：n：p数据，使我们能够测试和改善基于生理的生态系统模型，提高生物地球化学周期的预测能力，并改善生物地球化学周期的预测能力，并通过对未来的气候变化进行了依据。和更广泛的影响审查标准。

项目成果

Better together? Lessons on sociality from Trichodesmium

• DOI: 10.1016/j.tim.2023.05.001
• 发表时间: 2023-09-11
• 期刊: TRENDS IN MICROBIOLOGY
• 影响因子: 15.9
• 作者: Eichner，Meri;Inomura，Keisuke;Shaked，Yeala
• 通讯作者: Shaked，Yeala

Biochemical Barriers on the Path to Ocean Anoxia?

• DOI: 10.1128/mbio.01332-21
• 发表时间: 2021-08-31
• 期刊: mBio
• 影响因子: 6.4
• 作者: Giovannoni S;Chan F;Davis E 2nd;Deutsch C;Wolf S
• 通讯作者: Wolf S

Coastal processes modify projections of some climate-driven stressors in the California Current System

沿海过程改变了加州洋流系统中一些气候驱动压力源的预测

• DOI: 10.5194/bg-18-2871-2021
• 发表时间: 2021
• 期刊: Biogeosciences
• 影响因子: 4.9
• 作者: Siedlecki, Samantha A.;Pilcher, Darren;Howard, Evan M.;Deutsch, Curtis;MacCready, Parker;Norton, Emily L.;Frenzel, Hartmut;Newton, Jan;Feely, Richard A.;Alin, Simone R.
• 通讯作者: Alin, Simone R.