MSA: Quantifying whole-stream denitrification and nitrogen fixation with integrated modeling of N2 and O2 fluxes

MSA：通过 N2 和 O2 通量的集成建模量化全流反硝化和固氮

• 批准号: 2307284
• 负责人: Amy Marcarelli
• 金额: $ 30万
• 依托单位: Michigan Technological University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2307284&HistoricalAwards=false
• 关键词: MSA; Quantifying; whole; stream; denitrification

Human activities on the landscape have increased the input of nitrogen (N) and phosphorus (P) to freshwater environments. This nutrient pollution has led to algae blooms and low-oxygen conditions in streams, lakes and the coastal ocean. Nitrogen can by removed by denitrification, a natural process carried out by microbes that transforms dissolved nitrogen (nitrate) into N2 gas. It is important to understand where, when, and how much denitrification occurs in streams and rivers to understand how to manage and protect these ecosystems. However, measuring denitrification rates requires using separate substrates in enclosed chambers, which creates unrealistic conditions for microbes. In this project, we will develop modeling approaches to quantify denitrification in stream sections by measuring concentrations of N2 gas over day-night cycles. We will test these models in experimental and natural streams across varying concentrations and ratios of N and P. We will create sampling methods and share our model using an open-source framework so that our approach can be adopted by researchers to study other streams and rivers. For broader impact activities, we will provide training opportunities for undergraduate students and create a summer short-course on coding and data training in ecology for high school students.Models that estimate freshwater denitrification rates using day-night cycles of N2 concentrations have recently been improved by integrating inverse modeling approaches that have been widely studied for estimating rates of primary production and respiration using oxygen gas (O2) concentrations. However, many different processes contribute to changes in N2 concentrations besides denitrification that have not yet been integrated into these models. For example, N2 gas can be removed from ecosystems by physical processes like diffusion and bubble formation, as well as by biological processes like nitrogen fixation (the biologically-mediated conversation of N2 gas to ammonium). We aim to improve existing models to simultaneously resolve denitrification and nitrogen fixation through a combination of experimental and field survey measurements. First, we will apply open-water N2 flux models in experimental streams where the relative activity of denitrification and N2 fixation will be manipulated by varying water column N:P, and where we will quantify bubble formation and gas exchange to parameterize our model. Second, we will apply open-water models to nine streams that are part of the National Ecological Observatory Network (NEON), selected to have a gradient of N:P and where prior NSF-funded research has documented a gradient of denitrification and N2 fixation activity. Together, these activities will both provide much improved estimates of N2 fluxes from streams in different ecoregions in the United States, and provide improved modeling techniques that can be applied by ourselves and others to better understand nitrogen cycling and removal in streams and rivers.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.

人类活动增加了氮、磷向淡水环境的输入。这种营养污染导致藻类大量繁殖，河流、湖泊和沿海海洋出现低氧状况。氮可以通过反硝化作用去除，这是一种由微生物进行的将溶解的氮（硝酸盐）转化为N2气体的自然过程。了解溪流和河流中的反硝化作用发生在何处、何时以及多少，对于了解如何管理和保护这些生态系统至关重要。然而，测量反硝化速率需要在封闭的室中使用单独的基质，这为微生物创造了不现实的条件。在这个项目中，我们将开发建模方法，通过测量昼夜循环中N2气体的浓度来量化流段中的反硝化作用。我们将在不同浓度和N和P比例的实验和自然溪流中测试这些模型，我们将创建采样方法并使用开源框架分享我们的模型，以便研究人员可以采用我们的方法来研究其他溪流和河流。对于更广泛的影响活动，我们将为本科生提供培训机会，并为高中生开设一个关于生态学编码和数据培训的暑期短训班。最近，通过整合已被广泛研究的利用氧气（O2）浓度。然而，许多不同的过程有助于氮浓度的变化，除了反硝化尚未被整合到这些模型。例如，N2气体可以通过扩散和气泡形成等物理过程以及固氮（N2气体到铵的生物介导转化）等生物过程从生态系统中去除。我们的目标是改善现有的模型，同时解决反硝化和固氮通过实验和实地调查测量相结合。首先，我们将在实验流中应用开放水域N2通量模型，其中反硝化和N2固定的相对活性将通过改变水柱N：P来操纵，并且我们将量化气泡形成和气体交换以参数化我们的模型。其次，我们将开放水域模型应用于9个流，是国家生态观测网络（氖）的一部分，选择有梯度的N：P和以前NSF资助的研究已经记录了梯度的反硝化和N2固定活动。总之，这些活动将大大改善对美国不同生态区溪流中N2通量的估计，并提供改进的建模技术，可供我们自己和他人应用，以更好地了解溪流和河流中的氮循环和去除。该奖项反映了NSF的法定使命，并通过利用基金会的知识价值和更广泛的影响进行评估，被认为值得支持审查标准。