RII Track-2 FEC: Aquatic Intermittency Effects on Microbiomes in Streams (AIMS)

RII Track-2 FEC：水生间歇性对溪流中微生物组的影响 (AIMS)

• 批准号: 2019603
• 负责人: Amy Burgin
• 金额: $ 599.89万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019603&HistoricalAwards=false
• 关键词: RII; Track; FEC; Aquatic; Intermittency

Understanding of links among microbial communities (microbiomes), stream health, and water quality relies on studies of perennially flowing streams. However, more than half of global stream-miles do not flow continuously. These intermittent streams occur across the entire country--from western deserts to eastern forests. Despite their ubiquity, research on intermittently flowing streams is impeded by a lack of: 1) physical infrastructure designed to measure intermittency, and 2) scientific training that straddles aquatic and terrestrial ecology. The Aquatic Intermittency effects on Microbiomes in Streams (AIMS) project will address the first obstacle by creating a network of instrumented sites designed to generate “Big Data” to quantify flow intermittency, stream microbiomes, and water quality. AIMS will confront the second obstacle by using its network to provide training in collaborative science and interdisciplinary methods to study intermittent streams, and by providing workforce training in environmental "Big Data" tools through a new On Ramps to Data Science program, which will focus on data generated by microbiome sequencing, environmental sensors, and Geographic Information Systems (GIS). This infrastructure and training will support a team of 18 investigators, including nine early career scientists spanning five EPSCoR jurisdictions (AL, ID, KS, MS, OK). To build capacity in team science, 11 graduate students and two postdoctoral associates will be recruited using a cohort model that will provide cross-jurisdictional training in scientific communication, inclusive mentoring, data management and collaboration. Students will be trained through AIMS Undergraduate Program (AIMS UP), which will recruit participants from regional partners, such as Haskell Indian Nations University, Alabama A&M, and the Shoshone-Bannock Summer Youth Program. Our overarching objective is to create research infrastructure and training capable of integrating big data sources needed to address water quality at the critical nexus between intermittent and perennial streams.Our scientific understanding of streams derives from perennially flowing systems; yet, over half of the world’s streams and rivers only flow intermittently -- a fraction that is projected to increase with climate change. These less-studied intermittent channels form the nexus between terrestrial and aquatic ecosystems and are a potentially important control point for influencing downstream water quality. Furthermore, how hydrology, biogeochemical processes and microbial communities (microbiomes hereafter) interact to affect water quality is likely distinct in intermittent streams compared to perennial streams. The Aquatic Intermittency effects on Microbiomes in Streams (AIMS) project will fill this knowledge gap in order to predict how intermittent streams influence downstream water quality, which requires quantifying how microbiomes and hydrology interact to control biogeochemical cycling and water quality. AIMS will integrate datasets on hydrology, microbiomes, and biogeochemistry in three regions to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., microbes, biogeochemistry) to control water quality in intermittent streams. Our solution to build scientific capacity and workforce development is to: 1) create a network of instrumented sites to quantify and predict how intermittency controls downstream water quality, 2) educate and train scientists from diverse backgrounds in collaborative science and interdisciplinary methods to study intermittent streams, and 3) provide workforce training in environmental “big data” tools including microbiome sequencing, environmental sensors for hydrology and water quality, and Geographic Information Systems (GIS) through a new program On Ramps to Data Science. The project will support 18 faculty members (50% early-career researchers; ECR) in five EPSCoR jurisdictions (AL, ID, KS, MS, OK), and will hire and train one project manager, two postdoctoral researchers, and 11 graduate students in a collaborative environment. ECRs will benefit from support, mentoring and networking programs, while mid- and late-career faculty will gain new skills focused on Data Science, new skills and new collaborators. The AIMS Undergraduate Program (AIMS UP) will recruit two students per summer from regional partners, such as Haskell Indian Nations University, Alabama A&M, and the Shoshone-Bannock Summer Youth Program. The overarching objective is to create research infrastructure and training capable of integrating data streams needed to address water quality and its links to microbiomes at the critical nexus between intermittent and perennial stream ecosystems.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.

了解微生物群落之间的联系（微生物组），流健康和水质依赖于多年流动流的研究。但是，超过一半的全球河流不会连续流动。这些间歇性的溪流发生在整个国家 - 从西部沙漠到东部森林。尽管存在着无处不在的研究，但缺乏间歇性流动流的研究受到：1）旨在衡量间歇性的物理基础设施，以及2）跨越水生和陆地生态学的科学训练。对流中微生物的水生间歇性影响（AIMS项目）将通过创建旨在生成“大数据”的仪器网站网络来解决第一个障碍，以量化流量间歇性，流微生物组和水质。 AIMS将通过使用其网络提供协作科学和跨学科方法的培训来面对第二个障碍，以研究间歇流，并通过在环境中提供劳动力培训“大数据”工具的劳动力培训，该工具通过对数据科学的坡道上的新工具进行“大数据”工具，该计划将重点关注由微生物组测序，环境传感器，环境传感器和地理信息系统（GIS）生成的数据。这种基础设施和培训将支持一支由18名调查人员组成的团队，其中包括跨越五个EPSCOR司法管辖区（AL，ID，KS，MS，MS，OK）的9名早期职业科学家。为了在团队科学领域建立能力，将使用一个同类模型招募11名研究生和两名博士后同事，该模型将在科学沟通，包容性心理，数据管理和协作方面提供跨犹太人的培训。将通过AIMS本科课程（AIMS UP）对学生进行培训，该课程将招募来自地区合作伙伴的参与者，例如Haskell Indian Nations University，Alabama A＆M和Shoshone Bannock Summer Youth计划。我们的总体目标是创建研究基础设施和培训，能够整合间歇性和多年生流之间关键的Nextus所需的大数据来源。我们对流的科学理解来自多年来流动的系统。然而，世界上一半以上的河流和河流只会间歇性流动 - 预计将随着气候变化的增加而增加。这些研究较少的间歇通道构成了陆地和水生生态系统之间的下一个，并且是影响下游水质的潜在重要控制点。此外，与多年生流相比，水文学，生物地球化学过程和微生物群落（以下简称微生物组）在间歇流中可能有所不同。对流中微生物组的水生间歇性影响（AIMS）项目将填补这一知识差距，以预测间歇流如何影响下游水质，这需要量化微生物组和水文学如何相互作用，以控制生物地球化学循环和水质。 AIMS将在三个区域中整合有关水文，微生物组和生物地球化学的数据集，以测试总体假设，即物理驱动因素（例如攀岩，水文学）与生物学驱动因素（例如，微生物，生物地球化学）相互作用，以控制间歇流中的水质。我们建立科学能力和劳动力发展的解决方案是：1）创建一个仪器网站网络，以量化和预测间歇性控制下游水质的控制方式，2）教育和培训来自不同科学和跨学科的科学家的科学家，以研究间歇性流以及3）在包括环境中的“大量数据”工具中的工作人员培训，并提供跨学科的方法。 （GIS）通过有关数据科学坡道的新程序。该项目将在5个EPSCOR司法管辖区（AL，ID，KS，MS，OK）中支持18位教职员工（50％的早期研究人员； ECR），并将聘请和培训一名项目经理，两名博士后研究人员和11名合作环境中的研究生。 ECRS将从支持，心理和网络计划中受益，而中后期职业教师将获得针对数据科学，新技能和新合作者的新技能。目标本科课程（AIMS UP）每个夏天将从区域合作伙伴中招募两名学生，例如Haskell Indian Nation University，Alabama A＆M和Shoshone-Bannock Summer Youth计划。总体目的是创建能够整合解决水质及其与微生物组的数据流的研究基础架构和培训，这是在间歇性和多年生流生态系统之间的关键隔壁上的联系。这奖反映了NSF的法定任务，并通过使用基金会的知识优点和广泛的范围来评估，以评估的支持是宝贵的。

项目成果

Drivers of spatiotemporal patterns of surface water inputs in a catchment at the rain-snow transition zone of the water-limited western United States

美国西部水资源有限的雨雪过渡区流域地表水输入时空模式的驱动因素

• DOI: 10.1016/j.jhydrol.2022.128699
• 发表时间: 2023
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: Hale, K.;Kiewiet, L.;Trujillo, E.;Krohe, C.;Hedrick, A.;Marks, D.;Kormos, P.;Havens, S.;McNamara, J.;Link, T.
• 通讯作者: Link, T.

The Drying Regimes of Non‐Perennial Rivers and Streams

非常年河流和溪流的干涸状况

• DOI: 10.1029/2021gl093298
• 发表时间: 2021
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Price, Adam N.;Jones, C. Nathan;Hammond, John C.;Zimmer, Margaret A.;Zipper, Samuel C.
• 通讯作者: Zipper, Samuel C.

Assessing placement bias of the global river gauge network

• DOI: 10.1038/s41893-022-00873-0
• 发表时间: 2022-04-25
• 期刊: NATURE SUSTAINABILITY
• 影响因子: 27.6
• 作者: Krabbenhoft, Corey A.;Allen, George H.;Olden, Julian D.
• 通讯作者: Olden, Julian D.

Causes, Responses, and Implications of Anthropogenic versus Natural Flow Intermittence in River Networks

河网中人为与自然流量间歇的原因、响应和影响

• DOI: 10.1093/biosci/biac098
• 发表时间: 2022
• 期刊: BioScience
• 影响因子: 10.1
• 作者: Datry, Thibault;Truchy, Amélie;Olden, Julian D;Busch, Michelle H;Stubbington, Rachel;Dodds, Walter K;Zipper, Sam;Yu, Songyan;Messager, Mathis L;Tonkin, Jonathan D
• 通讯作者: Tonkin, Jonathan D

Pervasive changes in stream intermittency across the United States

• DOI: 10.1088/1748-9326/ac14ec
• 发表时间: 2021-08-01
• 期刊: ENVIRONMENTAL RESEARCH LETTERS
• 影响因子: 6.7
• 作者: Zipper, Samuel C.;Hammond, John C.;Allen, Daniel C.
• 通讯作者: Allen, Daniel C.