CAREER: Understanding heterogeneity in lake biogeochemistry across time and space

职业：了解湖泊生物地球化学在时间和空间上的异质性

• 批准号: 2048031
• 负责人: Kevin Rose
• 金额: $ 89.97万
• 依托单位: Rensselaer Polytechnic Institute
• 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: 2021-03-15 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048031&HistoricalAwards=false
• 关键词: CAREER; Understanding; heterogeneity; lake; biogeochemistry

Freshwater aquatic ecosystems, which include lakes, ponds, and reservoirs, provide important services to society, including power generation, recreational opportunities, and the provisioning of clean drinking water. Additionally, freshwater aquatic ecosystems are a major component of the global carbon cycle. Lakes emit a substantial amount of carbon dioxide to the atmosphere, which is derived from a combination of internal organic matter breakdown and external inputs of inorganic carbon from surrounding watersheds. Dissolved oxygen, which is consumed as organisms break down organic matter, is declining in lakes around the world, threatening the ability of these ecosystems to support the current diversity and biomass of organisms they harbor. Past attempts to understand coupled carbon dioxide and dissolved oxygen dynamics in lakes have not accounted for seasonal variation in light intensity and temperature or water column heterogeneity, both of which influence gross fluxes of both gasses. This project seeks to understand how heterogeneity in environmental conditions, in both time and space, impacts carbon and oxygen balance in aquatic ecosystems, and thus improve our understanding of the role lakes play in the global carbon cycle. Together, the integrated research and education plan of this project will provide educational and training opportunities to a wide range of students and early career scientists through improved course materials, a large workshop, and local outreach efforts. This project will also leverage datasets that exist at many organizations and institutions, and the insights gained via the process of compiling and harmonizing diverse data sets will be translatable to many other networks and research efforts. Finally, outreach to citizen-scientists and lake associations around the world will leverage the power of comparative network science to understand individual lake conditions in a global context.Lakes often exhibit substantial and dynamic structural heterogeneity, largely driven by thermal stratification. This project focuses on the production and consumption of carbon dioxide and dissolved oxygen in lakes, and how heterogeneity in time and space regulate the dynamics of these critical biogeochemical fluxes. Lakes are globally important hot-spots of carbon cycling, venting about as much carbon dioxide to the atmosphere as is taken up by the world’s oceans. Theoretically, carbon dioxide and dissolved oxygen are stoichiometrically coupled via metabolic processes, but departures from expectations based on stoichiometry and partial pressure in the atmosphere regularly occur in aquatic ecosystems. Understanding what causes these departures may provide insights into underlying biogeochemical processing in lakes, and may enable more accurate predictions of continental-scale carbon dioxide emissions from lakes. This project aims to combine high-frequency sensor observations, manually collected data, long-term data sets and ecosystem modeling to understand the dynamics of lake carbon dioxide and dissolved oxygen across large environmental gradients. Data will be obtained and harmonized from diverse sources such as the National Ecological Observatory Network (NEON) and collaborating scientists and organizations in the Global Lake Ecological Observatory Network (GLEON).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.

淡水水生生态系统包括湖泊、池塘和水库，为社会提供重要服务，包括发电、娱乐机会和提供清洁饮用水。此外，淡水水生生态系统是全球碳循环的主要组成部分。湖泊向大气排放大量二氧化碳，这些二氧化碳是内部有机物分解和周围流域无机碳外部输入的结合产生的。溶解氧是生物分解有机物所消耗的，在世界各地的湖泊中，溶解氧正在下降，威胁着这些生态系统支持其所拥有的生物目前的多样性和生物量的能力。过去试图了解耦合的二氧化碳和溶解氧在湖泊中的动态没有考虑季节性变化的光强度和温度或水柱的异质性，这两者都影响总通量的两种气体。该项目旨在了解环境条件在时间和空间上的异质性如何影响水生生态系统中的碳和氧平衡，从而提高我们对湖泊在全球碳循环中所起作用的理解。该项目的综合研究和教育计划将通过改进课程材料、举办大型讲习班和在当地开展外联工作，为广大学生和早期职业科学家提供教育和培训机会。该项目还将利用许多组织和机构现有的数据集，通过汇编和协调不同数据集的过程获得的见解将可转化为许多其他网络和研究工作。 最后，与世界各地的公民科学家和湖泊协会的联系将利用比较网络科学的力量，在全球范围内了解单个湖泊的状况。湖泊往往表现出大量的动态结构异质性，主要是由热分层驱动的。该项目的重点是生产和消费的二氧化碳和溶解氧在湖泊中，以及如何在时间和空间的异质性调节这些关键生态地球化学通量的动态。湖泊是全球重要的碳循环热点，向大气排放的二氧化碳与世界海洋吸收的二氧化碳一样多。理论上，二氧化碳和溶解氧通过代谢过程化学计量耦合，但偏离基于化学计量和大气分压的预期经常发生在水生生态系统中。 了解是什么原因导致这些偏离可能会提供深入了解湖泊的潜在生物地球化学过程，并可能使更准确的预测大陆尺度的湖泊二氧化碳排放量。该项目旨在将联合收割机高频传感器观测、人工收集的数据、长期数据集和生态系统建模相结合，以了解湖泊二氧化碳和溶解氧在大环境梯度下的动态。数据将从不同的来源获得和协调，如国家生态观测网络（氖）和全球湖泊生态观测网络（GLEON）的合作科学家和组织。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知识价值和更广泛的影响审查标准进行评估。

项目成果

People, infrastructure, and data: A pathway to an inclusive and diverse ecological network of networks

人员、基础设施和数据：通往包容性和多元化的网络生态网络的途径

• DOI: 10.1002/ecs2.4262
• 发表时间: 2022
• 期刊: Ecosphere
• 影响因子: 2.7
• 作者: SanClements, Michael D.;Record, Sydne;Rose, Kevin C.;Donnelly, Alison;Chong, Steven S.;Duffy, Katharyn;Hallmark, Alesia;Heffernan, James B.;Liu, Jianguo;Mitchell, Jessica J.
• 通讯作者: Mitchell, Jessica J.

Indicators of climate change impacts on the water cycle and water management

• DOI: 10.1007/s10584-021-03057-5
• 发表时间: 2021-03
• 期刊: Climatic Change
• 影响因子: 4.8
• 作者: C. Peters-Lidard;K. Rose;J. Kiang;M. Strobel;M. Anderson;A. Byrd;M. Kolian;L. Brekke;D. Arndt

Widespread deoxygenation of temperate lakes

• DOI: 10.1038/s41586-021-03550-y
• 发表时间: 2021-06-03
• 期刊: NATURE
• 影响因子: 64.8
• 作者: Jane, Stephen F.;Hansen, Gretchen J. A.;Rose, Kevin C.
• 通讯作者: Rose, Kevin C.

Predicting arctic‐alpine lake dissolved oxygen responses to future tree line advance at the Swedish forest‐tundra transition zone

预测北极-高山湖泊溶解氧对瑞典森林-苔原过渡带未来林线推进的反应

• DOI: 10.1111/gcb.15748
• 发表时间: 2021
• 期刊: Global Change Biology
• 影响因子: 11.6
• 作者: Jane, Stephen F.;Rose, Kevin C.
• 通讯作者: Rose, Kevin C.

Understanding Lake Residence Time Across Spatial and Temporal Scales: A Modeling Analysis of Lake George, New York USA

• DOI: 10.1029/2022wr034168
• 发表时间: 2024-02
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Guillaume A. R. Auger;Michael R. Kelly;Vincent W. Moriarty;K. C. Rose;Harry R. Kolar