Collaborative Research: Network Cluster: Using Big Data approaches to assess ecohydrological resilience across scales

合作研究：网络集群：使用大数据方法评估跨尺度的生态水文恢复力

• 批准号: 2011439
• 负责人: Benjamin Abbott
• 金额: $ 33.3万
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 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=2011439&HistoricalAwards=false
• 关键词: Collaborative; Research; Network; Cluster; Using

The part of the Earth surface that sustains life (the Critical Zone) consists of bedrock, soil, water, air, and living things that have been interacting for billions of years. The Critical Zone can absorb many disturbances while still supporting life on Earth, but the age of humans or the “Anthropocene” has put unprecedented pressure on the Critical Zone. When long-term disturbances like climate change are combined with short-term disturbances like fires or flooding, ecosystems can be pushed past a breaking point where important ecosystem services shut down. This project seeks to understand and predict Critical Zone resilience in the face of multiple natural and human disturbances. The research will combine river flow and chemistry data from throughout the U.S. to shed light on how quickly ecosystems recover from local disturbances and to what degree long-term change is altering the structure of the Critical Zone. The team of researchers will combine ecological approaches with data science methods to analyze large quantities of information from thousands of locations. Existing data from public and private organizations across the U.S. will be compiled into a publicly available data base to compare ecosystem recovery times and trajectories. The general patterns observed in the “big data” analysis will be tested by in-depth field studies at four sites experiencing multiple disturbances such as wildfire, acidification, and extreme storms. This project will help Earth science researchers and educators across the U.S. develop a deeper understanding of how the Earth system maintains itself and how humans can avoid eroding the ecosystem services that sustain us. To achieve this goal, all data and approaches will be shared publicly and the research team will lead an innovative outreach and education program. This comprehensive program will educate 7-12 grade teachers to bring cutting-edge ecology and data science to schools across America. To enhance diversity in Earth science and data science, a field camp will be co-designed and implemented in collaboration with historically black colleges and universities. While observatory-based Critical Zone research produces important findings on catchment-scale processes, the global scale of disturbance in the Anthropocene transcends the bounds of a single site or funding cycle, posing a challenge for traditional investigative approaches. This spatial and temporal mismatch significantly limits the predictive power of individual site studies in the context of regional- to continental-scale environmental change. To advance network-scale syntheses and integrate across scales, this project will apply an iterative “pattern to process” and “process to pattern” approach to investigate how Critical Zone structure controls water, carbon, nutrients, and response to overlapping disturbances in the context of multi-dimensional resilience. In this context, the overarching hypothesis is that Critical Zone structure (i.e. configuration of biological, chemical, and physical characteristics) controls the timing, direction, and intensity of linkages among multiple responses and that these linkages regulate ecosystem resilience and resistance to climate and land cover disturbance. To test this overarching hypothesis, (1) existing ecohydrological data will be compiled from across the continental U.S. into a multi-dimensional Critical Zone database, (2) advanced statistical analysis will be performed using complex-systems tools on “big data” to identify state changes in ecological function and ecosystem services, (3) process-hypotheses will be refined based on these data-driven approaches, and (4) in-depth process investigations will be performed at four high-vulnerability focal sites in the northeast and southwest. The database and complex-systems approaches will be shared to empower the Critical Zone community to transition into a phase of data-driven hypothesis generation and cross-site research. To broaden the participation of underrepresented groups in Critical Zone and data science the project will educate and empower a diverse new generation of STEM thinkers from middle and high school to the graduate college level. A comprehensive grade 7-12 education program will reach hundreds of students from high-need Vermont schools (historically marginalized economic, racial or disability groupings) by “educating the educators” in Critical Zone and data science. Furthermore, in collaboration with HBCUs, outdoor education on Critical Zone and data science will be designed and implemented for a diverse group of undergraduate students. This project is jointly funded by the Critical Zone Collaborative Network Program, the Hydrologic Sciences Program in the NSF Division of Earth Sciences, and the Established Program to Stimulate Competitive Research (EPSCoR).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.

地球表面维持生命的部分（临界区）由基岩、土壤、水、空气和生物组成，这些生物已经相互作用了数十亿年。临界区可以吸收许多干扰，同时仍然支持地球上的生命，但人类的年龄或“人类世”给临界区带来了前所未有的压力。当气候变化等长期干扰与火灾或洪水等短期干扰相结合时，生态系统可能会被推过一个临界点，使重要的生态系统服务关闭。该项目旨在了解和预测在面对多种自然和人为干扰的关键区的弹性。这项研究将结合来自美国各地的联合收割机河流流量和化学数据，以揭示生态系统从局部干扰中恢复的速度，以及长期变化在多大程度上改变了临界区的结构。研究团队将联合收割机生态学方法与数据科学方法相结合，分析来自数千个地点的大量信息。来自美国公共和私人组织的现有数据将被汇编成一个公开的数据库，以比较生态系统的恢复时间和轨迹。“大数据”分析中观察到的一般模式将通过在经历野火、酸化和极端风暴等多种干扰的四个地点进行深入的实地研究来测试。 该项目将帮助美国各地的地球科学研究人员和教育工作者更深入地了解地球系统如何维持自身，以及人类如何避免侵蚀维持我们的生态系统服务。为了实现这一目标，所有的数据和方法都将公开共享，研究团队将领导一个创新的推广和教育计划。这个综合性的计划将教育7-12年级的教师，为美国各地的学校带来尖端的生态学和数据科学。为了加强地球科学和数据科学的多样性，将与历史上的黑人学院和大学合作共同设计和实施一个实地营地。虽然基于观测的临界区研究对流域尺度的过程产生了重要的发现，但人类世的全球扰动规模超越了单一地点或资金周期的界限，对传统的调查方法构成了挑战。这种空间和时间上的不匹配极大地限制了在区域到大陆范围的环境变化的背景下对个别地点进行研究的预测能力。为了推进网络规模的综合和跨尺度的整合，该项目将采用迭代的“模式到过程”和“过程到模式”方法来研究关键区结构如何控制水，碳，营养物质以及在多维弹性背景下对重叠干扰的响应。在这种情况下，首要的假设是，临界区结构（即生物，化学和物理特性的配置）控制的时间，方向和强度的多重响应之间的联系，这些联系调节生态系统的弹性和抵抗气候和土地覆盖干扰。为了检验这一总体假设，（1）将把美国大陆现有的生态水文数据汇编成一个多维关键区数据库，（2）将使用复杂系统工具对“大数据”进行高级统计分析，以确定生态功能和生态系统服务的状态变化，（3）将根据这些数据驱动的方法对过程假设进行改进，（4）深入开展东北、西南4个重点脆弱点的过程调查。将共享数据库和复杂系统方法，以使临界区社区能够过渡到数据驱动的假设生成和跨站点研究阶段。为了扩大代表性不足的群体在临界区和数据科学中的参与，该项目将教育和授权从初中和高中到研究生大学水平的多元化的新一代STEM思想家。一个全面的7-12年级教育计划将通过在关键区域和数据科学方面“教育教育工作者”，覆盖来自佛蒙特州高需求学校（历史上被边缘化的经济、种族或残疾群体）的数百名学生。此外，与HBCUs合作，将为不同的本科生群体设计和实施关键区和数据科学的户外教育。该项目由临界区合作网络计划、NSF地球科学部水文科学计划和激励竞争性研究的既定计划（EPSCoR）共同资助。该奖项反映了NSF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。

项目成果

Organizational Principles of Hyporheic Exchange Flow and Biogeochemical Cycling in River Networks Across Scales

• DOI: 10.1029/2021wr029771
• 发表时间: 2022-02
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: S. Krause;Benjamin W. Abbott;V. Baranov;S. Bernal;P. Blaen;T. Datry;J. Drummond;J. Fleckenstein;Jesus Gomez Velez;D. Hannah;J. Knapp;M. Kurz;J. Lewandowski;E. Martí;C. Mendoza‐Lera;A. Milner;A. Packman;G. Pinay;A. Ward;Jay P. Zarnetzke

The meanings of the Critical Zone

• DOI: 10.1016/j.ancene.2023.100377
• 发表时间: 2023-03
• 期刊: Anthropocene
• 影响因子: 3.6
• 作者: Raymond M. Lee;Boris Shoshitaishvili;Rachel L. Buck;J. Bekker;Benjamin W. Abbott

The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime

• DOI: 10.1029/2023wr034484
• 发表时间: 2023-07
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Brian C. Brown;Aimee H. Fulerton;D. Kopp;Flavia Tromboni;Arial J. Shogren;J. Webb;C. Ruffing;M. Heaton;Lenka Kuglerová;Daniel C. Allen;L. McGill;J. Zarnetske;M. Whiles;Jeremy B. Jones;Benjamin W. Abbott

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

• DOI: 10.1007/s13253-022-00513-2
• 发表时间: 2022-09
• 期刊: Journal of Agricultural, Biological and Environmental Statistics
• 作者: Matthew Heiner;Matthew J. Heaton;Benjamin W. Abbott;P. White;C. Minaudo;R. Dupas

Improving sustainable agriculture promotion: an explorative analysis of NRCS assistance programs and farmer perspectives

改善可持续农业推广：对 NRCS 援助计划和农民观点的探索性分析

• DOI: 10.1080/14735903.2022.2056997
• 发表时间: 2022
• 期刊: International Journal of Agricultural Sustainability
• 影响因子: 3.4
• 作者: Thompson, Carson D.;Severe, Emilee;Norris, Adam J.;Gudmundsen, Jacob;Lewis, Mary;Currit, Elisabeth;Newbold, Nicholas;Abbott, Benjamin W.
• 通讯作者: Abbott, Benjamin W.