NRT-DESE: Risk and uncertainty quantification in marine science

NRT-DESE:海洋科学中的风险和不确定性量化

基本信息

  • 批准号:
    1545188
  • 负责人:
  • 金额:
    $ 299.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-10-01 至 2021-09-30
  • 项目状态:
    已结题

项目摘要

NRT-DESE: Risk and Uncertainty Quantification in Marine ScienceThe ocean is the last great frontier on Earth, a major driver of climate and productivity, and a critical resource for humans and wildlife. Managing ocean resources requires scientists and managers to work seamlessly to understand the top-down effects of human actions and the bottom-up effects of climate-change on the ocean system. This National Science Foundation Research Traineeship (NRT) project at Oregon State University (OSU) will prepare a new generation of natural resource scientists and managers who will combine mathematics, statistics, and computer science with environmental and social sciences to study, protect, and manage ocean systems. This traineeship program anticipates preparing sixty-one (61) MS and PhD students, including thirty (30) funded trainees, to work in transdisciplinary research groups on user-inspired problems using large and ever-expanding data resources. With powerful analytical tools, they will be best equipped to track and study the top-down effects of human actions and the bottom-up effects of climate change on the ocean system. Besides fulfilling current educational gaps in marine science and management, this OSU NRT program promotes: 1) a transformative and scalable new marine science and policy graduate minor that teaches students to quantify and communicate risk and uncertainty of data-based model forecasts and policy scenarios; 2) the discovery of mechanisms that control the response of marine systems to climate change and human pressures; 3) the development of evidence-based practices for recruiting, training, and retaining diverse graduate students and for placing them into a range of successful careers in Science, Technology, Engineering and Mathematics (STEM). Through a combination of technical coursework, communication workshops, national and international internships, stakeholder engagement, peer mentoring, and involvement in transdisciplinary research projects, OSU NRT trainees will learn about the science of big data, risk and uncertainty quantification and communication and sustainability. They will learn tools and techniques to assist communities in managing resources through change and to recover quickly in the event of a disaster. In line with the learning objectives, the training and research will link new developments in mathematical and statistical quantification of risk and uncertainty, complex and large datasets on marine systems emerging from novel sensors, and outreach and engagement of stakeholders who affect, and are affected by, ocean systems. In addition, students with diverse expertise, developed through internships, will leverage each other's strong disciplinary knowledge and skills as they collaborate to address complex stakeholder-identified climate and policy problems. These collaborations will have the ultimate goal of devising management solutions in the face of change and uncertainty. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.This work is supported, in part, by the Alliances for Graduate Education and the Professoriate (AGEP) program. AGEP is committed to the national goal of increasing the numbers of underrepresented minorities (URMs), entering and completing STEM graduate education and postdoctoral training to levels representative of the available pool. The AGEP program supports the development, implementation, study, and dissemination of innovative models and standards of graduate education and postdoctoral training that are designed to improve URM participation, preparation, and success.
NRT-DESE:海洋科学中的风险和不确定性量化海洋是地球上最后的伟大前沿,是气候和生产力的主要驱动力,也是人类和野生动物的重要资源。管理海洋资源需要科学家和管理者无缝合作,以了解人类行为自上而下的影响以及气候变化对海洋系统的自下而上的影响。俄勒冈州立大学 (OSU) 的国家科学基金会研究实习 (NRT) 项目将培养新一代自然资源科学家和管理者,他们将数学、统计学和计算机科学与环境和社会科学相结合,以研究、保护和管理海洋系统。该培训项目预计准备六十一 (61) 名硕士生和博士生,其中包括三十 (30) 名受资助的受训人员,在跨学科研究小组中使用大量且不断扩展的数据资源,研究用户引发的问题。 凭借强大的分析工具,他们将最有能力跟踪和研究人类行为自上而下的影响以及气候变化对海洋系统的自下而上的影响。除了填补当前海洋科学和管理方面的教育空白外,俄勒冈州立大学 NRT 项目还促进:1)变革性和可扩展的新海洋科学和政策研究生辅修课程,教学生量化和传达基于数据的模型预测和政策情景的风险和不确定性; 2)发现控制海洋系统对气候变化和人类压力的反应的机制; 3) 开发基于证据的实践,以招募、培训和留住多样化的研究生,并让他们在科学、技术、工程和数学 (STEM) 领域取得一系列成功的职业生涯。 通过结合技术课程、交流研讨会、国内和国际实习、利益相关者参与、同行指导以及参与跨学科研究项目,OSU NRT 学员将学习大数据科学、风险和不确定性量化以及沟通和可持续性。他们将学习工具和技术,帮助社区通过变革管理资源,并在发生灾难时快速恢复。根据学习目标,培训和研究将把风险和不确定性的数学和统计量化的新发展、新型传感器产生的海洋系统的复杂和大型数据集以及影响和受其影响的利益相关者的外展和参与联系起来。 ,海洋系统。 此外,通过实习培养出不同专业知识的学生将利用彼此强大的学科知识和技能,合作解决利益相关者确定的复杂的气候和政策问题。这些合作的最终目标是针对变化和不确定性制定管理解决方案。 NSF 研究培训 (NRT) 计划旨在鼓励开发和实施大胆的、新颖的、具有潜在变革性和可扩展的 STEM 研究生教育培训模型。 培训课程致力于通过创新、循证且符合不断变化的劳动力和研究需求的综合培训模式,对高度优先的跨学科研究领域的 STEM 研究生进行有效培训。这项工作的部分支持是研究生教育和教授联盟 (AGEP) 计划。 AGEP 致力于实现以下国家目标:增加代表性不足的少数族裔 (URM) 的数量,进入并完成 STEM 研究生教育和博士后培训,使其达到代表现有群体的水平。 AGEP 计划支持研究生教育和博士后培训创新模式和标准的开发、实施、研究和传播,旨在提高 URM 的参与、准备和成功。

项目成果

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Lorenzo Ciannelli其他文献

Using age compositions derived from spatio-temporal models and acoustic data collected by uncrewed surface vessels to estimate Pacific hake (Merluccius productus) biomass-at-age
使用时空模型得出的年龄组成和无人水面船只收集的声学数据来估计太平洋无须鳕(Merluccius Productus)的年龄生物量
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Derek G. Bolser;Aaron M Berger;Dezhang Chu;Steve de Blois;John Pohl;Rebecca E. Thomas;John Wallace;Jim Hastie;Julia Clemons;Lorenzo Ciannelli
  • 通讯作者:
    Lorenzo Ciannelli

Lorenzo Ciannelli的其他文献

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{{ truncateString('Lorenzo Ciannelli', 18)}}的其他基金

Collaborative Research: NNA Research: Global changes, local impacts: Study of glacial fjords, ecosystems and communities in Greenland
合作研究:NNA 研究:全球变化,当地影响:格陵兰冰川峡湾、生态系统和社区研究
  • 批准号:
    2127242
  • 财政年份:
    2022
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant
Collaborative Research: Tradeoffs between phenology and geography constraints in response to climate change across species life cycles
合作研究:物种生命周期中应对气候变化的物候和地理限制之间的权衡
  • 批准号:
    2049623
  • 财政年份:
    2021
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant
Collaborative Research: Effects of Changing Temperature on the Gulf of Alaska Ecosystem
合作研究:温度变化对阿拉斯加湾生态系统的影响
  • 批准号:
    1558648
  • 财政年份:
    2016
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant
RCN-SEES: Sustainability of Marine Renewable Resources in Subarctic Systems Under Incumbent Environmental Variability and Human Exploitation
RCN-SEES:现有环境变化和人类开发下亚北极系统海洋可再生资源的可持续性
  • 批准号:
    1140207
  • 财政年份:
    2011
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant
CMG Collaborative Research: Reconstruction of Dispersal Strategies of Marine Organisms via Semiparametric Dynamic Spatial Regression
CMG 合作研究:通过半参数动态空间回归重建海洋生物的扩散策略
  • 批准号:
    0934961
  • 财政年份:
    2009
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant
CMG: Collaborative Research: Nonlinear Spatio-Temporal Dynamics and Source-Sink Reconstruction in Marine Species
CMG:合作研究:海洋物种的非线性时空动力学和源汇重建
  • 批准号:
    0621153
  • 财政年份:
    2006
  • 资助金额:
    $ 299.98万
  • 项目类别:
    Standard Grant

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  • 批准号:
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  • 财政年份:
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  • 项目类别:
    Standard Grant
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  • 批准号:
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  • 财政年份:
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  • 批准号:
    1631776
  • 财政年份:
    2016
  • 资助金额:
    $ 299.98万
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  • 批准号:
    1633722
  • 财政年份:
    2016
  • 资助金额:
    $ 299.98万
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  • 批准号:
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  • 财政年份:
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  • 资助金额:
    $ 299.98万
  • 项目类别:
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