Project Details
Description
NRT-DESE: Risk and Uncertainty Quantification in Marine Science
The 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.
Status | Finished |
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Effective start/end date | 10/1/15 → 09/30/21 |
Funding
- National Science Foundation