NRT: Ecosystem science in the face of rapid ocean change: a convergence approach

NRT: Ecosystem science in the face of rapid ocean change: a convergence approach

This National Science Foundation Research Traineeship (NRT) award to the University of Maine will leverage the unique resources of the Gulf of Maine to train the next generation of scientists, managers, and policymakers in a new, convergent approach to ecosystem science. Researchers, students and community partners will generate, integrate, and apply transdisciplinary knowledge to inform responses to rapid ocean change.

Program participants will develop new ways of understanding and creating data, knowledge, and tools that can be leveraged to enable ecosystem-based approaches. The NRT program activities will help to address the challenges facing Maine’s coastal communities, and are relevant to other natural resource dependent rural communities. This NRT will also benefit society by broadening participation in marine science through the recruitment of trainees from underrepresented groups and training a workforce that recognizes the full array of knowledge and tools available for ecosystem based management (EBM) and climate resilience.

Project participants will contribute science and tools that local, state, tribal and federal resource managers can use to enable ecosystem-based responses to rapid ocean change and develop integrative data streams and tools that blend traditional and local ecological knowledge, existing fisheries and environmental science approaches, and new and emergent data streams. The capacity of scientists, environmental professionals, and other coastal community members will be strengthened as they are more fully prepared to engage in solutions-oriented science and stewardship.

This NRT project anticipates training at least 45 graduate students (22 PhD, 23 MS) over 5-years, including 23 NSF-funded trainees (11 PhD, 12 MS).

This NRT will encourage scholars from across the natural and social sciences to advance EBM knowledge and practice, while empowering community, tribal, and government partners to engage more deeply in ecosystem science and stewardship. EBM refers to place-based management of human interactions with marine species and ecosystems that contributes to the resilience and sustainability of the system; recognizes the reciprocal and multifaceted connections among people and other elements of the system, and seeks to achieve multiple societal goals.

The NRT will develop and institutionalize a new curriculum and academic culture through coursework, community engagement, and collaborative research; build community and government capacity to contribute to EBM in Maine and beyond, create a novel model for engaging diverse trainees in place-based, solutions-oriented science, and develop ways of for integrating and communicating big data from computational science, ecology, genomics, oceanography, and the social sciences with traditional and local ecological knowledge to advance ecosystem science and improve stewardship of ocean systems. Through the convergence of local and traditional knowledge, fine-scale environmental and social data, and new and emerging data-driven methods, this NRT program will develop the intellectual frontier and applications of coastal marine ecosystem science in new ways.

The team will generate and synthesize empirical information and develop and test theories deeply relevant to ecology, environmental governance, and socio-environmental systems science. Trainees will generate data, knowledge and tools directly relevant to the Maine Climate Action Plan’s climate mitigation and adaptation strategies.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

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.