The National Estuarine Research Reserve System ’s Science Collaborative program is committed to practicing and supporting responsive and inclusive collaborative science.
Our work is grounded in the Collaborative Science Mindset and Principles we co-developed alongside our partners in the National Estuarine Research Reserve System (NERRS) and National Oceanic and Atmospheric Administration.
Different Ways of Knowing
The NERRS strives to recognize and affirm the existence, value, and validity of different knowledge systems, and the complementary role that longstanding and evolving knowledge in all forms holds alongside institutional science. In building reciprocal relationships with partners, the NERRS and the Science Collaborative acknowledge knowledge systems and ways of knowing that are different yet equivalent to institutional science.
All elements of our program encourage project teams to examine the unique diversity and complexity of the socio-ecological systems in which they work. Doing the best work possible in these environments requires authentic collaboration grounded in reciprocal, equitable, and inclusive relationships. This includes awareness of and integration and elevation of different systems of knowledge so that all participants benefit and feel empowered to bring their experiences to solving coastal and estuarine issues.
DEIJA In Practice
Key program elements emphasize our commitment to improving how we practice and support collaborative science. Some examples of how our program activities support diversity, equity, inclusion, justice, and accessibility:
- Requests for proposals - Value and elevate other systems of knowledge, such as Indigenous knowledge, alongside institutional knowledge.
- Proposal review - Guidance documents recognize all knowledge systems as equally valid and explicitly instruct reviewers about what this might entail when conducting a review.
- Data sharing - Guidance documents include language defining traditional ecological knowledge and Indigenous knowledge, acknowledge differences in the ownership of data across knowledge systems, and specify how these data must be handled.
- Accessible collaboration resources - Tools, advice, and case examples are publicly available in multiple formats via our Guide to Collaborative Science and Resource Library.