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    Pooled Monitoring Initiative’s Restoration Research Award Program

    Pooled Monitoring Initiative’s Restoration Research Award Program supports researchers conducting applied studies and developing tools to inform watershed restoration decisions by regulators and practitioners.

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    This grant was recently updated

    Applications are now open, previously closed, with a deadline of January 28, 2027, at 4 pm EST. Registration is now available for online information sessions on December 11 and January 8, both from noon to 1 pm EST.

    Funder: Chesapeake Bay Foundation

    Due Dates: December 11, 2026 (Information session) | January 8, 2027 (Information session) | January 28, 2027, 4 pm EST (Application)

    Funding Amounts: Approximately $1,988,000 available; literature reviews up to $50,000; research projects uncapped, with project-specific timelines

    Summary: Supports applied research addressing watershed restoration questions raised by Chesapeake Bay regulators and practitioners.

    Key Information: Applicants need not be based in Maryland, but proposed work must be relevant to Maryland’s restoration, regulatory, or practitioner communities.


    Description

    The Chesapeake Bay Trust administers the Pooled Monitoring Initiative’s Restoration Research Award Program with state agencies, EPA’s Chesapeake Bay Program Office, local governments, and other partners. The initiative pools resources to connect questions raised by regulatory and practitioner communities with researchers who can deliver findings for direct use in watershed restoration decisions.

    The program supports literature syntheses, hypothesis-driven research, and regulatory or practitioner tools addressing the annual Request for Proposals’ research questions. Its goals include increasing confidence in restoration outcomes, identifying suitable site conditions for particular techniques, improving practice adoption through social science, and informing permitting and monitoring. Research may involve fieldwork, laboratory experiments, modeling, or appropriately collected existing data.


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