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$1 million project aims at restoration efforts to Great Bay Estuary

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The upcoming project is an interdisciplinary effort to restore eelgrass beds and oyster reefs to Great Bay and test the efficacy of combining these efforts. (Courtesy photo)

The Municipal Alliance for Adaptive Management (MAAM) and its project partners are commencing a $1,000,000 Oyster and Eelgrass Restoration Project in the Great Bay Estuary. This two-year, federally funded project is the result of innovative regional collaboration and support from U.S. Sen. Jeanne Shaheen, D-NH.

The upcoming project is an interdisciplinary effort to restore eelgrass beds and oyster reefs and test the efficacy of combining these efforts. The project team is comprised of multiple partners, including the University of New Hampshire (UNH), the Piscataqua Region Estuaries Partnership, The Nature Conservancy, Conservation Law Foundation, the National Oceanic and Atmospheric Administration (NOAA), New Hampshire oyster farmers, and other stakeholders.

The Municipal Alliance for Adaptive Management is a collaborative effort established by an inter-municipal agreement between 7 municipalities (Rochester, Dover, Portsmouth, Exeter, Newington, Milton, and Rollinsford) which own 8 wastewater treatment facilities that discharge to the Great Bay watershed and are subject to the US Environmental Protection Agency's (EPA) 2021 Great Bay Total Nitrogen General Permit. The permit is designed to comprehensively regulate nitrogen loading from 13 eligible New Hampshire wastewater treatment facilities on a watershed-wide scale and incorporates an adaptive approach to achieving water quality standards in the Great Bay estuary through a combination of mandatory point source and voluntary nonpoint source nitrogen reductions.

The MAAM was formed in 2021 to facilitate and enhance community collaboration, stakeholder input, resource sharing, expertise, and efficient use of investment to support members' compliance with the General Permit and to better understand and accomplish water quality monitoring and improvement in the Great Bay watershed. The MAAM intends to approach the voluntary nonpoint source nitrogen reduction work in the permit by engaging many stakeholders in the watershed to work collaboratively to develop a series of actions and projects across the municipalities that will benefit the water quality of Great Bay. Partnering communities have committed to participate in the planning and cost of ambient water quality monitoring, data gathering, and water quality analysis along with other stakeholders. Their financial commitment for the duration of the permit is to collectively fund at least $200,000 annually towards this voluntary water quality monitoring and analysis. To date, the MAAM communities have funded $226,075 in 2021 and $422,805 in 2022 for these monitoring activities and related costs and voted to fund $566,700 for 2023 at the December 7th meeting.

In an effort to expand the voluntary work beyond what the communities are already accomplishing, the MAAM filed an application in 2021 through Congressionally Directed Spending with Senator Shaheen's office to support a restoration project and the MAAM's efforts to improve water quality in the Great Bay Estuary. Senator Shaheen advocated for this project as Chair of the Senate Appropriations Subcommittee on Commerce, Justice, Science, and Related Agencies; and in 2022, MAAM was provided notice of its approved federal appropriation in the FY 2022 federal budget in the amount of one million dollars ($1,000,000).

This $1,000,000 investment in both eelgrass and oyster bed restoration will employ natural efforts to treat and improve water quality in the estuary. Historically, restoration efforts in Great Bay for oysters and eelgrass largely have occurred independently. This project is designed to build upon the long-term history of research by UNH, NOAA, and partners to restore eelgrass beds and oyster reefs together, support ongoing mapping efforts and monitor progress to better understand both habitat types and how they interact. It will consist of four major objectives: 1) Eelgrass bed and oyster reef restoration through the development of 1.0 acre of oyster habitat and 0.5 acre of eelgrass habitat; 2) Monitoring the efficacy of oyster reef and eelgrass bed restoration; 3) Modeling the effects of oysters and eelgrass on water quality; and 4) Production of a draft comprehensive restoration program.

In carrying out these objectives, the project team seeks to learn about and advance the successful creation of sustainable habitat in Great Bay by trying new restoration techniques, monitoring the restoration sites, using modeling to quantify beneficial impacts from oysters and eelgrass, and synthesizing this knowledge to develop a long-term restoration plan for eelgrass and oysters with multiple partners.

The data gathered from this project will inform future eelgrass and oyster restoration efforts, the effects of performing this work in adjacent areas, and provide additional understanding of the role of these projects on water quality in the estuary. MAAM and the project partners anticipate that in addition to meeting the project objectives, the Great Bay estuary will benefit from increased eelgrass and oysters in the estuary which generates positive impacts on its health.

Project implementation is planned for two years, beginning in spring 2023 and success will be evaluated upon the completion of all monitoring efforts to study the health of the eelgrass beds and oyster reefs restored during this process, reporting on the anticipated water quality benefits resulting from these efforts and development of a comprehensive restoration plan.

More information about the project's researchers and other research in the Great Bay Estuary can be found on the Jackson Estuarine Laboratory's website https://marine.unh.edu/research-centers/facilities/jackson-estuarine-laboratory.

To learn more about the Municipal Alliance for Adaptive Management and this collaborative work in the region, visit https://www.cityofportsmouth.com/legal/municipal-alliance-adaptive-management.

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