GUIDE CASE STUDY: Collaborative science projects are designed to inform and catalyze action, but often those impacts do not develop until after a grant ends. Two project teams working with New England reserves found different ways to support the work of their partners after their grants ended.
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Keywords: enhance collaboration
Reserves: Great Bay, NH, Narragansett Bay, RI, Waquoit Bay, MA, Wells, ME
This resource is a collection of media materials developed for education and outreach for the NY-NJ Eel Partnership that emerged from a two-year science transfer project focused on community eel monitoring.
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Keywords: communication, community science, eels, education (place-based)
GUIDE RESOURCE: This action plan, which emerged through user engagement around the Great Bay Estuary, provides an example of how planning early for end-of-project transitions can successfully fuel future projects with partners.
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Keywords: buffer, living shoreline, watershed, enhance collaboration
This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the October 2023 webinar "Building Capacity for Reserves to be Motus Wildlife Tracking Leaders."
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Keywords: shorebird habitat, climate change, estuarine habitat, wildlife, motus
Reserves: ACE Basin, SC, Grand Bay, MS, Hudson River, NY, San Francisco Bay, CA
This 2022 paper which appeared in Nature discusses a modeling approach to examine the marsh ’s buffering capacity in a changing climate (from 2020 to 2100), considering a potential marsh restoration plan (from 2020 to 2025) and potential marsh loss due to sea-level rise.
This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the May 2021 webinar Can Oyster Aquaculture Help Restore Coastal Water Quality?
This resource includes links to five datasets generated by a collaborative research project that measured nitrogen removal from oyster aquaculture using complement biogeochemistry and genetic methods.
This project overview describes a 2016 Collaborative Research project that designed and applied predictive models to better understand the buffering services provided by Piermont Marsh on New York's Hudson River.