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Resources

Resources

A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.

Displaying 1 - 10 of 48
Multimedia |
Project Lead Kaitlin Gannon gives a short introduction to 2021 science transfer project, "Launching a Community Science Eel Monitoring Project".
Webinar Summary |
This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the two-part February and March 2024 webinar series, "A Collaborative Approach to Advancing Blue Carbon Research and Data Applications."
Multimedia |
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.
Webinar Summary |
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."
Multimedia |

Cultural ecosystem services (CES), one of four main categories of ecosystem services, are often described as the non-material benefits that humans receive from their interactions with the environment.

Report |

This report summarizes five cultural ecosystem service assessment methods piloted by the 2020 catalyst project, Cultural Ecosystem Services in Estuary Stewardship and Management.

Website |

Educators from the Chesapeake Bay National Estuarine Research Reserve in Virginia (CBNERRVA) and the Virginia Institute of Marine Science's (VIMS) Marine Advisory Program cre

Webinar Summary |

This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the September 2022 webinar "Cultural Ecosystem Services in Estuary Stewardship and Management."

Journal Article |

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.

Journal Article |

This 2021 paper from the University of South Florida discusses how machine learning was used to map aquifers throughout the Kenai Lowlands to locate groundwater discharge, providing a framework to extend this method of modeling groundwater to other reserves.