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Resources

Resources

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

Displaying 11 - 20 of 144
Journal Article |
Abstract

Rising coastal flood risk and recent disasters are driving interest in the construction of gated storm surge barriers worldwide, with current studies recommending barriers for at least 11 estuaries in the United States alone.

Report |
About the project

Through a 2020 catalyst project, staff from the South Carolina Department of Natural Resources worked with ACE Basin NERR and U.S.

Report |

This white paper, developed by a 2020 catalyst project, provides an overview of expanding and deepening the application of cultural ecosystem services in the National Estuarine Reserve System.

Report |

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

Journal Article |

A peer-reviewed article describing the potential link between water temperature variability and eelgrass loss in the Coos Estuary of southwest Oregon.

Journal Article |

A peer-reviewed article describing several of the biosensor tools and the design process used to build them, as part of the 2021 Collaborative Research project incorporating bivalve biosensors into estuary monitoring infrastructure. 

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

Report |

Recommendations for the NERRS SWMP, summarizing outputs in an archivable format deemed useful by end users (NERRS research staff).

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.