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.

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

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.

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

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

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. 

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

GUIDE CASE STUDY: During the second year of their project, a team based at the Wells Research Reserve suffered the tragic loss of the lead science investigator. This individual had served as the Reserve's research coordinator for many years and possessed a deep reservoir of scientific knowledge about the local ecosystems on which the project was focused. In addition to the intense emotional impact, the loss of a respected researcher and team member posed a significant challenge to the project.

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 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.