This instructional and informational webinar features background information on the 2020 science transfer Storm Stories project, how end-user feedback was incorporated, the tools and products that have been developed through the project, and how reserves can access resources.

This factsheet, developed by a 2020 catalyst project, provides a brief overview of CES frameworks and categories to complement the information contained in the factsheet “Expanding and Deepening the Application of Cultural Ecosystem Services in Estuary Stewardship and Management ”.

This factsheet, developed by a 2021 catalyst project, summarizes information to strengthen the conceptual foundation and meaningful application of cultural ecosystem services (CES) in the NERRS.

This factsheet, developed as part of a 2020 catalyst project, consolidates case studies of applied CES assessments.

This web resources includes a compilation of lesson plans for grades K - 12 about coastal and estuarine ecology that are intended to complement programs that involve schools in local wetland restoration projects.

This dataset contains processed Surface Elevation Table data from five reserves along with metadata, R scripts, reports, and figures, illustrating how SET can be processed, analyzed and visualized.

This factsheet describes the process of environmental DNA (eDNA) water sampling in estuarine systems, and provides specific methdology recommendations to facilitate detection of invasive species.

This data resource includes eDNA sequences, fish species summary tables, and DNA extractions from Wells, Great Bay, Hudson, Apalachicola, South Slough, and Heʻeia National Estuarine Research Reserves.

This national synthesis report analyzes SET data from 15 National Estuarine Research Reserves across the continental United States, summarizing wetland water level trends over a 19-year period.

A 2018 catalyst project developed tools for working with SET data including a series of computer codes - R scripts - for processing, quality checking, analyzing and visualizing these complex datasets. The statistical codes re available through GitHub and are explained in a Guide to the SETr Workflow.