This data resource includes marsh vegetation, water level data and modeling outputs from a project that examined how Piermont Marsh in New York buffers the impacts of storms.

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 curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.

These datasets and statistical analysis codes model surge barrier effects on the Hudson River estuary, developed as part of the 2018 catalyst project Assessing the Physical Effects of Storm Surge Barriers on the Harbor and Hudson River Estuary.

These datasets contain sediment core samples from dam impoundments on tributaries to the Hudson River and tidal wetland complexes in the Hudson River estuary, collected as part of the 2016-2020 collaborative research project Dams and Sediment on the Hudson (DaSH).

This dam sediment estimation tool, developed through the Dams and Sediment in the Hudson (DaSH) project, supports dam removal planning for the Lower Hudson River valley.

These facilitation guides and job aids, part of a Resilience Metrics toolkit, provide tools and activities for each step of the process to develop and track metrics of adaptation success.

This dataset includes a suite of measures of ecological and physical functions of built sustainable shoreline structures at a set of demonstration sites along the Hudson River.

This tool is a novel approach to compare the resilience of different marshes to sea level rise.

This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.