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.

These four case studies give examples of four best practices for conflict management in collaborative science. They were developed as part of the Resilience Dialogues project to share lessons learned about effective collaboration from within the National Estuarine Research Reserve System.

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).

These case studies, part of a Resilience Metrics toolkit, show how particular communities have defined and tracked their progress on climate adaptation goals.

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

This model was developed by the Hudson River Sustainable Shorelines project team and can be used to understand the energy regimes impacting shorelines and to help identify suitable shoreline stabilization alternatives for sites along the Hudson River.