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 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 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.

Thin-layer placement (TLP) is an emergent climate adaptation strategy that mimics natural deposition processes in tidal marshes by adding a small amount of sediment on top of marsh in order to maintain elevation relative to sea level rise.

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).