Seventeen projects involving 27 reserves across the nation and totaling more than $2 million have been recommended for support by NOAA’s National Estuarine Research Reserve System (NERRS) Science Collaborative.

This dataset comprises the data collected and produced as part of the 2016 research project Investigating the Interconnectedness of Climate Change, Nuisance Mosquitoes, and Resilience of Coastal Salt Marsh Systems.

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.

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).