This project overview describes a 2017 Collaborative Research project that is piloting and refining DNA-based monitoring protocols that can be applied to specific issues and species of interest in estuarine ecosystems.

This project overview describes a 2018 Catalyst project led by Grand Bay Reserve that developed standardized tools to quality-check, analyze, and visualize Surface Elevation Table data.

This article, published in Estuaries and Coasts in 2021, estimates sediment impounded behind dams, compares this with new estimates of watershed sediment yield, and assesses the potential fate for dam sediment released into the estuary.

This open-access article examines how a proposed surge barrier for New York harbor might perform over time as sea level rises and storms become more frequenty.

This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the November 2020 webinar Measuring Climate Adaptation Success and Progress: Introduction to the Resilience Metrics Toolkit

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.

This project overview describes a 2018 Catalyst project that facilitated the development of a collaborative research agenda to study the ecological and physical impacts of storm surge barriers on the Hudson River Estuary.

This resource contains the webinar recording as well as the presenter slides and Q&A responses from the September 2020 webinar Dams and Sediment in the Hudson.

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.