This dataset compiles salt marsh monitoring from four New England NERRs from 2010 to 2018, as part of a catalyst project to sythesize and identify regional trends in salt marsh data in the reserve system.

This how-to guide describes how to synthesize salt marsh monitoring data from the National Estuarine Research Reserve System.

This how-to guide describes how to integrate plant cover data from two common methods of estimating marsh plant cover.

This webinar, conducted June 30, 2020, presents research findings from the 2018-2020 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 resource contains the presenter slides, Q&A responses, recording, and presenter bios from the June 2020 webinar Credit for Going Green: Using an Expert Panel Process to Quantify the Benefits of Buffers.

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.

This open-access article, published Geophysical Research Letters in 2020, uses turbidity observations to characterize estuary response following extreme discharge such as from storm-related flooding, which can be a proxy for sediment release from dam removals.

This article, submitted for publication to Earth Surface Processes and Landforms in 2020, describes findings from the Dams and Sediment in the Hudson (DaSH) project related to tidal wetland growth in the Hudson River estuary as a result of human activities. It presents sediment accumulation rates in marshes along the Hudson and reveals the rapid growth of marshes associated with anthropogenic structures.

This factsheet summarizes findings from the Dams and Sediment in the Hudson (DaSH) collaborative research project.