Jobos Bay - Photo credit: NOAA
These marsh sustainability and hydrology datasets were collected as part of a 2017 collaborative research project.
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.
These datasets are from an intensive field sampling in and adjacent to aquaculture operations in North Carolina, concentrating on wild shellfish resources and the physical and chemical environment, to assess ecosystem services and potential impacts of the oyster farms.
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 He’eia National Estuarine Research Reserves.
These five related carbon storage, greenhouse gas flux and environmental variable datasets were generated by the Bringing Wetlands to Market research team and used to develop a coastal wetland greenhouse gas model for New England.
These tidal wetland carbon stocks and environmental driver data were collected as part of the 2016-2019 collaborative research Pacific Northwest Carbon Stocks and Blue Carbon Database Project.
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 sediment and hydrodynamic data were collected as part of the 2016-2020 collaborative research project Improved Understanding of Sediment Dynamics for the Coos Estuary that produced a new bathymetric dataset for Coos Bay and a hydrodynamic model characterizing sediment distribution and circulation in the estuary.
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.
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).
The collaborative research project, Re-engineering Living Shorelines for High-Energy Coastal Environments, produced four datasets as part of their assessment of liviing shoreline installations at GTM Reserve in Florida.
Three related datasets were generated by the 2015 - 2019 collaborative research project Evaluating Living Shorelines to Inform Regulatory Decision-Making in South Carolina.
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 geodatabase contains GIS layers that illustrate the distribution of existing wetlands and identify locations where restoration is likely to have the greatest positive environmental impact in Douglas County, WI.
The Communities, Lands & Waterways Data Source is an encyclopedic compilation of all available data describing the socioeconomic and environmental conditions in the Coos Bay area.