The 2020-2021 catalyst project Refining Techniques for High-Frequency Monitoring of Chlorophyll in the NERRS brought together twelve biogeochemically diverse reserves to compare results from new YSI in situ sensor technology with ex
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A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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With funding from the NERRS Science Collaborative, scientists from 12 biogeographically diverse Reserves compared fluorescence measurements taken by the YSI EXO TAL sensor to extracted chlorophyll concentrations processed in the lab.
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Standardized protocols for sensor-based chlorophyll monitoring are now available for use by staff around the system to implement high frequency chlorophyll monitoring at their reserves.
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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.
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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.
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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.
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This curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.
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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.
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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).
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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.