Thin-layer sediment placement (TLP) is a promising management tool for enhancing tidal marsh resilience to rising seas.

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

This 2021 article which appeared in Estuaries and Coasts provides a synthesis of native oyster restoration projects conducted from California, USA, to British Columbia, Canada.

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.

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 paper, published in Biological Conservation, describes an innovative approach developed by the NERRS to evaluate the ability of tidal marshes to thrive as sea levels rise.

This 2017 article appeared in the journal Ecology, and presents findings from a study assessing the individual and synergistic effects of air temperature and salinity on Olympia oyster mortality across temporal patterns that accurately reflect the natural environment.

This 2016 journal article was published in Proceedings of the Royal Society B. The study highlights how extreme precipitation events in 2011 may have contributed to near 100% mass mortality of wild oysters in northern San Francisco Bay.

This journal article was published in Estuaries and Coasts in 2016, and decribes a study of how seasonal changes in temperature and salinity impact larval Olympia oyster recruitment across a range of sites and time intervals.