A peer-reviewed article describing the potential link between water temperature variability and eelgrass loss in the Coos Estuary of southwest Oregon.

This 2021 paper from the University of South Florida discusses how machine learning was used to map aquifers throughout the Kenai Lowlands to locate groundwater discharge, providing a framework to extend this method of modeling groundwater to other reserves.

This article, published in JGR Oceans in 2020, describes the use of a high-resolution model of water and sediment dynamics used in the Coos Bay estuary in Oregon to assess how 150 years of modification have altered sediment storage and transport.

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 project overview describes a 2016 Collaborative Research project in which researchers are conducting the first-ever comprehensive blue carbon assessment in Pacific Northwest tidal wetlands.

This project overview describes a 2018 Catalyst project that demonstrated the feasibility of including carbon finance in funding strategies that support the conservation and restoration of tidal wetlands in the Pacific Northwest.

This article, which appeared in Global Change Biology, discusses findings from a study that quantified total ecosystem carbon stocks of major tidal wetland types in the Pacific Northwest.

This project overview describes a 2018 Catalyst project that created the web-based toolkit Resilience Metrics to share lessons learned on successful climate adaptation planning within the National Estuarine Research Reserve System.

This project overview describes a 2017 Collaborative Research project where Kachemak Bay Reserve staff and local partners are developing a conceptual model and geospatial layer that can be used to predict specific locations where groundwater discharge and recharge occur.