This project overview describes a 2015 Science Transfer project at the Tijuana River Reserve that used existing knowledge and gathered new data to improve the health and management of lagoons in southern California.

This project overview describes a 2015 Science Transfer project that used scenario planning and the best available science to facilitate local dialogue addressing how climate change may impact the Kenai Peninsula, Alaska.

This project overview describes a 2017 Collaborative Research project that generated precise estimates of nutrient retention by Lake Erie wetlands to inform management and decision making.

This project overview describes a 2017 Collaborative Research project that tested the effectiveness of thin-layer sediment placement as a marsh adaptation strategy.

These slides summarize a webinar given by Thomas Grothues of the Jacques Cousteau Reserve on September 19, 2018 about methods for analyzing trends in SWMP temperature with missing data.

This manual was developed as part of the Hudson River Sustainable Shorelines Project and describes simple, low-cost, representative methods for evaluating the function and integrity of ecologically enhanced shoreline projects.

Eleven projects have been recommended for funding by the National Oceanic and Atmospheric Administration ’s National Estuarine Research Reserve System (NERRS) Science Collaborative.

These slides summarize a webinar given by Sarah Nuss of the Chesapeake Bay-VA Reserve on May 31, 2018 about her 2015 Science Transfer project seeking to create a network that supported the transfer of graduate student science to K-12 educators in Virginia.

These slides summarize a webinar given by Danielle Boudreau and Syverine Bentz on December 20, 2017, on how they used scenario planning to overcome uncertainty around barriers to climate adaptation in southcentral Alaska.

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.