This factsheet describes the process of environmental DNA (eDNA) water sampling in estuarine systems, and provides specific methdology recommendations to facilitate detection of invasive species.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
Displaying 11 - 20 of 20See Keywords and Reserves
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.
See Keywords and Reserves
This 2018 catalyst project streamlined and enhanced mapping and decision support tools to help New Jersey coastal communities prepare for sea level rise and extreme storms.
See Keywords and Reserves
This case study discusses an example of an Ecosystem Services Conceptual Model for cultural services at Heʻeia National Estuarine Research Reserve in Hawaii.
See Keywords and Reserves
These coastal hazard risk communication training process agendas can be used to as a model help facilitators develop trainings for coastal decision makers in other communities.
See Keywords and Reserves
These facilitation guides and job aids, part of a Resilience Metrics toolkit, provide tools and activities for each step of the process to develop and track metrics of adaptation success.
See Keywords and Reserves
These case studies, part of a Resilience Metrics toolkit, show how particular communities have defined and tracked their progress on climate adaptation goals.
See Keywords and Reserves
These coastal hazard risk communication workshop materials can be used to help facilitate trainings for coastal decision makers.
See Keywords and Reserves
This climate adaptation planning toolkit compiles lessons learned by five National Estuarine Research Reserves. It is designed to help communities set goals and identify specific indicators to evaluate progress toward a climate resilient future.
See Keywords and Reserves
This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.