The eDNAtlas is accessed via an interactive ArcGIS Online (AGOL) map that allows users to view and download sample site information and lab results of species occurrence for the U.S. The results are based on samples analyzed at the National Genomics Center for Wildlife and Fish Conservation (NGC) and associated with geospatial attributes created by the Boise Spatial Streams Group (BSSG).
The AGOL maps display results for all species sampled within an 8-digit USGS hydrologic unit or series of units. The map initially opens to the western or eastern project extent, but each allows users to zoom to areas of interest. Symbols indicate whether a field sample has been collected and processed at a specific location, and if the latter, whether the target species was present. Each site is assigned a unique identification code in the database to ensure that it can be tracked and matched to geospatial habitat descriptors or other attributes for subsequent analyses and reports. This functionality previously was enabled only for sample sites on flowing waters but the 6/2021 update added a "HighRes" feature class for lakes, springs, and small streams. These samples may be viewed using the species NHDPlusHR checkbox.
Users also have the option to Download the entire ArcGIS GeoDatabase for local use. The GeoDatabase has more information than is available from the AGOL interactive maps, and enables more detailed queries, analyses, and creation of custom maps. Please refer to the individual feature class metadata in the GeoDatabase for more specific information.
If you use these data, please cite as: Young, Michael K.; Isaak, Daniel J.; Schwartz, Michael K.; McKelvey, Kevin S.; Nagel, David E.; Franklin, Thomas W.; Greaves, Samuel E.; Dysthe, J. Caleb; Pilgrim, Kristine L.; Chandler, Gwynne L.; Wollrab, Sherry P.; Carim, Kellie J.; Wilcox, Taylor M.; Parkes-Payne, Sharon L.; Horan, Dona L. 2018. Species occurrence data from the aquatic eDNAtlas database. Fort Collins, CO: Forest Service Research Data Archive. Updated 30 June 2021. https://doi.org/10.2737/RDS-2018-0010.
We would also like to credit Jennifer Hernandez for the significant amount of work she has put into developing this database.