R/UC-2

Impact/Outcome:

This section describes how this project has advanced scientific knowledge and/or made a difference in the lives of coastal residents, communities, and environments. Maryland Sea Grant has reported these details to the National Oceanic and Atmospheric Administration (NOAA), one of our funding sponsors.

RECAP: Researchers created a computer model that predicts the distribution and composition of biodiversity in freshwater streams across a large region of Maryland. The scientists shared the tool with natural-resource managers to inform ongoing efforts to protect and improve these streams, which in turn could help improve water quality in Chesapeake Bay.

RELEVANCE: In 2010, the Environmental Protection Agency established a Total Maximum Daily Load (TMDL) to reduce excess amounts of nutrients and sediment flowing into the Chesapeake Bay. Meeting the demands of the TMDL requires significant improvements to water quality throughout the Bay’s watershed. One tool to accomplish this goal is to restore and protect freshwater streams. This research project has provided comprehensive and high-resolution information on the spatial distribution of aquatic species in Maryland streams. Categorizing stream reaches by species composition provides an empirical basis for identifying degraded and vulnerable stream reaches and prioritizing them for restoration and protection.

RESPONSE: Maryland Sea Grant supported research by principal investigators Matthew Fitzpatrick and Andrew Elmore of the University of Maryland Center for Environmental Science’s Appalachian Laboratory. They developed a biological classification of freshwater stream reaches in Maryland west of the Chesapeake Bay. A challenge in creating this model was to accurately predict species composition in stream locations that have not been monitored directly by the Maryland Biological Stream Survey (MBSS). The new model incorporates statewide data about physical parameters (e.g. slope and soil type) and biological parameters (e.g. fish and benthic macroinvertebrate species) to predict species composition in streams across the study area. The researchers created the model using statistical approaches, such as Gradient Forests, not previously used in this context. Through a competitive process, Miriam Johnston was selected as a Maryland Sea Grant Research Fellow and conducted research on this project.

RESULTS: Completed in 2014, the model classifies Maryland streams into 29 unique groupings of macroinvertebrate species and 22 of fish. The model indicates that the biodiversity of fish and macroinvertebrate assemblages can decline in a rapid, non-linear fashion in response to changes in physical parameters, such as declining forest cover caused by construction projects and other development. The researchers created an online website (http://streammapper.al.umces.edu/streamsbiodiv.html) that maps these community types in streams across Maryland. The website provides information regarding the physical and biological attributes of each 10-meter stream reach in Maryland west of Chesapeake Bay.

The researchers shared the model in a meeting with the Maryland Department of Natural Resources’ Monitoring and Non-Tidal Assessment Division. The scientists also described the model during a day-long workshop sponsored by the Maryland Water Quality Monitoring Council. Attendees included prospective users from management agencies, industry, non-profits, and academia.