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Adapting EPA’s National Coastal Condition Assessment approach to support local coastal resource management using secondary data sources
Citation:
Harwell, L., C. McMillion, AND A. Lamper. Adapting EPA’s National Coastal Condition Assessment approach to support local coastal resource management using secondary data sources. 2021 National Monitoring Conference on Working Together for Clean Water, Virtual, April 19 - 23, 2021.
Impact/Purpose:
Communicate the research regarding the development of a framework to increase the utility National Coastal Condition data and methods for use at state and local coastal resource management scales
Description:
The US EPA’s National Coastal Condition Assessment (NCCA) is a wellspring of coastal ecological data. Using probabilistic survey designs and standardized sampling protocols, estuarine and near-shore waters are sampled coast to coast, including the Great Lakes. The physical, chemical, and biological data produced by the NCCA are used to characterize the extent of ecological conditions in coastal resources across the U.S. However, as robust and plentiful as the NCCA data set is, sometimes it is not enough. For many cases, the NCCA data lacks the spatial density, sampling frequency, or targeted indicators needed to support state and local coastal management priorities. To address this challenge, we reimagined a series of existing approaches to create an open-source code framework for integrating NCCA with secondary data to address information gaps that are often present at smaller spatial scales. The process synthesizes multi-sourced data using a hexagon mosaic over a GIS shapefile representing a coastal area of interest. A subset of individual hexagons is randomly selected to help optimize spatial balance in the hexagons chosen to represent the sampled coastal population. The NCCA data analysis method is incorporated to produce a cumulative distribution function for ecological metrics representing the estimated distribution of measured values across the entire area of interest. Generated results may be visualized in various ways or further analyzed. Our objective for this work is to offer a simple approach to capitalize on the availability of locally-held coastal data collected through state, local, and citizen-science programs to produce more robust NCCA-like coastal condition assessments for smaller areas of coastal resources.
