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HP8 Field Biological Monitoring of Ecosystem Impairment
() Inferring causes of biological impairment in Appalachian streams (1): Watershed-based problem formulation.
Boschen, C.1, Burton, J.1, Bailey, J.4, Gerritsen, J.2, Lowman, B.4, Ludwig, J.3, Wilkes, S.3, Wirts, J.4, Zheng, L.2, 1 Tetra Tech Inc., Fairfax, VA, USA4 West Virginia Department of Environmental Protection, Charleston, WV, USA2 Tetra Tech Inc., Owings Mills, MD, USA3 Tetra Tech Inc., Charleston, WV, USA
ABSTRACT- Human activities such as mining, logging, agriculture and residential development have caused biological degradation to streams of West Virginia, USA. Through its benthic macroinvertebrate monitoring program, the West Virginia Department of Environmental Protection (WVDEP) has identified streams across the state that do not meet aquatic life use designations and are, therefore, considered biologically impaired. Total Maximum Daily Loads (TMDLs) are being developed for all biologically-impaired streams within the state. TMDL development requires that the causes of impairment, or stressors to the biological community, be identified so that pollutants can be controlled in each watershed. USEPA's Stressor Identification, a formal investigative process, was used to identify and rank physical, chemical, and biological stressors that may have caused impairments to the aquatic community. This process involves the analysis of all available water quality, habitat, physical, biological, historical, anecdotal, and observational data to infer the likely causes of impairment for each stream. We developed a comprehensive conceptual model that provides the linkage between potential impairment causes, their sources, and the pathway by which each stressor can impact the benthic macroinvertebrate community. Data were analyzed using established water quality standards and stressor-response threshold values were developed based on statistical analysis and reference population data. Quantitative data were plotted and analyzed spatially using a "geo-order" scheme of assigning relative positions to sampling locations from downstream to upstream for each impaired stream and its tributaries within a subwatershed. Watershed characteristics (e.g. land use, soils), point source inventories, site observations, and other lines of evidence were included in the analysis to identify sources of the stressors. The problem formulation, conceptual model development, and data analysis described here are critical to set the stage for diagnostic model development, and for strength of evidence analysis to evaluate each candidate cause, and develop stream-specific conclusions.
Key words: bioassessment, stressor identification, streams, TMDL
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