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PREDICTING LEVELS OF STRESS FROM BIOLOGICAL ASSESSMENT DATA: EMPIRICAL MODELS FROM THE EASTERN CORN BELT PLAINS, OHIO, USA
Citation:
Norton, S B., S M. Cormier, M. Smith, R. C. Jones, AND M SchubauerBerigan. PREDICTING LEVELS OF STRESS FROM BIOLOGICAL ASSESSMENT DATA: EMPIRICAL MODELS FROM THE EASTERN CORN BELT PLAINS, OHIO, USA. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 21(6):1168-1175, (2002).
Impact/Purpose:
The purpose of this research project is to provide methods, tools and guidance to Regions, States and Tribes to support the TMDL program. This research will investigate new measurement methods and models to link stressors to biological responses and will use existing data and knowledge to develop strategies to determine the causes of biological impairment in rivers and streams. Research will be performed across multiple spatial scales, site, subwatershed, watershed, basin, ecoregion and regional/state.
Description:
Interest is increasing in using biological community data to provide information on the specific types of anthropogenic influences impacting streams. We built empirical models that predict the level of six different types of stress with fish and benthic macroinvertebrate data as explanatory variables. Significant models were found for six stressor factors: stream corridor structure; siltration; total suspended solids (TSS), biochemical oxygen demand (BOD), and iron (Fe); chemical oxygen demand (COD) and BOD; zinc (Zn) and lead (Pb); nitrate and nitrite (NOx) and phosphorus (P). Model R2 values were lowest for the siltation factor and highest for TSS, BOD, and Fe. Model R2 values increased when spatial relationships were incorporated into the model. The models generally performed well when applied to a random subset of the data. Performance was more mixed when models were applied to data collected from a previous time period, perhaps because of a change in the spatial structure of these systems. These models may provide a useful indication of the levels of different stresses impacting stream reaches in the Eastern Corn Belt Plains ecoregion of Ohio, USA. More generally, the models provide additional evidence that biological communities can serve as useful indicators of the types of anthropogenic stress impacting aquatic systems.