Empirical stressor–response relationships for prospective risk analysis

Abstract

AbstractEnvironmental modeling has long been a recognized part of environmental risk assessment. Traditionally, environmental models have been deterministic models for specific processes over small areas using spatially aggregated subunits for data collection and processing. For an analysis of environmental risk factors on a regional scale, such models are not always appropriate because of uncertainties in the processes, heterogeneity of the environment, and extensive data requirements. Under such circumstances, statistical modeling of the environment can offer useful insights because it deals with a combination of processes and provides a broad view of the degree and significance of the factors impacting ecological resources on a regional scale. Using data from the Eastern Cornbelt Plains ecoregion of Ohio, USA, we have developed several statistical models relating anthropogenic activities on the watershed and a set of stream condition variables to the biological quality of stream segments. The effects of land use and in‐stream physical and chemical factors on the biological indicator, the index of biotic integrity, have been studied using nested watersheds as geographic units. The effects of scale and spatial aggregation have been integrated into the model. A geographic information system database was built using Arc/Info® software (Environmental Systems Research Institute, Redlands, CA, USA) for integrating and summarizing data. The results can be used as a screening model to help planners review the potential cumulative impacts of human activities on indicators of fish community structure. Future work will try to account more explicitly for distance decay of pollutants and the effects of underlying geology and soils on variations in biological diversity.