Predicting Levels of Stress from Biological Assessment DatA: Empirical Models from the Eastern Corn Belt Plains
Biological assessment is becoming an increasingly popular tool in the evaluation of stream ecosystem integrity. However, little progress has been made to date in developing tools to relate assessment results to specific stressors. This paper continues the investigation of the feasibility of using fish and benthic macroinvertebrate community structure to distinguish among major types and degrees of anthropogenic stressors in the Eastern Corn Belt Plains ecoregion of Ohio, USA.
This paper builds on a previous effort that constructed a data set of spatially and temporally matched stressor and response data, reduced the stressor data to sic orthogonal factors, and explored the ability of the biological community to discriminate among the different types and degrees of stress. . That study found that biological variables could significantly distinguish higher and lower quality sites classified on the basis of six different types of stress: quality sites classified on the basis of six different types of stress: quality of stream corridor structure; degree of situation; total suspended solids (TSS), iron (Fe), and biochemical oxygen demand (BOD); chemical oxygen demand (COD) and BOD; lead (Pb) and zinc (Zn); and nitrate and nitrite (NOx) and phosphorus (P). Functions based on biological variables could also discriminate between sites having different predominant stressors (12 of 15 pairwise combinations).