Bottom-up and top-down approaches to assess multiple stressors over large geographic areas

• Published in: Environmental toxicology and chemistry Vol. 19; no. 4; pp. 1066 - 1075
• Main Authors: Dyer, Scott D., White-Hull, Charlotte, Carr, Gregory J., Smith, Eric P., Wang, Xinhao
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Hoboken Wiley Periodicals, Inc 01.04.2000; SETAC
• Subjects: Agnatha. Pisces; Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Biotic integrity; Ecotoxicology, biological effects of pollution; Effects of pollution and side effects of pesticides on vertebrates; Effluent; Freshwater; Fundamental and applied biological sciences. Psychology; Geographic information system; Index; Mixtures; Pisces; USA, Ohio, Great Miami R; Ohio; United States; North America; America; USA, Ohio; Evaluation; Environmental management; Stress; Freshwater environment; Biotic integrity index; Vertebrata; Animal community; Geographic information system; Pisces; Watershed; Stream; Water pollution; Environmental monitoring
• ISSN: 0730-7268; 1552-8618
• DOI: 10.1002/etc.5620190437

The relationship of multiple factors, such as instream habitat, drainage area, gradient, cumulative effluent, conventional pollutants, and chemical mixtures, to fish communities was explored at the subbasin, basin, and state level within the state of Ohio, USA. Two approaches were used: bottom‐up, which focused on subbasin‐ and basin‐level relationships within the Great Miami River, Ohio, and top‐down, focusing on relationships across the entire state. Data were provided by the Ohio Environmental Protection Agency and the U.S. Environmental Protection Agency. These data were integrated via a geographical information system. Multiple linear regression was used to determine the strength of stressor–response relationships. The greatest amount of variation of the index of biotic integrity (IBI) and selected metrics was addressed at the subbasin level, followed by the basin and state level, respectively. Overall, habitat factors were the best predictors and positively related to the IBI and number of fish species. Chemical factors, such as cumulative effluent, metals, ammonia, and biochemical oxygen demand, were consistently observed as negative, moderating factors for IBI and fish taxa richness and were the best predictors of the percent of fish observed with deformities, fin erosions, lesions, and tumors.