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INDICATORS OF RISK: AN ANALYSIS APPROACH FOR IMPROVED RIVER MANAGEMENT
Citation:
Autrey, B C., R. B. Benjamin, F A. Fulk, J E. Flotemersch, AND K A. Blocksom. INDICATORS OF RISK: AN ANALYSIS APPROACH FOR IMPROVED RIVER MANAGEMENT. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.
Impact/Purpose:
The goal of this research is to develop methods and indicators that are useful for evaluating the condition of aquatic communities, for assessing the restoration of aquatic communities in response to mitigation and best management practices, and for determining the exposure of aquatic communities to different classes of stressors (i.e., pesticides, sedimentation, habitat alteration).
Description:
A risk index is an approach to measuring the level of risk to the plants and/or animals (biota) in a certain area using water and habitat quality information. A new technique for developing risk indices was applied to data collected from Mid-Atlantic streams of the U.S. during 1997 and 1998 because the assumptions required by traditional methods of statistical analysis were not met. Specifically, water and habitat quality data were used to develop risk indices for the invertebrates (animals such as insects, mussels, worms and snails) in these streams. Multiple habitat and water quality measurements were used as predictors of measurements of invertebrates (responses) such as the number of species present or the diversity of invertebrates. Potential predictor and response variables were ranked and sorted. The top 1/3 of the values were placed into the "high" category, the middle 1/3 were placed into the "moderate" category and the bottom 1/3 were placed into the "low" category. Using a step-wise discriminant analysis (a statistical method for determining which measurements are best able to discriminate among groups) followed by Chi-Square tests (a statistical method for determining if the observed distribution of measurements is significantly different from the expected distribution), a set of good (discriminating) predictors were chosen for each response variable. Then, a Maximum Response Profile (MRP) was defined for each response variable. The MRP is the combination of the categories (high, moderate or low) of the discriminant predictors that most frequently results in the response being in the most desirable category (indicating good biological condition). A Risk Index (RI) was then calculated for each response measurement at each sampling location. Each RI was the total number of discriminant predictors at each location that did not fall into the MRP. High RI values were consistently associated with response measurements in the least desirable category (indicating poor biological condition). This analysis approach may help resource managers to better understand the water and habitat quality problems most adversely affecting the biota in their streams, thereby equipping them better to manage these systems.