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(52-31) Assessing landscape level ecological risks using the relative risk model. Landis, Wayne*,1,10, Chen, Joy1, Duncan, A. Bruce2, Luxon, Matt3, Markiewicz, April1, Moraes, Rosana4, Obery, Angela5, Thomas, Jill6, Walker, Rachel7, Wiegers, Janice8, 1 Western Washington University, Bellingham, WA10 2 U. S. Environmental Protection Agency, Region 10, Seattle, WA3 Windward Associates, Seattle, WA4 Chalmers University of Technology, Gothenburg, Sweden5 Department of Environmental Quality, Eugene, OR6 National Council for Air and Stream Improvement, Anacortes, WA7 Serve-Ag Research, Devonport, Tasmania8 Alaska Department of Environmental Conservation, Fairbanks, AK ABSTRACT- Since 1997 the relative risk method (RRM) proposed by Wiegers and Landis has been used in seven studies to generate regional risk hypothesis at a variety of scales. These scales have ranged from an urban watershed a few square kilometers in size, to a Brazilian rainforest and large coastal marine areas. The methodology is inherently spatially explicit and uses non-dimensional ranks to allow the combining of multiple stressors, habitats and impacts to allow cumulative estimates of relative risk. The patterns of risk can be mapped within a landscape and then tested using a variety of techniques. There are ten fundamental steps in all of our assessments: 1) list the important management goals for the region and where they are; 2) make a map that includes potential sources and habitats relevant to the management goals; 3) break the map into regions based upon a combination of management goals, sources and habitats; 4) make a conceptual model that ties the stressors to the receptors and to the assessment endpoints; 5) develop a ranking scheme to allow the calculation of relative risk to the assessment endpoints; 6) calculate the relative risks; 7) evaluate uncertainty and sensitivity analysis of the relative rankings; 8) generate testable hypotheses for future investigations to confirm the risk rankings; 9) test the hypotheses with particular attention to landscape patterns; and 10) communicate the results in a fashion that portrays the relative risks and uncertainty in a response to the management goals. Testing of the risk predictions with examining population dynamics and community structure is presented for two cases. The use of Monte Carlo methods in the evaluation of uncertainty has also been developed for the Finally, the application of the RRM is presented for the analysis of management options for regional sustainability. Key words: regional risk assessment, relative rank method, sustainability, environmental management |
