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INTEGRATING INDICATORS OF ECOLOGICAL CONDITION, STRESSOR EXPOSURE, AND QUALITY OF LIFE TOWARDS AN ASSESSMENT OF REGIONAL VULNERABILITY
Citation:
Smith, E R., R. V. O'Neill, L. T. Tran, AND M. O'Connell. INTEGRATING INDICATORS OF ECOLOGICAL CONDITION, STRESSOR EXPOSURE, AND QUALITY OF LIFE TOWARDS AN ASSESSMENT OF REGIONAL VULNERABILITY. Presented at 3rd International Congress on Environmental indices and indicators: Systems analysis approach INDEX2001: Quality of Life Indiework, Rome, Italy, October 2-5, 2001.
Impact/Purpose:
Provide regional-scale, spatially explicit information on the extent and distribution of both stressors and sensitive resources.
Develop and evaluate techniques to integrate information on exposure and effects so that relative risk can be assessed and management actions can be prioritized.
Predict consequences of potential environmental changes under alternative future scenarios.
Effectively communicate economic and quality of life trade-offs associated with alternative environmental policies.
Develop techniques to prioritize areas for ecological restoration.
Identify information gaps and recommend actions to improve monitoring and focus research.
There are two task objectives that reflect the work done by LCB in support of the ReVA Program objectives:
Provide information management, spatial analysis support, and data and information accessibility for the ReVA Program
Provide program management support, technology transfer, and outreach.
Description:
The U.S. Environmental Protection's Regional Vulnerability Assessment (REVA) Program is developing and evaluating approaches to integrate information on environmental condition, estimated stressor exposures, and quality of life indicators so that regional risks can be prioritized and risk reduction activities can be targeted. As part of EPA's efforts to improve ecological risk assessment methodologies, REVA is focusing on the assessment of multiple stressors affecting multiple resources over a multi-state region. The research is designed to address the questions of 1) which ecosystems in a region are at the greatest risk?, 2) which stressors pose the greatest risk?, and 3) how are these risks likely to change in the future?. Using primarily existing data and model results, and considering the need to include estimates of error and uncertainty , REVA is exploring a variety of statistical and other techniques to synthesize information into relative rankings of vulnerability that are meaningful to decision-makers. These techniques include development of a weighted sums index, weight of evidence methods, multivariate statistics,
fuzzy set theory, and decision theory. Decision support tools that utilize these approaches are under development and will be evaluated as to their suitability for addressing different environmental management questions.