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LINKING BROAD-SCALE LANDSCAPE APPROACHES WITH FINE-SCALE PROCESS MODELS: THE SEQL PROJECT
Citation:
Wagner, P F. LINKING BROAD-SCALE LANDSCAPE APPROACHES WITH FINE-SCALE PROCESS MODELS: THE SEQL PROJECT. Presented at US International Association Landscape Ecology (IALE) Annual Meeting, Las Vegas, NV, April 2, 2004.
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:
Regional landscape models have been shown to be useful in targeting watersheds in need of further attention at a local scale. However, knowing the proximate causes of environmental degradation at a regional scale, such as impervious surface, is not enough to help local decision makers of a major metropolitan community develop long- term planning strategies. Using broad scale models outputs in such a setting leaves little room for the future growth necessary to such communities. In order to meet local planning needs a finer scale modeling approach which takes into account both regional landscape data, as well as, community growth and development patterns must be implemented. A decision support tool developed by the EPA's Regional Vulnerability Assessment Program (ReVA) which synthesizes, presents, and projects future scenarios was utilized to combine both broad-scale landscape data and fine-scale process models. We have found that this mixed approach successfully meets the planning needs of local decision-makers, while providing information useful to regional EPA offices.