5th Symposium on Fire and Forest Meteorology and the 2nd International Wildland Fire Ecology and Fire Management Congress

Tuesday, 18 November 2003: 9:00 AM
Spatial Modeling Tools for Prioritizing Limited Prescribed Fire Resources
J. Kevin Hiers, Eglin Air Force Base, Niceville, FL; and J. H. Furman and S. C. Laine
Prescribed fire resources are frequently insufficient to manage landscapes for all conservation or resource management objectives, necessitating tradeoffs as to the portion of the landscape that receives fire within any given year. Defining the rules of these tradeoffs when applying limited prescribed fire to large landscapes is made more difficult by the complexity of weighing competing management objectives at the landscape scale. Eglin Air Force Base has used a simple four-step spatial modeling process to help managers prioritize limited prescribed fire resources across its 185,000-ha landscape. First, managers and biologists identify key conservation criteria and landscape management objectives that drive the application of prescribed fire. Second, remote sensing and other spatial data are developed to directly or indirectly represent all of these criteria. Third, using geographic information system software in a facilitated workshop, each criterion is weighted by managers according to its contribution to overall burn prioritization, and values for the criterion are scored as to how they influence the need to burn. Lastly, the model is validated through research and monitoring and is adapted to evolving management objectives. This process was successfully transferred to the 80,000-ha Blackwater River State Forest. The advantages to this simple modeling approach for prioritizing limited prescribed fire resources are its reliance on accessible geographic information system software, the articulation of spatially explicit management objectives, its ease of transferability, and its clearly stated assumptions about management actions that may be tested through monitoring and reviewed through public comment.

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