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Modeling Prescribed Surface-Fire Regimes for Pinus strobus Conservation
Authors:JENNIFER L BEVERLY†  DAVID L MARTELL†
Institution:Faculty of Forestry, University of Toronto, Earth Sciences Centre, 33 Willcocks Street, Toronto, Ontario, M5S 3B3 Canada
Abstract:Abstract:  We developed a simple model of   Pinus strobus L. stand dynamics to compare the impacts of different temporal arrangements of surface fires designed to reflect the application of fire as both an essential ecosystem process (natural fire) and as an efficient means of producing specific habitat features or other values (optimal fire). We used a stochastic simulation model of fire processes to estimate the mean fire-return interval that would maximize stand structural diversity. We investigated trade-offs between structural diversity and temporal population stability associated with changes in the fire interval and used a deterministic version of the model to explore the effects of scheduling fires at fixed intervals. In stochastic simulations, maximum structural diversity occurred at intermediate levels of disturbance (40-year mean fire interval). When fires were scheduled at fixed intervals, a longer, 100-year return interval maximized diversity. Mean fire-return interval was a mitigating factor in the diversity-stability relationship, which changed from positive to negative as the fire interval was reduced progressively from 250 to 5 years. As an alternative to scheduling fires at specified mean intervals, we developed a goal-programming model (a form of linear programming model) and used it to identify an optimal fire schedule for achieving habitat and visual-quality objectives. In comparison with the 40-year stochastic mean fire interval, which maximized structural diversity, the optimal schedule produced comparable levels of both diversity and fire frequency. Our results show how simulation and goal-programming models can be used to evaluate prescribed fire-scheduling alternatives and to explore the comparative advantages of natural and optimal fire-management approaches.
Keywords:decision analysis  disturbance  optimization  prescribed fire  simulation
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