Modelling regeneration and pest control alternatives for a forest system in the presence of fire risk

This thesis attempts to provide solutions for the fire and pest protection forest management modelling and model representation problems. The modelling problem seeks the optimal regeneration harvest and pest protection schedules by age and species taking into account fire risk, that produces a desired wood quantity over time at maximum discounted net profit. An LP model is developed to economically evaluate alternative regimes for protection spraying of susceptible forest species against insect infestations and alternative harvesting strategies which include conversion of susceptible species to non-susceptible, by planting. These strategies are evaluated subject to catastrophic loss due to fire. The model representation problem, which involves issues of understandability, was addressed by using a high level model development system and a processing network representation of the underlying algebraic description. An iterative simulation-optimization approach is developed which tests how well the deterministic model holds in a simulated stochastic environment. This validation procedure involves solving the optimization problem deterministically using average values for the fire and infestation proportions and also at each time period updating the system state by simulating the state transition for the next time period with the simulation model using randomly generated proporations and resolving using the updated state as the new initial condition. An optimal wood supply trajectory in a simulated stochastic environment is therefore constructed. The results from the iterative stochastic solution provided a confidence measure for the deterministic solution. The effectiveness of the deterministic model was evaluated in terms of how flexible its structure is in distinguishing alternative policy options.