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In Senegal, as in most developing countries, domestic energy, much of which is used for preparing meals, is essentially drawn from fuelwood and charcoal. Extensive woodfelling for energy purposes causes severe damages to natural forests, already badly hit by drought and other types of human mismanagement. In this dissertation, it is argued that forest resources, wood energy producers, wood energy consumers and the State are part of a system, the dynamics of which can be represented by simple laws. A simulation model based on these laws is put forward as a tool for preparing the country's long term energy and forestry policies. In this model, the quantities of commercial wood fuels consumed, which affect the dynamics of forest resources, are determined by seeking an equilibrium of prices and consumed quantities on a spatial domestic energy market. The modelisation of price formation over space allows for an estimation of prices as a function of consumed quantities. Price formation is modelized not only for fuelwood and charcoal, but also for the main substitutes. Distances between production sites and consumers play an important role as they determine transport costs. The modelisation of consumption allows for an estimation of consumed quantities by fuel, as a function of prices. Consumers are classified by zone and type of village or town. Consumption by fuel is a result of energy requirements, stove-efficiencies and interfuel-substitution. Interfuel substitution is achieved by letting the part of each fuel (within the total energy requirements) slowly tend towards long-term equilibrium parts. The long term parts are themselves variables given by a linear logistic model as a function of explanatory variables. The importance of fuel prices and consumer income, within these explanatory variables, is highlighted. Apart from the extraction of commercialized wood fuels, the following phenomena are among those affecting the dynamics of forest resources in the model : natural vegetation growth (with yield reductions in case of vegetation depletion or drought), forest clearing for agricultural purposes, forest management (including establishment of fuelwood plantations), and extraction of uncommercial fuelwood. Decision variables, present at all levels of the model, allow for an evaluation of forestry and energy policies. This is shown by some examples of simulation results.