This paper explored the long-term,ceteris-paribus effects of potential CO₂ fertilization on the global forest sector. Based on the findings of Norby et al. (PNAS 2005,102(50)) about forest response to elevated [CO₂].

Forest productivity was increased in the Global Forest Products Model (GFPM) in proportion to the rising [CO₂] projected in the IPCC scenario A1B,A2,and B2. Projections of the forest area and forest stock and of the production,consumption,prices,and trade of products ranging from fuelwood to paper and paperboard were obtained with the GFPM for each scenario,with and without CO₂ fertilization beginning in 2011 and up to 2065.

CO2 fertilization increased wood supply,leading to lower wood prices which in turn induced modest lower prices of end products and higher global consumption. However,production and value added in industries decreased in some regions due to the relative competitive advantages and to the varying regional effects of CO₂ fertilization.

The main effect of CO₂ fertilization was to raise the level of the world forest stock in 2065 by 9 to 10 % for scenarios A2 and B2 and by 20 % for scenario A1B. The rise in forest stock induced by fertilization was in part counteracted by its stimulation of the wood supply which resulted in lower wood prices and increased harvests.

Forest managers must deal with inherently stochastic ecological and economic processes. The future growth of trees is uncertain, and so is their value. The randomness of low-impact, high frequency or rare catastrophic shocks in forest growth has significant implications in shaping the mix of tree species and the forest landscape. In addition, the fluctuations of wood prices influence greatly forest revenues.

Markov decision process models (MDPs) offer a rigorous and practical way of developing optimum management strategies, given these multiple sources of risk.

Examples illustrate how such management guidelines are obtained with MDPs for combined ecological and economic objectives, including diversity of tree species and size, landscape diversity, old growth preservation, and carbon sequestration.

The findings illustrate the power of the MDP approach to deal with risk in forest resource management. They recognize that the future is best viewed in terms of probabilities. Given these probabilities, MDPs tie optimum adaptive actions strictly to the state of the forest and timber prices at decision time. The methods are theoretically rigorous, numerically efficient, and practical for field implementation.