Forest planning and productivity-risk trade-off through the Markowitz mean-variance model

Using the Markowitz mean-value (M-V) portfolio model, we study forest planning looking at arbitration between productivity and risk. By weighting the forest productivity with factors of future climate change effects, we compute the optimal tree species mixes, within reach of forest managers, in ninety French administrative departments. Considering three productivity measures (wood production, carbon sequestration and economic valorization) and their respective variances, we found that: a) optimizing productivity and carbon sequestration yields allocations close to the empirical ones; b) forest managers prefer low variance to high productivity, i.e. their revealed risk aversion is high; and c) unlike maximizing wood productivity or carbon sequestration, which lead to similar portfolios, maximizing the economic value of wood production increases (decreases) wood production and carbon sequestration under risk aversion (neutrality). Under high risk aversion, the economic valorization would lead to a high species specialization, which is very unlikely in reality. In all considered scenarios, the objectives set out in the Kyoto Protocol would be attained, which puts into question its relevance in terms of additionality.