Currently transformation from even-aged management to near-natural forest management is being
considered or undertaken throughout the Atlantic region of Europe. What in general lies in this
transformation is the desire for a higher degree of utilisation in forest management of the natural
processes inherent in the forest ecosystem. The motivations for transforming involve economic,
biological and social values. At the same time, potential climate changes are expected to change
growing conditions of tree species – possibly having a high impact on future forest growth.
The purpose of this dissertation was to analyse the effects of general uncertainties, such as climate
change uncertainty, on the economics of transformation – how they affect the process and how we
can deal with them. In addition to climate change uncertainty, risk of wind throw and price
uncertainty were also included. Specifically, the studies of the dissertation analysed changes in
stand structure and the choice of species at the stand and forest level. Only the value of timber was
considered. Both optimisation and simulation approaches have been applied in the dissertation.
Methods include dynamic programming, evolution algorithms, quadratic programming, portfolio
theory and Monte Carlo simulation. A number of models have been used including Markov chains,
binomial distributions, random walks, and vector autoregressive models. The dissertation comprises
four papers. As to the contributions of Paper 1, it is shown how transformation in structure and
species composition can be modelled, including risk of wind throw, at the forest level taking into
account planning resources available to forest managers. Using a specific case, the dependence on
the initial forest structure, when evaluating transformation strategies, was demonstrated.
Furthermore, the economic trade-offs between minimising vulnerability to storm damage and the
fixed costs associated with harvest interventions through the choice of cutting cycle were
demonstrated. The contribution of Paper 2 lies in the demonstration of how expectations on future
knowledge arrival may influence the decisions of a forest manager. This may very well be seen
when dealing with climate change uncertainty, where we suspect that certainty as to the direction of
this change will increase over time, as knowledge is accumulated. The main contribution of Paper 3
lies in the analysis of optimal transformation strategies simultaneously with including climate
change uncertainty represented by changes in growth conditions. Thereby, the potential influence of
such changes can be assessed. Furthermore, it was shown that a good economic result of
transformation may be achieved in several ways. The contribution of Paper 4 lies in the inclusion of
several species in an analysis of risk reduction potentials through species diversification, when riskii
is represented by variation in returns. Furthermore, is it shown how climate change uncertainty may
be incorporated into a model alongside risk of wind throw and price uncertainty – allowing us to
directly analyse risk reducing potentials of diversification under climate chang