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| We develop a modelling concept that updates
knowledge and beliefs about future climate changes, to model
a decision-maker’s choice of forest management alternatives,
the outcomes of which depend on the climate condition.
& Aims Applying Bayes’ updating, we show that while the
true climate trajectory is initially unknown, it will eventually
be revealed as novel information become available. How fast
the decision-maker will form firm beliefs about future climate
depends on the divergence among climate trajectories, the
long-term speed of change, and the short-term climate
variability.
& Methods We simplify climate change outcomes to three
possible trajectories of low, medium and high changes. We
solve a hypothetical decision-making problem of tree species
choice aiming at maximising the land expectation value
(LEV) and based on the updated beliefs at each time step.
& Results The economic value of an adaptive approach would
be positive and higher than a non-adaptive approach if a large
change in climate state occurs and may influence forest
decisions.
& Conclusion Updating knowledge to handle climate change
uncertainty is a valuable addition to the study of adaptive forest
management in general and the analysis of forest decisionmaking,
in particular for irreversible or costly decisions of
long-term impact. | |
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