Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem
management. The maximization of worst-case outcomes according to the “maximin” decision rule, based on
the two parameters mean and variance of a financial indicator, is a prominent approach to integrate
uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination
for a forest plantation investment can be seen as a problem of optimal portfolio selection, to be solved
according to the “maximin” decision rule. Yet, it is well known that portfolios computed from expected
means and variances are highly sensitive to changes in the estimated parameters. The financial results may
be poor if we rely too much on the historical data. This paper tests an extended worst-case model that
considers a lower bound for the expected mean net present value (NPV) of a tree species portfolio and an
upper bound for its variance. Biased expected mean NPVs, variances and correlations for the tree species
Picea abies [L.] Karst. (Spruce) and Fagus sylvatica L. (Beech) were used to test the variability of the resulting
tree species portfolios (27 scenarios). A comprehensive simulated data set, which was adopted from an
existing study and defined as the independent reference, served to evaluate the financial performance of the
tree species portfolios obtained from optimization with the biased data. Compared with the results of
classical worst-case optimization instances, it was feasible to reduce the variability of tree species shares
effectively when the optimization was carried out with the extended worst-case approach. Furthermore, the
financial performance of this approach was better when tested with the independent data. The worst-case
forest NPVs achieved with the extended approach were on average 10% (statistical confidence 0.95) or 147%
(statistical confidence 0.99) greater in comparison to the results of the classical approach. The influence of
the uncertainty parameter selection was tested and the results were discussed against the controversial
viewpoints on the usefulness of the “information-gap decision theory”. Finally, the significance of our results
for sustainable ecosystem management is pointed out.
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Addressing uncertainty is a key requirement to follow the principle of precaution in sustainable ecosystem
management. The maximization of worst-case outcomes according to the “maximin” decision rule, based on
the two parameters mean and variance of a financial indicator, is a prominent approach to integrate
uncertainty in decision-making. In forestry, the problem of selecting the optimum tree species combination
for a forest plantation investment can be seen as a problem of optimal portfoli...
»