Economically optimal management of continuous cover forests can be obtained via a new approach to adaptive control function optimization. We maximize our objective function, the expected present value, with consideration of stochastic prices, timber quality variations and dynamically changing spatial competition. The parameters of the control function are optimized via the first order optimum conditions based on a multivariate polynomial approximation of the objective function. The second order maximum conditions are investigated and used to determine relevant parameter ranges. The procedure is described and optimal results are derived for general function multi species CCF forests. A numerically specified model with empirical data showed that if the stochastic price variations are not considered when the harvest decisions are taken, the expected present value is reduced by 23%.
The analysis in this paper shows that the fundamental theory of the CO 2 level in the atmosphere, under the influence of changing CO 2 emissions, can be modeled as a first order linear differential equation with a forcing function, describing industrial emissions.Observations of the CO 2 level at the Mauna Loa CO 2 observatory and official statistics of global CO 2 emissions, from Edgar, the Joint Research Centre at the European Commission, are used to estimate all parameters of the forced CO 2 differential equation.
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