Control function optimization for stochastic continuous cover forest management

Abstract

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