Optimizing high and low thinnings in loblolly pine with dynamic programming

Abstract

A four state-descriptor dynamic programming model was used to seek economically optimal thinning regimes for high and low thinning in loblolly pine (Pinustaeda L.). Given the assumptions of the study, low thinning generated higher present values than high thinning. Growth equations were estimated from data generated by a stochastic growth simulator. Reasons for the occurrence of slightly suboptimal solutions are discussed. The paper reviews situations in which the principle of optimality might be violated when thinning problems are being solved with forward recursion dynamic programming.