Optimal forest harvest decisions: A stochastic dynamic programming approach

Abstract A method is presented for determining optimal economic strategies for density management in loblolly pine stands in the southern United States. A stochastic dynamic programming model employs a price state transition matrix constructed using time-series data for National Forest pine stumpage in the South. The model also incorporates WTHIN, a pine growth and yield simulator widely used in the South to support economic analyses of stand management alternatives. Results indicate that optimal net present values associated with management strategies determined for the stochastic model (relative to a deterministic equivalent) are higher due to differences in the thinning and final harvest decisions recommended by the two models.