Stochastic Dynamic Optimization for Forest Rotation with Uncertain Stumpage Prices

This study investigates the effect of uncertain stumpage prices on the optimal forest rotation decision and related profitability under various silvicultural scenarios. The study applies loblolly pine (Pinus taeda L.) growth and yield models with distinct silvicultural scenarios in the Piedmont and Upper Coastal Plain region of the southeastern United States. It then applies chance-constrained dynamic optimization to derive optimal rotation age and related profitability on per acre basis. The growth and yield models show that using a combination of herbicide and fertilizer silvicultural treatment leads to a higher timber yield and profit at a lower optimal rotation age than other treatment scenarios. Furthermore, the stochastic optimization model shows that low risk tolerance results in low returns. Within a particular risk tolerance level, silvicultural treatment options with higher standard deviations almost always produce higher returns. The findings of this article contribute to the literature on optimizing forest management when considering uncertain stumpage prices over time, given different risk tolerance levels. Study Implications: This study applies a stochastic dynamic mathematical programming method to evaluate the impact of uncertain stumpage prices on the optimal forest rotation decision and related profitability under different silvicultural and risk preference scenarios. The implication of this model demonstrates a tradeoff between maximizing average returns and minimizing the uncertainty of returns. The results suggest a risk-averse landowner would likely wait longer to realize greater sawtimber yield to assure a positive profit as sawtimber is the most valuable timber relative to the other two products considered, chip-N-saw and pulpwood.