Determining the optimal planting density and land expectation value - A numerical evaluation of decision model

Abstract

Different decision models can be constructed and used to analyze a regeneration decision in even-aged stand management. However, the optimal decision and management outcomes determined in an analysis may depend on the decision model used in the analysis. This paper examines the proper choice of decision model for determining the optimal planting density and land expectation value (LEV) for a Scots pine (Pinus sylvestris L.) plantation in northern Sweden. First, a general adaptive decision model for determining the regeneration alternative that maximizes the LEV is presented. This model recognizes future stand state and timber price uncertainties by including multiple stand state and timber price scenarios, and assumes that the harvest decision in each future period will be made conditional on the observed stand state and timber prices. Alternative assumptions about future stand states, timber prices, and harvest decisions can be incorporated into this general decision model, resulting in several different decision models that can be used to analyze a specific regeneration problem. Next, the consequences of choosing different modeling assumptions are determined using the example Scots pine plantation problem. Numerical results show that the most important sources of uncertainty that affect the optimal planting density and LEV are variations of the optimal clearcut time due to short-term fluctuations of timber prices. It is appropriate to determine the optimal planting density and harvest policy using an adaptive decision model that recognizes uncertainty only in future timber prices. After the optimal decisions have been found, however, the LEV should be re-estimated by incorporating both future stand state and timber price uncertainties.