Bootstrap Simulation, Markov Decision Process Models, and Role of Discounting in the Valuation of Ecological Criteria in Uneven-Aged Forest Management

Abstract

This chapter presents general methods combining stochastic simulation and Markov decision process models, with a specific application to the issue of discounting ecological criteria. The literature argues for and against discounting ecological costs and benefits like standard financial investments. As part of this debate, this chapter investigates some purely ecological consequences of discounting ecological criteria. The methods are Markov decision process models with infinite time horizon and discounted or undiscounted ecological objectives, based on bootstrap simulations of stand growth. The data were from Douglas-fir/western hemlock forests in the U.S. Pacific Northwest, with the assumption of continuous-cover forestry. The ecological criteria examined here included the stand basal area per hectare, the tree species and size diversity measured with Shannon’s index, and the percentage of the forest in late seral stage. In maximizing expected tree species diversity, 18 out of 64 possible stand states would call for different decisions with discounting. For tree size diversity, the decisions differed for five stand states. For basal area all but two states called for the same decision. For late seral forest frequency, discounting led to different decisions for 13 stand states. However, for only a few stand states were the ecological criteria substantially different immediately after harvest. Thus, discounting would matter only for a few stand states, which in the study area had a low frequency. Given this initial condition, only the expected late seral forest frequency differed substantially after a decade with discounting. In the long run, the initial condition does not matter and discounting the criteria gave very similar values as not discounting.