Graduate Thesis Or Dissertation

The valuation and use of site information for Douglas-fir reforestation in Western Oregon : a decision analysis

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  • Existing forest site maps have been described as "invaluable tools" in forest management. Their, economic value potentially materializes as the summed advantage from better decisions in all phases of forestry. Via Bayesian decision analysis, this study establishes optimal use and economic value of site information for one facet of management only: The choice of an optimal planting density in Douglas-fir reforestation. Two case studies were undertaken in extremely different environments of Southwestern and Northwestern Oregon. The prior analysis is based on a review of existing ref3restation records and a simulation model. Optimal prior acts differ substantially from present policies. Their implementation may reduce expected costs by approximately $50 per acre. Based on ecological variables observed an 350 survival plots, prediction aids for first-year survival arid site class, the main sources of uncertainty,are established. Plant water relations, and particularly the available water capacity of soils, emerge as prime determinants of survival and productivity. During preposterior analysis, Bayes' strategy translates ecological knowledge directly into optimal managerial choices for specific site units. Site information is evaluated economically, based on prospective reduction of reforestation costs. Expected values of site information are relatively low and almost identical in both ownerships. In the Northwestern Oregon study, it is a rather uniform environment for reforestation which limits the value of information. In the very diverse environment of the Southwestern Oregon ownership, lower marginal costs for plantation establishment, and smaller opportunity losses set these limits. A larger potential value of site information is likely for activities with high marginal costs in Southwestern Oregon. Bayesian decision analysis emphasizes the duality of ecology and economics in forest management. Combined with a system of collecting and analyzing operational records, it resembles a traditional forestry approach to uncertainty: Biolley's control method. As an extended, economically, statistically and computationally refined equivalent of the control method, Bayesian decision analysis deserves a place in the theory of forestry and in practical management of our forests.
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