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Assessing Uncertainty in a Stand Growth Model by Bayesian Synthesis

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Abstract:

The Bayesian synthesis method (BSYN) was used to bound the uncertainty in projections calculated with PIPESTEM, a mechanistic model of forest growth. The application furnished posterior distributions of (a) the values of the model's parameters, and (b) the values of three of the model's output variables--basal area per unit land area, average tree height, and tree density--at different points in time. Confidence or credible intervals for the output variables were obtained directly from the posterior distributions. The application also provided estimates of correlation among the parameters and output variables. BSYN, which originally was applied to a population dynamics model for bowhead whales (Raftery et al. 1996, JASA 90:402-442), is generally applicable to deterministic models. Extension to two or more linked models is discussed. A simple worked example is included in an appendix. For. Sci. 45(4):528-538.

Keywords: Loblolly pine; confidence intervals; mechanistic models; posterior distributions

Document Type: Journal Article

Affiliations: Professor, Department of Statistics, Rutgers University, 110 Frelinghuysen Road, Piscataway, NJ 08854

Publication date: November 1, 1999

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