Assessing uncertainty in a stand growth model by Bayesian synthesis

Edwin J. Green, David W. MacFarlane, Harry T. Valentine, William E. Strawderman

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)528-538
Number of pages11
JournalForest Science
Volume45
Issue number4
StatePublished - Nov 1999

All Science Journal Classification (ASJC) codes

  • Forestry
  • Ecology
  • Ecological Modeling

Keywords

  • Confidence intervals
  • Loblolly pine
  • Mechanistic models
  • Posterior distributions

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