Estimates of the distributions of forest ecosystem model inputs for deciduous forests of eastern North America

P. J. Radtke, T. E. Burk, P. V. Bolstad

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Techniques for evaluating uncertainties in process-based, computer simulation models are evolving in response to the proliferation of such models and the demand for their use in the management of forest ecosystems. Many evaluation techniques require precise statements of the uncertainties associated with each model input. Statements of uncertainty are typically formulated as probability density functions (pdfs). Here, pdfs are developed for 29 inputs of the process-based, forest ecosystem, computer simulation model PnET-II, many of which are inputs to other well-known forest ecosystem models. The inputs considered describe vegetation characteristics of forests typical of the Eastern Deciduous Forest biome of North America. Data were compiled largely from published literature to estimate pdfs. The compiled distributions can be used to conduct various model evaluations including uncertainty assessment, calibration, and sensitivity analysis.

Original languageEnglish (US)
Pages (from-to)505-512
Number of pages8
JournalTree physiology
Volume21
Issue number8
DOIs
StatePublished - Jan 1 2001

Keywords

  • BGC
  • Bayesian melding
  • Big leaf model
  • Calibration
  • Model evaluation
  • PnET
  • Process model
  • Sensitivity analysis

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