Title page for ETD etd-07252007-210531

Type of Document Master's Thesis
Author Herring, Nathan Daniel
Author's Email Address ndh129@vt.edu
URN etd-07252007-210531
Title Sensitivity Analysis of the Forest Vegetation Simulator Southern Variant (FVS-Sn)for Southern Appalachian Hardwoods
Degree Master of Forestry
Department Forestry
Advisory Committee
Advisor Name Title
Radtke, Philip J. Committee Chair
Burkhart, Harold E. Committee Member
Prisley, Stephen P. Committee Member
  • FVS
  • Sensitivity Analysis
  • FVS-Sn
  • response surface
  • error budget
  • Forest Vegetation Simulation
  • Southern Appalachian Hardwoods
Date of Defense 2007-07-18
Availability unrestricted
The FVS-Sn model was developed by the USDA Forest Service to project and report forest growth and yield predictions for the Southern United States. It is able to project forest growth and yield for different forest types and management prescriptions, but it is a relatively new, complex, and untested model. These limitations notwithstanding, FVS-Sn once tested and validated could meet the critical need of a comprehensive growth and yield model for the mixed hardwood forests of the southern Appalachian region.

In this study, sensitivity analyses were performed on the FVS-Sn model using Latin hypercube sampling. Response surfaces were fitted to determine the magnitudes and directions of relationships between FVS-Sn model parameters and predicted 10-year basal area increment. Model sensitivities were calculated for five different test scenarios for both uncorrelated and correlated FVS-Sn input parameters and sub-models.

Predicted 10-year basal area increment was most sensitive to parameters and sub-models related to the stand density index and, to a lesser degree, the large tree diameter growth sub-model. The testing procedures and framework developed in this study will serve as a template for further evaluation of FVS-Sn, including a comprehensive assessment of model uncertainties, followed by a recalibration for southern Appalachian mixed hardwood forests.

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