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Local calibration of the Forest Vegetation simulator (FVS) using custom inventory dataAuthor(s): J. D. Shaw; G. Vacchiano; R. J. DeRose; A. Brough; A. Kusbach; J. N. Long
Source: In: Society of American Foresters 2006 National Convention [electronic resource]: Pittsburgh, Pennsylvania, October 25-29. Bethesda, MD: Society of American Foresters, 2006: 10 p.
Publication Series: Miscellaneous Publication
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DescriptionFort Bragg, North Carolina includes over 65,000 acres of longleaf pine forest, which is primary habitat for the endangered red-cockaded woodpecker (RCW). Effective management of the RCW depends on effective management of the longleaf pine forest. However, growth and yield models available in the geographic area that includes Fort Bragg over-predict stand growth and produce unrealistic projections of future stand conditions. Among these models is the Southern Variant of the Forest Vegetation Simulator (FVS), which was developed and is maintained by the USDA Forest Service. The FVS framework covers all forested land in the contiguous 48 states and coastal Alaska, but there is considerable variation in the extent to which the accuracy of regional FVS variants has been tested by local users. While FVS is of limited use on Fort Bragg in its current form, forest managers in the installation recognized the high potential of FVS as a management tool. As a result, a scheduled periodic inventory of Fort Bragg was designed so the data could be used to test and calibrate selected FVS submodels. This paper describes data considerations, evaluation methods, and re-calibration procedures used to produce a "Fort Bragg version" of FVS.
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CitationShaw, J. D.; Vacchiano, G.; DeRose, R. J.; Brough, A.; Kusbach, A.; Long, J. N. 2006. Local calibration of the Forest Vegetation simulator (FVS) using custom inventory data. In: Society of American Foresters 2006 National Convention [electronic resource]: Pittsburgh, Pennsylvania, October 25-29. Bethesda, MD: Society of American Foresters, 2006: 10 p.
KeywordsFVS, simulation, growth models, longleaf pine, model validation
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