Predicting Forest Regeneration in the Central Appalachians Using the REGEN Expert SystemAuthor(s): Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani
Source: Journal of Sustainable Forestry 30:790–822
Publication Series: Scientific Journal (JRNL)
Station: Southern Research Station
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DescriptionREGEN is an expert system designed by David Loftis to predict the future species composition of dominant and codominant stems in forest stands at the onset of stem exclusion following a proposed harvest. REGEN predictions are generated using competitive rankings for advance reproduction along with other existing stand conditions. These parameters are contained within modular REGEN knowledge bases (RKBs). To extend REGEN coverage into hardwood stands of the Central Appalachians, RKBs were developed for four site classes (xeric, subxeric, submesic, mesic) based on literature and expert opinion. Data were collected from 48 paired stands in Virginia and West Virginia to calibrate the initial RKBs.
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CitationVickers, Lance A.; Fox, Thomas R.; Loftis, David L.; Boucugnani, David A. 2011. Predicting Forest Regeneration in the Central Appalachians Using the REGEN Expert System. Journal of Sustainable Forestry 30:790–822.
Keywordshardwoods, Virginia, West Virginia, clear-cutting, harvesting, regeneration model, silviculture, species composition, oak, forest management, sustainable
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