Title: Predicting Forest Regeneration in the Central Appalachians Using the REGEN Expert System
Author: Vickers, Lance A.; Fox, Thomas R.; Loftis, David L.; Boucugnani, David A.;
Source: Journal of Sustainable Forestry 30:790–822
Publication Series: Scientific Journal (JRNL)
Description: REGEN 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.
Keywords: hardwoods, Virginia, West Virginia, clear-cutting, harvesting, regeneration model, silviculture, species composition, oak, forest management, sustainable
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
XML: View XML
Vickers, 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.
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility