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  1. Predicting the regeneration of Appalachian hardwoods: adapting the REGEN model for the Appalachian Plateau

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    Author(s): Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani
    Date: 2013
    Source: In: Guldin, James M., ed. 2013. Proceedings of the 15th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-GTR-175. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 277-280.
    Publication Series: Paper (invited, offered, keynote)
    Station: Southern Research Station
    PDF: Download Publication  (43.96 KB)
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    Description

    The difficulty of achieving reliable oak (Quercus spp.) regeneration is well documented. Application of silvicultural techniques to facilitate oak regeneration largely depends on current regeneration potential. A computer model to assess regeneration potential based on existing advanced reproduction in Appalachian hardwoods was developed by David Loftis of the U.S. Forest Service, Bent Creek Experimental Forest. REGEN is a competition-based, expert system which predicts dominant and codominant species composition at the onset of stem exclusion. A knowledge base containing competitive rankings for each species and size combination of advance reproduction is used to make predictions. REGEN was initially developed for hardwood forests in the Blue Ridge Physiographic Province of the Southern Appalachians and is only applicable for predicting regeneration following a heavy disturbance, such as a clearcut. We have developed preliminary REGEN knowledge bases for hardwood forests in the Appalachian Plateau Province.

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    Citation

    Vickers, Lance A.; Fox, Thomas R.; Loftis, David L.; Boucugnani, David A. 2013. Predicting the regeneration of Appalachian hardwoods: adapting the REGEN model for the Appalachian Plateau. In: Guldin, James M., ed. 2013. Proceedings of the 15th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-GTR-175. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 277-280.

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