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Formulating a stand-growth model for mathematical programming problems in Appalachian forestsAuthor(s): Gary W. Miller; Jay Sullivan
Source: In: Gillespie, Andrew R.; Parker, George R.; Pope, Phillip E.; Rink, George: eds. Proceedings of the 9th Central Hardwood Forest Conference; Gen. Tech. Rep. NC-161. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station: 353-362
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
PDF: Download Publication (1.72 MB)
DescriptionSome growth and yield simulators applicable to central hardwood forests can be formulated for use in mathematical programming models that are designed to optimize multi-stand, multi-resource management problems. Once in the required format, growth equations serve as model constraints, defining the dynamics of stand development brought about by harvesting decisions. In large models representing forests with varying cover types equations from several unique simulators can be combined to account for individual stand growth. The inclusion of appropriate growth functions greatly enhances the validity and scope of management guidelines generated by optimization routines. Although several growth models are available for Appalachian hardwoods, few have been formulated to serve as inputs to such analytical models. Methods for formulating nonlinear growth constraints for a two-stage matrix simulator used in certain Appalachian hardwood stands are demonstrated. A generalized growth constraint is presented that may be indexed by size class, species group, and stand for sizable management problems.
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CitationMiller, Gary W.; Sullivan, Jay. 1993. Formulating a stand-growth model for mathematical programming problems in Appalachian forests. In: Gillespie, Andrew R.; Parker, George R.; Pope, Phillip E.; Rink, George: eds. Proceedings of the 9th Central Hardwood Forest Conference; Gen. Tech. Rep. NC-161. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station: 353-362
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