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Empirically Derived Optimal Growth Equations For Hardwoods and Softwoods in ArkansasAuthor(s): Don C. Bragg
Source: Gen. Tech. Rep. SRS–48. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 421-424
Publication Series: Miscellaneous Publication
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DescriptionAccurate growth projections are critical to reliable forest models, and ecologically based simulators can improve siivicultural predictions because of their sensitivity to change and their capacity to produce long-term forecasts. Potential relative increment (PRI) optimal diameter growth equations for loblolly pine, shortleaf pine, sweetgum, and white oak were fit to data from the Arkansas portion of the Eastwide Forest Inventory Data Base (EFIDB). Large sample sizes are necessary for successful application of the PRI mathodology, and in aggregate almost 29,000 trees were used to develop these models, In the final model versions, only a handful (< 30 per species) of the fastest growing trees given their species, size, and growing conditions were retained from the Arkansas EFIDB. Shortleaf pine, sweetgum, and white oak all generated skewed model curves, while loblolly pine produced a monotonically declining curve. Comparison of these optimal increment models across tree size indicated that loblolly pine had higher potential than the other species until -10 cm in diameter at breast height (d.b.h.), after which sweetgum and white oak overtook it at intermediate sizes. However, loblolly pine optimal performance decreased at a lesser rate than any of the other species, so that by 60cm d.b.h. it once again had the greatest potential. The other taxa outperformed shortleaf pine throughout most of the diameter range considered, while sweetgum proved intermediate between shortleaf and white oak. These optimal diameter functions are a valuable first step in the development of forest simulators.
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CitationBragg, Don C. 2002. Empirically Derived Optimal Growth Equations For Hardwoods and Softwoods in Arkansas. Gen. Tech. Rep. SRS–48. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 421-424
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