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Estimating maximum stand density for mixed-hardwood forests among various physiographic zones in the eastern US

Formally Refereed
Download (PDF 1.77 MB): https://research.fs.usda.gov/download/treesearch/64668.pdf

Abstract

Quantifying maximum stand density is important to evaluate the potential stand density of the target populationin forest management. However, most of the past research in the eastern US was mainly focused on plantedmonocultures, coniferous forests, a few commercially important species at the stand level, or in a particulargeographic region. This study aimed to estimate the maximum stand density for mixed-hardwood forests acrossphysiographic zones in the eastern US between two decades (1996-2009 and 2010-2021). Data used in analyseswere collected from the US national forest inventory established and maintained by the USDA Forest Service’sForest Inventory and Analysis (FIA) program.Results showed that the slope of the self-thinning lines varied among forest types. Estimating maximum standdensity index (SDImax) from size-density relationships produced more precise estimates than using SDI-sizecurves. Among all forest types, elm-ash-cottonwood (Ulmus-Fraxinus-Populus) showed consistent SDImax estimateswhereas other forest types varied by regions. New England had considerably higher SDImax in aspen-birch(Populus-Betula), oak-hickory (Quercus-Carya) and oak-pine (Quercus-Pinus) forests than other physiographiczones. Most of the combinations showed consistent SDImax between two time periods. Only six combinationsshowed a significant gain (4-14% increase), which was likely driven by the growth of the same dominant speciesgroups. The findings of this work provided not only additional insights of maximum stand density in the region,but also a methodology for forest ecologists and managers to quantify SDImax for a variety of forest types.

Citation

Yang, Sheng-I; Brandeis, Thomas J. 2022. Estimating maximum stand density for mixed-hardwood forests among various physiographic zones in the eastern US. Forest Ecology and Management. 521(2): 120420-. https://doi.org/10.1016/j.foreco.2022.120420.
Citations