Modeling Stem Taper of Southern Appalachian Red Spruce

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Date

2023-05-24

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Virginia Tech

Abstract

Red spruce (Picea rubens Sarg.) is a commercially and ecologically important conifer species that primarily exists at northern latitudes of eastern North America. During the last glaciation, its range extended down the Appalachian Mountain chain into North Carolina and Tennessee. Since the planet warmed over the subsequent millennia, only small, sky-island populations remain at the highest peaks of the southern Appalachians where their habitat continues to be threatened by a warming climate. While they have been recognized for the rare wildlife habitat they provide in the region, these populations remain understudied. This thesis aimed to provide additional quantitative methods for managing red spruce stands through regionally fitted stem taper equations and to examine differences in stem form between the northern and southern populations of red spruce. In Chapter 1, five stem taper equations were evaluated for their ability to predict upper stem diameters and total volume in southern Appalachian red spruce: a simple linear, a quadratic polynomial, a segmented, a variable exponent, and a geometric model. Based on past studies and our results, we found that the best equations to use were the variable exponent and segmented polynomial models. Users should consider their own objectives and practical limitations in choosing which equation to use. In Chapter 2, we examined differences in stem form using three methods: a sectional rate of change in diameter, a sectional form class ratio, and a region variable added to two taper equations. The results were mixed, with the rates of change showing significant differences (p<0.05), but the form class ratios showing a mix of significant and insignificant differences. The two equations also had contrasting significance results. This made it unclear whether there were significant differences in stem form between the two populations but supported the idea that localized taper equations would provide the best results.

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Keywords

spruce, stem, taper, biometrics, picea rubens, regression, modeling, forestry, appalachia, southern, diameter, volume

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