A Site-Index Function for Naturally Regenerated Longleaf Pine in the East Gulf Area

Abstract

A site-index function is presented for naturally regenerated stands of longleaf pine (Pinus palustris Mill.) in the East Gulf area. The equation resulted in minimum average differences in consecutive site-index estimates five years apart in 170 stands, when compared to two equations currently in use.

Longleaf Pine Characteristics Associated with Arthropods Available for Red-Cockaded Woodpeckers

“…Site index is a measure of the quality of a site for growing trees using tree height at given ages as indicators (Avery 1975). Tree height was measured with a clinometer and used in conjunction with tree age to estimate site index using Farrar's (1981) equation when age was 230 years. When age was <30 we used Schumacher and Coile's (1960) equation for longleaf pine.…”

Currently Available Site Index Equations That Use On-Site Tree Measurements for Naturally Regenerated Longleaf Pine in Its Historical Range

“…This usually results from factors such as harvesting costs are not justified on lower quality sites or silvicultural investment was made in other more inherently productive stands [16,18]. An example can be seen in Table 1 of [19] where only 2 sites were used in equation fitting of ages 71-90 years for site indexes of 76-85 feet (23.2 m to 25.9 m, base age 50 years), and none were used for site indexes of 86-95 feet (26.2 m to 29.0 m). There were a total of 38 observations for ages 71-90 years, and hence the "section" of curves for those ages are from lower quality sites.…”

“…All equations are base age invariant, and although in many ways anamorphic curves do not adequately represent the biological height patterns of naturally regenerated longleaf stands, anamorphic curves have the advantage of being base age invariant. Equations [5] through [13] were developed using the same naturally regenerated dataset established in the states of Alabama, Florida, Georgia, and Mississippi [19], commonly referred to as the Regional Longleaf Pine Growth Study (RLGS). Farrar (1981, [19]) produced initial curves using this dataset with a 4th degree polynomial equation form, fit using weighted least squares with the inverse of age 2 as the weight.…”

“…It does not appear that serial correlation was accounted for. When using additional data beyond that used by [19], [21] updated his fourth-degree polynomial equation, and fit a second-degree polynomial equation and a Chapman-Richards equation. Ordinary least squares was used, and serial correlation was not accounted for.…”

“…For the RLGS dataset, different equations not only resulted from updated datasets, but also the selection of different functional forms. Carmean et al (1989, [14]) took the equation from [19] and produced a polymorphic site index equation of the Chapman-Richards form. A different weighting approach from [19] was used by [14] when estimating parameters for the site index equation.…”