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

Abstract

The longleaf pine (Pinus palustris P. Mill.) forest type occupied a much greater area in the United States prior to the arrival of Europeans, estimated to be around 37.2 million hectares. This area has been greatly reduced, and these ecosystems now occupy only about 1.2 to 1.6 million hectares. However, there has been a great interest in the restoration of this forest type mainly due to concerns about the loss of ecosystem services associated with these forests; the improved seedling quality and yield potentials bolster those efforts. Beyond that, existing stands are actively managed through different types of practices, including thinnings, prescribed burns often to manipulate the vegetation of other species, and the various timings of clearcuts. Thus, managers need tools to estimate site quality and ultimately productivity. A commonly used measure of site quality is site index, or the height of some defined dominant portion of the stand at a standardized base or index age. The primary objectives are to summarize the 16 existing equations to estimate site index and dominant height in naturally regenerated longleaf pine stands and to examine and visually compare their predicted behavior across a range of site quality and age conditions. Important considerations when using site index of anamorphism and polymorphism as well as base-age invariance are reviewed. Biologically, polymorphism is often considered advantageous since for many species differences in site quality not only result in different asymptotic dominant heights, but also varying rates in their approach to the asymptote. Of the 16 equations examined, only nine of them were polymorphic in nature, but all equations were base-age invariant. There is not an individual equation that is clearly superior because, for instance, it is either anamorphic in nature, is polymorphic but developed based on anamorphic curves, fit using data obtained from temporary plots, or it is limited geographically. Given these limitations, others can use this publication as a reference to determine which equation they feel is best for their particular situation.