Masters Theses
Date of Award
5-2023
Degree Type
Thesis
Degree Name
Master of Science
Major
Forestry
Major Professor
Sheng-I Yang
Committee Members
Consuelo Brandeis, Donald Hodges
Abstract
The Forest Inventory and Analysis (FIA) conducts Timber Products Output (TPO) studies to assess timber resource use across the United States. The TPO studies gather information through surveys of primary wood processing facilities to quantify the utilization of roundwood by geographic location, tree species, and timber product type. However, not all responding mills provide information on tree species utilized. As a result, a portion of the reported volume falls into the “unknown/unclassified” softwood or hardwood category, which account for up to 74% of total hardwood/softwood southern volumes in some cases. In addition, the detailed species in the TPO survey forms do not correspond with those species reported. To correct the issue, southern TPO allocates the by-species volume by using the species proportion generated from the average annual harvest removals in FIA inventory.
The purposes of this study were to (1) quantify the differences of by-species volumes between the mill survey and current methodology, and (2) evaluate alternative data selection methodologies to estimate species proportions across the southern states for sawlogs and other products. Large differences exist for some tree species, states, and years when comparing the species proportions reported by mills and estimated using the current methodology. All alternative methodologies provided improvements for varying product classes, but none of the alternatives showed enough improvement for sawlogs to justify switching the current methodology. The findings of this study provide insights on the current methodology in producing by-species volumes and can subsequently be applied to evaluate future methods in TPO.
Recommended Citation
Skiba, Tara, "Exploring alternative methodologies to estimate by-species sawlog volume in the southeastern United States. " Master's Thesis, University of Tennessee, 2023.
https://trace.tennessee.edu/utk_gradthes/9220