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UNDERSTANDING HARVEST UTILIZATION RATES AND STRATEGIES FOR ENHANCED VALUE RECOVERY DURING PRIMARY PROCESSING IN THE CENTRAL APPALACHIAN REGION Shawn T Grushecky West Virginia has an abundant forest resource base that has underpinned portions of its economy for decades. These forests support a diverse primary and secondary forest products industry. A common thread that ensures the continued success of the forest industry, from the private landowners to the manufactures of fine furniture, is the strength of the logging and primary processing components of this supply chain. The purpose of this research is to evaluate the use of raw materials on logging operations, to understand the financial and operational aspects related to pulpwood merchandising, and to investigate new strategies for the development of standard hardwood log grades. Whole-tree and landing-based utilization rates were determined from data collected on 30 active logging jobs in West Virginia during 2008. Utilization is defined as the amount of volume that is delivered to market over the total volume harvested for individual tree stems. On average, 3.6 markets were used by the loggers sampled. The average whole-tree utilization rate in the woods was 88% and was over 97% on the landings sampled. No relationship between the number of markets and utilization rate was determined. Results from this study provide estimates on the efficiency of forest resource use as well as the characteristics and quantity of material being left after harvest. Roundwood merchandising operations have been seen as a potential way to supply raw materials to bioenergy facilities at competitive costs. The feasibility of developing such a facility in the central Appalachians was investigated. The purchase and subsequent merchandising of over 188 tons of hardwood pulpwood resulted in negative net revenues for all species studied. Handling cost was one of the largest contributing factors. As markets and pricing change, the metrics developed in this analysis can be used to produce new estimates of merchandising profitability. Hardwood sawlog yield information is an important component that helps define hardwood sawmill profitability. This research investigated the use of cluster analyses and ordinal logistic regression in segregating red oak sawlogs based on potential revenue. A combination of statistical classification and an applied approach was found to be the best method for developing log grades. The final log grading table presented is not without problem; however it is the first comprehensive investigation of log grades in over 45 years and will help to begin the dialogue towards the development of a standardized hardwood log grading system.

Harvest utilization rates and strategies for enhanced value recovery during primary processing in the central appalachian region