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Profitability potential for Pinus taeda L. (loblolly pine) short-rotation bioenergy plantings in the southern USA
- Perdue, James H., Stanturf, John A., Young, Timothy M., Huang, Xia, Dougherty, Derek, Pigott, Michael, Guo, Zhimei
- Forest policy and economics 2017 v.83 pp. 146-155
- Pinus taeda, bioenergy, coasts, crops, economic feasibility, economic sustainability, feedstocks, geographic information systems, growth models, highlands, lowlands, plantations, profitability, site preparation, upland soils, Alabama, Florida, Georgia, Louisiana, North Carolina, South Carolina, Texas, Virginia
- The use of renewable resources is important to the developing bioenergy economy and short rotation woody crops (SRWC) are key renewable feedstocks. A necessary step in advancing SRWC is defining regions suitable for SRWC commercial activities and assessing the relative economic viability among suitable regions. The goal of this study was to assess the potential profitability, based on obtainable yield and economic feasibility; of Pinus taeda L. (loblolly pine) across 13 states of the southern USA. A process-based growth model, 3PG, produced estimated yields of P. taeda in terms of mean annual increment (MAI) that were evaluated as internal rate of return on investment (IRR) and land expectation value (LEV). Coastal areas (southeast Texas, southwest Louisiana, and northern Florida) have the highest potential MAI production ranging from 13.7 to 18.9Mgha−1yr−1. LEVs ranged from −1126 to 3111$ha−1 on upland sites and −2261 to 2341$ha−1 on lowland sites. IRR ranged from −0.3% to 14.2% on uplands and −2.9% to 10.4% on lowlands. On soils of the same textural class, LEV and IRR were higher on uplands relative to lowlands given lower site preparation costs, although the projected yield from upland soils are generally lower than those from lowland soils. The highest LEV and IRR were in northern Florida, southern Alabama, southern Georgia, and southern South Carolina. The lowest LEV and IRR were in Virginia and northern North Carolina. Spatially categorizing suitable lands in biological and economic terms can use geographic information system technology to advantage in combination with societal considerations to begin to answer sustainability questions as well as identify suitable sites for bioenergy plantations.