RESTORING SUSTAINABLE FORESTS ON APPALACHIAN MINED LANDS FOR WOOD PRODUCTS, RENEWABLE ENERGY, CARBON SEQUESTRATION, AND OTHER ECOSYSTEM SERVICES

Abstract

The overall purpose of this project is to evaluate the biological and economic feasibility of restoring high-quality forests on mined land, and to measure carbon sequestration and wood production benefits that would be achieved from forest restoration procedures. In this quarterly report, we present a preliminary comparison of the carbon sequestration benefits for two forest types used to convert abandoned grasslands for carbon sequestration. Annual mixed hardwood benefits, based on total stand carbon volume present at the end of a given year, range from a minimum of $0/ton of carbon to a maximum of $5.26/ton of carbon (low prices). White pine benefits based on carbon volume range from a minimum of $0/ton of carbon to a maximum of $18.61/ton of carbon (high prices). The higher maximum white pine carbon payment can primarily be attributed to the fact that the shorter rotation means that payments for white pine carbon are being made on far less cumulative carbon tonnage than for that of the long-rotation hardwoods. Therefore, the payment per ton of white pine carbon needs to be higher than that of the hardwoods in order to render the conversion to white pine profitable by the end of a rotation. These carbon payments may seem appealingly low to the incentive provider. However, payments (not discounted) made over a full rotation may add up to approximately $17,493/ha for white pine (30-year rotation), and $18,820/ha for mixed hardwoods (60-year rotation). The literature suggests a range of carbon sequestration costs, from $0/ton of carbon to $120/ton of carbon, although the majority of studies suggest a cost below $50/ ton of carbon, with van Kooten et al. (2000) suggesting a cutoff cost of $20/ton of carbon sequestered. Thus, the ranges of carbon payments estimated for this study fall well within the ranges of carbon sequestration costs estimated in previous studies.