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Background: The negative impacts of the exotic tree, Ailanthus altissima (tree-of-heaven, stink tree), is spreading throughout much of the Eastern United States. When forests are disturbed, it can invade and expand quickly if seed sources are nearby. Methods: We conducted studies at the highly dissected Tar Hollow State Forest (THSF) in southeastern Ohio USA, where Ailanthus is widely distributed within the forest, harvests have been ongoing for decades, and prescribed fire had been applied to about a quarter of the study area. Our intention was to develop models to evaluate the relationship of Ailanthus presence to prescribed fire, harvesting activity, and other landscape characteristics, using this Ohio location as a case study. Field assessments of the demography of Ailanthus and other stand attributes (e.g., fire, harvesting, stand structure) were conducted on 267 sample plots on a 400-m grid throughout THSF, supplemented by identification of Ailanthus seed-sources via digital aerial sketch mapping during the dormant season. Statistical modeling tools Random Forest (RF), Classification and Regression Trees (CART), and Maxent were used to assess relationships among attributes, then model habitats suitable for Ailanthus presence. Results: In all, 41 variables were considered in the models, including variables related to management activities, soil characteristics, topography, and vegetation structure (derived from LiDAR). The most important predictor of Ailanthus presence was some measure of recent timber harvest, either mapped harvest history (CART) or LiDARderived canopy height (Maxent). Importantly, neither prescribed fire or soil variables appeared as important predictors of Ailanthus presence or absence in any of the models of the THSF. Conclusions: These modeling techniques provide tools and methodologies for assessing landscapes for Ailanthus invasion, as well as those areas with higher potentials for invasion should seed sources become available. Though a case study on an Ohio forest, these tools can be modified for use anywhere Ailanthus is invading.

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. During the reporting period (October-December 2004) we completed the validation of a forest productivity classification model for mined land. A coefficient of determination (R 2 ) of 0.68 confirms the model's ability to predict SI based on a selection of mine soil properties. To determine carbon sequestration under different forest management scenarios, a field study was installed as a 3 x 3 factorial in a random complete block design with three replications at each of three locations, Ohio (Figure 1), West Virginia (Figure 2), and Virginia (Figure 3). The treatments included three forest types (white pine, hybrid poplar, mixed hardwood) and three silvicultural regimes (competition control, competition control plus tillage, competition control plus tillage plus fertilization). For hybrid poplar, total plant biomass differences increased significantly with the intensity of silvicultural input. Root, stem, and foliage biomass also increased with the level of silvicultural intensity. Financial feasibility analyses of reforestation on mined lands previously reclaimed to grassland have been completed for conversion to white pine and mixed hardwood species. Examination of potential policy instruments for promoting financial feasibility also have been completed, including lump sum payments at time of conversion, annual payments through the life of the stand, and payments based on carbon sequestration that provide both minimal profitability and fully offset initial reforestation outlays. We have compiled a database containing mine permit information obtained from permitting agencies in

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.4

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. We are currently estimating the acreage of lands in VA, WV, KY, OH, and PA mined under SMCRA and reclaimed to non-forested post-mining land uses that are not currently under active management, and therefore can be considered as available for carbon sequestration. To determine actual sequestration under different forest management scenarios, a field study was installed as a 3 x 3 factorial in a random complete block design with three replications at each of three locations, Ohio (Figure 1), West Virginia (Figure 2), and Virginia (Figure 3). The treatments included three forest types (white pine, hybrid poplar, mixed hardwood) and three silvicultural regimes (competition control, competition control plus tillage, competition control plus tillage plus fertilization). Each individual treatment plot is 0.5 acres. Each block of nine plots requires 4.5 acres, and the complete installation at each site requires 13.5 acres. The plots at all three locations have been installed and the plot corners marked with PVC stakes. GPS coordinates of each plot have been collected. Tree survival, height and diameter were measured after the first growing season. There were significant treatment and treatment x site interactions. A STELLA ® -based model helped us develop insight as to whether it is possible to differentiate the permanent SOC from the C contained in the labile forms of SOM. The model can be used for predicting the amount of C sequestered on mine lands, and the amount of C that is expected to reside in the mine soil for more than 1,000 years. Based on our work, it appears that substantial carbon payments to landowners would be required to reach "profitability" under present circumstances. However, even though the payments that we examine could generate non-negative LEVs, there is no guarantee that the payments will actually cause landowners to reforest in practice. It is landowner utility associated with forestland profitability that will be the determining factor in actual conversion-utility that likely would include cash flow timing, amenities, and even the credit position of the landowner.4