Site Quality Classification for Mapping Forest Productivity Potential on Mine Soils in the Appalachian Coalfield Region
Jones, Andy Thomas
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Surface mining for coal in the Appalachian region destroys native forests and replaces them with reclaimed landscapes that are often revegetated as grasslands and are unacceptable for managed forest production without extensive remediation. Tree survival and growth are dependent on many reclaimed mine land properties. However, conventional mapping techniques using USDA soil series does not identify these critical soil property differences. This study was conducted to create a forest site quality classification system to be used to evaluate the potential productivity of specific tree species on mine soils. High soil bulk density is the most common limitation on mine soils and methods to efficiently measure this property were evaluated. No valid quantitative method of measuring mine soil bulk density was found due to the high rock fragment content in the soil profile, but a method for estimating relative soil density class was developed. Other soil chemical and physical properties were analyzed at abandoned mine sites in Virginia, West Virginia, and Ohio. Mine soil properties differed throughout the Appalachian region, with Ohio sites having finer textures and less rock fragments, West Virginia sites having coarser textures and a high quantity of dark-colored shale, and Virginia sites dominated by sandstone rock types. Selected field-measured soil and site properties were regressed with site index (SI) base age 50 at 52 sample locations in 10- to 18-year old white pine (Pinus strobus L.) stands on reclaimed mine lands. Sufficiency curves for nine soil and site properties were produced and a general productivity index (PI) calculated. Regression of the general PI and measured SI of white pine produced an R2 of 0.61. The general PI was simplified to four soil properties (soil density, rooting depth, texture, and pH) most significantly related to the SI of white pine, and the properties were weighted based on their importance to white pine growth on mine soils. The modified PI model produced an R2 of 0.69 for a linear relationship between PI and measured SI. The SI values were divided into five classes of equal interval and the corresponding PI values were used to define five forest site quality classes that could be identified by measuring and mapping differences in the PI on older mine soils. The model may be modified for determination of hardwood productivity after validation sites are located. Soil and site properties that are correlated with seedling survival appear different than those properties important for tree productivity. The forest site quality classification system proposed here proved practical for mapping a selected mine site, and the maps may be used as a validation test after future reforestation.
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