English

Abstract

Soils formed on lands mined for coal in the Central Appalachians are currently classified by Soil Taxonomy primarily as Typic Udorthents, which does not distinguish these unique anthropogenic soils from other weakly developed natural soils. In this study, we evaluated the effectiveness of currently utilized mine soil series for describing and classifying a range of mine soil pedons in southwest Virginia. Using established series concepts, we mapped and classified approximately 450 ha of mine soils in an area that had been reclaimed in accordance with the U.S. Surface Mining, Control, and Reclamation Act (SMCRA) of 1977. We also used current series concepts to reclassify mine soils in an adjacent and overlapping 250 ha that had been mined prior to SMCRA, and had been mapped using older (non Soil Taxonomy) mine soil classification criteria in 1980. Established mine soil series concepts provided adequate information on particle-size and reaction class, but did not adequately describe drainage class, rock type or parent materials. Classification differences occurred on well-drained soils primarily at the family level and below. There were no established series to describe mine soils with impeded drainage, densic layers, and shallow or moderately deep depth classes, all of which commonly occurred in this study area, and are important criteria for separating soil series. Cambic horizons were also described, and generate classification issues at the order level. Using current taxonomic/mapping procedures, none of these dissimilar soils would be considered limiting inclusions to the dominant soil in the map unit. Since reaction class, drainage class, densic contacts, and soil depth directly affect soil management, we feel that it is important to recognize these features by establishing new mine soil series or phases of established series. Older, pre-SMCRA mined lands are much more complex in short-range landform variability than more modern reclaimed landscapes. This pattern of soil landscape variability and associated differences in land use capability is effectively captured by large scale mapping such as that employed by this study.