Soil biochemical properties in brown and gray mine soils with and without hydroseeding

Surface coal mining in the eastern USA disturbs hundreds of hectares of land every year and removes valuable and ecologically diverse eastern deciduous forests. Reclamation involves restoring the landscape to approximate original contour, replacing the topsoil, and revegetating the site with trees and herbaceous species to a designated post-mining land use. Re-establishing an ecosystem of ecological and economic value as well as restoring soil quality on disturbed sites are the goals of land reclamation, and microbial properties of mine soils can be indicators of restoration success. Reforestation plots were constructed in 2007 using weathered brown sandstone or unweathered gray sandstone as topsoil substitutes to evaluate tree growth and soil properties at Arch Coal\u27s Birch River mine in West Virginia, USA. All plots were planted with 12 hardwood tree species and subplots were hydroseeded with a herbaceous seed mix and fertilizer. After 6 years, the average tree volume index was nearly 10 times greater for trees grown in brown (3853 cm3) compared to gray mine soils (407 cm3). Average pH of brown mine soils increased from 4.7 to 5.0, while gray mine soils declined from 7.9 to 7.0. Hydroseeding doubled tree volume index and ground cover on both mine soils. Hydroseeding doubled microbial biomass carbon (MBC) on brown mine soils (8.7 vs. 17.5 mg kg−1), but showed no effect on gray mine soils (13.3 vs. 12.8 mg kg−1). Hydroseeding also increased the ratio of MBC to soil organic C in both soils and more than tripled the ratio for potentially mineralizable nitrogen (PMN) to total N. Brown mine soils were a better growth medium than gray mine soils and hydroseeding was an important component of reclamation due to improved biochemical properties and microbial activity in mine soils

Effects of Shovel Logging and Rubber-tired Skidding on Surface Soil Attributes in a Selectively Harvested Central Hardwood Stand

Shovel logging, a ground-based, non-tractive yarding method that uses an excavator fixed with a grapple instead of a bucket, offers the potential to yard felled wood with less impact to forest soils than conventional rubber-tired skidding methods. The results of this study, carried out in Apalachian hardwoods, indicated that, although neither conventional nor shovel logging methods can be recommended over the other based solely on short-term impacts to soil bulk density, shovel logging resulted in significantly less surface soil disturbance. In addition, shovel logging eliminated the need for primary skid trail construction, identified as a potential source of particulate matter that may contribute to nonpoint source pollution

Empirical Investigation of the Relevance and Predictive Ability of the Sas 99 Fraud Risk Factors

This study empirically examined the fraud risk factors adopted by the Accounting Standards Board in SAS No. 99 and developed a fraud prediction model that is useful in discriminating between fraud and no-fraud firms. The first phase of testing involved identifying and testing proxies for Cressey's fraud triangle (pressure, opportunity, and rationalization). A step-wise logistic regression analysis of matched sample firms was used to evaluate the usefulness of the fraud risk factors in discriminating between fraud and no-fraud firms. Notably, all data was collected from publicly available sources. After identifying the significant fraud risk factors, the study applied multiple discriminate analysis to the significant variables to develop a fraud prediction model. The results indicate that users of publicly available data should take additional precautions when companies have audit committees with a low percentage of outside directors, high management ownership exceeding 5%, high cumulative percentage ownership in the firm held by insiders, and/or a CEO who holds both the CEO and Chairman of the Board position. The prediction model correctly classified fraud firms 72% of the time. This finding is important since Kuruppu et al. (2003) noted that the Altman bankruptcy model, when applied to matched samples such as this study, only has an accuracy rate of between 40 and 50%. Additionally, studies that have expanded the financial ratios used by Altman (1969), such as Persons (1995) and Kaminski et al. (2004), have correctly identified fraud firms in the year prior to the fraud only 20 to 40% of the time. The fraud prediction model developed in this study is more accurate in correctly identifying no-fraud firms. The overall effect is that this fraud prediction model has a lower misclassification error of fraud and no-fraud firms than the other models.School of Accountin

Innovation Capacity: A Firm Level Response to Subsidy Activity in a National Setting

The purpose of this paper is to investigate the effect subsidies have on firm-level innovation across Eastern European and Central Asian countries and to assess if these effects move to increase firm-level capability. Specifically, we investigate the extent subsidy programs act to shape and guide firm-level innovative capabilities and how the presence of such capabilities affect operational performance. We employ a Probit model to investigate firm-level innovation and OLS regression to assess how subsidies, in association with the decision to adopt foreign technology and in-house research and development (R&D) affect firm productive capacity. Results suggest subsidies promote innovation and that when these subsidies are contemporaneously considered in the face of the decision to adopt foreign technologies and employ in-house R&D, firm-level capacity increases

Do-it-yourself digital: the production boundary, the productivity puzzle and economic welfare

Part of the debate about the ‘productivity puzzle’ concerns potential mismeasurement of GDP due to digital activities. This paper discusses some measurement issues arising from digitally-enabled substitutions in activity across the conventional production boundary. Production boundary issues are not new, as conventionally defined GDP statistics account for the monetary cost but not the time cost of consumption and production. This means changes in the way time is allocated between market and home production affect measured growth and productivity. Just as technological innovation in domestic appliances led to a substitution from home production into market consumption in the second half of the 20th century, today’s digital innovations are driving some reverse substitution out of the market into home production. Statistical agencies do not currently collect the data needed to measure the scale of the switch, but the available evidence suggests it may be enough to make a contribution to understanding the puzzling behaviour of measured productivityEconomics Statistics Centre of Excellenc

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Internet of Things for Sustainable Mining

The sustainable mining Internet of Things deals with the applications of IoT technology to the coupled needs of sustainable recovery of metals and a healthy environment for a thriving planet. In this chapter, the IoT architecture and technology is presented to support development of a digital mining platform emphasizing the exploration of rock–fluid–environment interactions to develop extraction methods with maximum economic benefit, while maintaining and preserving both water quantity and quality, soil, and, ultimately, human health. New perspectives are provided for IoT applications in developing new mineral resources, improved management of tailings, monitoring and mitigating contamination from mining. Moreover, tools to assess the environmental and social impacts of mining including the demands on dwindling freshwater resources. The cutting-edge technologies that could be leveraged to develop the state-of-the-art sustainable mining IoT paradigm are also discussed