John M. Galbraith

Effects of harvest frequency and biosolids application on switchgrass yield, feedstock quality, and theoretical ethanol yield.

Sustainable development of a bioenergy industry will require low‐cost, high‐yielding biomass feedstock of desirable quality. Switchgrass (Panicum virgatum L.) is one of the primary feedstock candidates in North America, but the potential to grow this biomass crop using fertility from biosolids has not been fully explored. The objective of this study was to examine the effects of harvest frequency and biosolids application on switchgrass in Virginia, USA. ‘Cave‐in‐Rock’ switchgrass from well‐established plots was cut once (November) or twice (July and November) per year between 2010 and 2012. Class A biosolids were applied once at rates of 0, 153, 306, and 459 kg N ha−1 in May 2010. Biomass yield, neutral and acid detergent fiber, cellulose, hemicellulose, lignin, and ash were determined. Theoretical ethanol potential (TEP, l ethanol Mg−1 biomass) and yield (TEY, l ethanol ha−1) were calculated based on cellulose and hemicellulose concentrations. Cutting twice per season produced greater biomass yields than one cutting (11.7 vs. 9.8 Mg ha−1) in 2011, but no differences were observed in other years. Cutting once produced feedstock with greater TEP (478 vs. 438 l Mg−1), but no differences in TEY between cutting frequencies. Biosolids applied at 153, 306, and 459 kg N ha−1 increased biomass yields by 25%, 37%, and 46%, and TEY by 25%, 34%, and 42%, respectively. Biosolids had inconsistent effects on feedstock quality and TEP. A single, end‐of‐season harvest likely will be preferred based on apparent advantages in feedstock quality. Biosolids can serve as an effective alternative to N fertilizer in switchgrass‐to‐energy systems.

An expert system for soil taxonomy

This study tested the feasibility of producing an automated expert system for Soil Taxonomy to identify soil order from stored data by building an expert system prototype. Soil Taxonomy rules for the Histosol, Spodosol, Andisol, and Oxisol orders were translated into decision tree format. Seventy independent properties were stored in tabular format for each pedon. Heuristic knowledge (expert rules) was added to the decision trees to query a minimum data set, with 13 field description properties required to contain data for each soil horizon, 20 default values, and three estimated values from lookup tables. The prototype expert system was developed using an object-oriented expert system shell. Twenty-seven subsections were named in the rules to identify the Histosol, Spodosol, Andisol, and Oxisol soil orders. Sixty-seven objects, 70 independent properties, and 135 calculated properties were needed to define these subsections and their properties. The tested prototype quickly and correctly identified the diagnostic horizons, nonspatial differentiae, and the soil order, proving the feasibility of developing an expert system for Soil Taxonomy using existing computer programs and programming methods. We recommend improvements in policy and procedure for recording field description data and development of the expert rules to add dynamic links to outside models and software and incorporate fuzzy logic. The project should be continued to improve the prototype interface and data output features and to complete an expert system to add the remaining soil orders for Soil Taxonomy.

DEVELOPMENT OF A FOREST SITE QUALITY CLASSIFICATION MODEL FOR MINE SOILS IN THE APPALACHIAN COALFIELD REGION 1

The Appalachian coalfields occur largely under rugged mountains covered by native hardwood forests. These forests, soils, and bedrock are removed by the surface mining process. Surface mines are not typically reclaimed to a managed forest land-use, but are often seeded with non-native grasses and legumes, or with pines, black locust, and shrubs for unmanaged forest land. Surface mining and reclamation techniques since the passage of the Surface Mining Control and Reclamation Act of 1977 (SMCRA) create highly compacted mine soils with high coarse fragment content, low organic matter, and high pH, which inhibits native forest reestablishment. The purpose of this study was to develop a forest site quality classification model to advise landowners on the production potential and feasibility of reforesting their mined lands with white pine (Pinus strobus L.). Ten selected physical, chemical, and site properties were assessed and a model was developed using variables that were the most highly correlated with the growth of 10- to 18-year-old white pines established on post- SMCRA surface-mined sites. A model with soil pH, texture, density, and rooting depth variables yielded a coefficient of determination of 0.71. Sufficiency curves were used in a productivity index (PI) model to classify reclaimed surface-mined land into one of five forest site quality classes (FSQC). A site index (SI50 = dominant tree height at age 50) for white pine was estimated for each class, and this measure of productivity may be used to aid in management decisions regarding reforestation of surface mines in the Appalachian coalfields.

A functional analysis of soil taxonomy in relation to expert system techniques

The characteristics of Soil Taxonomy are analyzed relative to various techniques for developing expert systems. Special emphasis is placed on computer program features that allow for more consistent application of classification systems and make them more user-friendly and understandable. We studied the functional logic and query processes employed by Soil Taxonomy to identify soil individuals and compared the methods with those used in other natural object classification systems. Numerical and classical identification methods and program features found in recent computer programs were evaluated for use with Soil Taxonomy. The keys in Soil Taxonomy are purely phenetic in nature and single-access in approach. In the absence of rule- and value confidence-weighting factors, the rules must be encoded without sequence modification to preserve the decision logic. Decisions in Soil Taxonomy query a large, often incomplete, and sometimes faulty data set, requiring error-checking of data and the addition of expert rules to the encoded decisions to prevent indecision. Soil Taxonomy rules check within the soil individual for the presence or absence of spatial and nonspatial differentiae, specific property values, or other qualifications. Soil Taxonomy is suitable as the subject of an object-oriented expert system, and planning has begun on development of an automated prototype for the Histosol, Andisol, Spodosol, and Oxisol soil orders. Expert system features coupled with additional models and algorithms can be used to improve the use and user-friendliness of Soil Taxonomy.

Using public domain data to aid in field identification of hydric soils

Hydric soil field identification is a common activity for natural resource professionals and planners, but it can be time consuming and labor intensive. This study used Soil Survey Geographic Database (SSURGO), National Wetlands Inventory (NWI), National Land Cover Data (NLCD), and other public domain data to make digital hydric soil predictive maps of two study areas in western Virginia. Soil scientists used the predictive maps as guides to conduct hydric soil field surveys and compared the results to delineations of SSURGO map units dominated by hydric soils and NWI and NLCD wetlands. At Stuarts Draft, 15% of the 1296-ha study area was composed of hydric soils compared with 14% estimated by SSURGO. At Blacksburg, 3% of the 828-ha study area was composed of hydric soils compared with 1% estimated by SSURGO. Both NWI and NLCD estimated 1% wetlands at each area. Locational correspondence was higher between the field survey and SSURGO than between the field survey and the NWI and NLCD wetlands at both study areas. The predictive maps were useful because the SSURGO delineations were closely aligned with field survey delineations, had <2% false negative identifications compared with >13% for NWI and NLCD at Stuarts Draft, and had ≤ 2% false positive identifications. Overlaying NWI and NLCD onto SSURGO polygons resulted in ≤ 1% improvement of predictive map utility, but all indicators of hydric soils were useful in narrowing the specific location of hydric soils within large SSURGO delineations.

INFLUENCE OF PHYSICAL, CHEMICAL, AND BIOLOGICAL MINE SOIL PROPERTIES ON WHITE OAK SEEDLING GROWTH 1

Landowners in the Appalachian region are becoming increasingly interested in restoring the native hardwood forest on mined land after reclamation. Trees are usually planted in topsoil substitutes consisting of blasted rock strata from the geologic profile. Reforestation attempts using native hardwoods have often been unsuccessful due to the highly variable nature of the physical, chemical, and biological properties of mine spoils. The purpose of this study was to determine which mine soil properties most influence white oak seedling growth, and to test whether or not these properties are adequately reflected in a preliminary mine soil classification model. Seventy-two 3-yr-old white oak trees were randomly selected across a reclaimed site in southwestern Virginia that varied greatly in spoil type and site properties. Tree height was measured and soil samples were taken to a 40 cm depth at the base of each tree and analyzed for physical, chemical, and biological properties hypothesized to influence tree growth. Tree height and biomass, which ranged from 15 to 125 cm, and 0.24 to 190.03 g, respectively, were regressed against mine soil and site properties. Potassium, size of microbial populations, extractable nitrogen, pH, soil texture, aspect, and phosphorous accounted for over 52% of the variability in tree growth. This study indicates that white oaks are most successful growing on east-facing aspects, in slightly-acidic, sandy loam textured, fertile mine soils that are conducive to soil microbial activity. These results suggest that sandstone rock types with suitable chemical properties should be selected for topsoil substitutes when native hardwood restoration is the desired post-mining land use.

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

This is the first quarterly Technical Report for the period October-December, 2003. A kick-off meeting was held with NETL administrators and scientists at Morgantown, WV, on December 2, 2002. The 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 this first quarterly reporting period, five Graduate Research Assistants were recruited, an MOA was drafted between Virginia Tech and three industry cooperators, preliminary field locations for controlled studies were located, and a preliminary analysis of a carbon inventory of forest sites on mined land was made.

Soil Taxonomy Proposals for Acid Sulfate Soils and Subaqueous Soils Raised by the 8th International Acid Sulfate Soils Conference

The 8th International Acid Sulfate Soils Conference presented examples and discussions for classification of ‘acid sulfate soils’ and related issues for ‘subaqueous soils’. When these soils are disturbed or exposed, the sulfides (predominantly pyrite) react with oxygen to produce sulfuric acid; soil materials that do this to a great extent are recognised as ‘sulfidic materials’ in Soil Taxonomy. Soil Taxonomy describes physical and chemical properties and thresholds for incubation of sulfidic materials for acidification, and has developed definitions for features and materials commonly seen in these soils. However, based on discussions and examples from field tours the conference has several proposals to modify and add to existing definitions, such as adding new subgroups, defining sulfuric materials and editing the definition of the sulfuric horizon. These changes are centred on improving the interpretative value of taxa in Soil Taxonomy as well as use and management recommendations and their value in soil survey products.

Impacts of fundamental changes to Soil Taxonomy

Soil Taxonomy is one of the dominant soil classification systems in the world, but has undergone revisions on a regular basis since 1983. It is larger and some parts have become difficult to apply without considerable experience. Some pedologists that are not daily users (e.g. soil mappers) have called for a simpler version. The second edition of the Illustrated Guide to Soil Taxonomy serves as a model for enhanced teaching purposes that can be used by others besides trained soil scientists. In 2014, a task force was created to develop a set of proposed improvements to Soil Taxonomy. Guiding principles were established to assist in the development of proposals to increase the use of Soil Taxonomy, minimise the impact on the existing soil survey and soil science division programs, and move toward harmonisation of definitions with other classification systems, such as the WRB and South African systems. Initially, 15 proposals have been listed. Examples of a simplified mollic epipedon and addition of several new soil orders are discussed. Accepted proposals will contribute toward the third edition of Soil Taxonomy. The impact will be easier collaboration between soil scientists in countries that use Soil Taxonomy and better communication with other professionals.

Potential Contribution of Combined Atmospheric Ca2+ and Mg2+ Wet Deposition Within the Continental U.S. to Soil Inorganic Carbon Sequestration

Abstract Soil inorganic carbon (SIC) stocks continuously change from the formation of pedogenic carbonates, a process requiring inputs of Ca 2+ and Mg 2+ ions. This study ranked the soil orders in terms of potential inorganic carbon sequestration resulting from wet Ca 2+ and Mg 2+ deposition from 1994 to 2003 within the continental United States. The analysis revealed that average annual atmospheric wet deposition of Ca 2+ and Mg 2+ was the highest in the Central Midwest-Great Plains region, likely due to soil particle input from loess-derived soils. The soil orders receiving the highest total average annual atmospheric wet Ca 2+ and Mg 2+ deposition, expressed as potential inorganic carbon formation (barring losses from erosion and leaching), were: 1) Mollisols (1.1 × 10 8 kg C), 2) Alfisols (8.4 × 10 7 kg C), 3) Entisols (3.8 × 10 7 kg C), and 4) Aridisols (2.8 × 10 7 kg C). In terms of area-normalized result, the soil orders were ranked: 1) Histosols (73 kg C km −2 ), 2) Alfisols and Vertisols (64 kg C km −2 ), 3) Mollisols (62 kg C km −2 ), and 4) Spodosols (52 kg C km −2 ). The results of this study provide an estimate of potential soil inorganic carbon sequestration as a result of atmospheric wet Ca 2+ and Mg 2+ deposition, and this information may be useful in assessing dynamic nature of soil inorganic carbon pools.