• Filtering Particle Size Distribution of Mixed Sediments (2012 INQUA Loess Conference)

    Most loess has unimodal textural curves, with a peak in the silt fraction. However, in thin loess areas, where loess overlies coarse-textured sediment, it often has a bimodal textural curve, due to pedoturbation. We present a method that can tease out these two textural signatures and thus, estimate the original particle size distribution of the loess. In this method the coarser sediment portion of such a “mixed” particle size distribution curve is removed, or “filtered out.” The end result is a curve (and data) that better reflect the original textural characteristics of the loess.

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  • The Soil Productivity Index (2012 AAG Conference)

    This poster introduces a new, ordinally based, Soil Productivity Index (PI). The demonstration map shows the PI for the lower 48 states. The PI uses family-level Soil Taxonomy information, i.e., interpretations of taxonomic features or properties that tend to be associated with natural low or high soil productivity, to rank soils from 0 (least productive) to 19 (most productive). The index has wide application, because, unlike competing indexes, it does not require copious amounts of soil data, e.g., pH, organic matter, or CEC, in its derivation.

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  • USDA Soil Texture Class Macro

    An Excel spreadsheet containing a macro for calculating the USDA soil texture class. The macro can be used as a cell function, allowing you to automatically calculate the texture class from a series of cells with percentages of soil separates.

    Download spreadsheet containing the USDA Soil Texture Class Macro (22.3 KB)
  • The Soil Productivity and Drainage Indexes (2011 NCSS Conference)

    This poster presents the Soil Drainage Index (DI) and introduces a new, Soil Productivity Index (PI). These indexes are taxonomically-based, ordinal estimates of relative soil properties and are shown mapped side-by-side for the lower 48 states. The DI is intended to reflect the amount of water that a soil can supply to growing plants under natural conditions. The PI uses interpretations of taxonomic features or properties that tend to be associated with naturally low or high soil productivity to rank soils from 0 (least productive) to 19 (most productive).

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  • Using Soil Surveys to Delineate Quaternary Parent Materials and Landforms (2010 Binghamton Geomorphology Symposium)

    We sought to create the best possible Quaternary geology map of the Des Moines Lobe solely using readily available National Cooperative Soil Survey (NCSS) data. We then sought to test whether that map is comparable to Quaternary geology maps previously published by geologists. Categorization of soil map units with respect to geologic unit successfully created a detailed Quaternary geologic map for the Des Moines Lobe, showing strong agreement with the existing Quaternary geologic maps while adding a user-controlled level of scale.

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  • Semantic calibration of digital terrain analysis scale

    DTA has not been field tested to the extent that traditional field metrics of topography have been. Human assessment of topography synthesizes multiple parameters at multiple scales to characterize a landscape, based on field experience. In order to capture the analysis scale used by field scientists, this study introduces a method for calibrating the analysis scale of DTA to field assessments.

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  • Top-ranked priority research questions for soil science in the 21st century

    Soils provide critical support essential for life on earth, regulate processes across diverse terrestrial and aquatic ecosystems, and interact with the atmosphere. In this paper, we present the outcomes of an initiative to identify pressing research questions as a tool for guiding future soil science research priorities.

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  • Thin, pedoturbated, and locally sourced loess in the western Upper Peninsula of Michigan

    County soil surveys document thin loess deposits across large tracts of Michigan’s western Upper Peninsula (UP), which we informally call the Peshekee loess. Our study is the first to examine the distribution, thickness and textural characteristics of these loess deposits, and speculate as to their origins. We introduce and describe a method by which the mixed sand data are removed, or “filtered out,” of the original particle size data, to better reflect the original textural characteristics of the loess.

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  • Precision of soil particle size results using laser diffractometry

    Because laser diffractometry produces much more detailed data than does traditional pipette analysis, and because a much smaller sample is used in the analysis, precision or repeatability of laser-produced PSA data is a concern. The approach presented provides both a simple method for assessing the variation in PSA data sets and establishes a comparable standard for determining when additional measurements are needed to find a more precise result.

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  • The need to continue improving soil survey maps

    Soil Survey maps are the preeminent data set collected about our environment. Although there are other impressive data sets that are regularly used for studying and utilizing the environment, none match the wide utility and potential of soil maps. Recent innovations create opportunities to increase both the resolution and the efficiency at which Soil Survey maps are made.

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