Despite the widespread availability of relatively detailed soil maps in the USA, few areas have a surficial geology map published with as much spatial detail. This apparent gap between disciplines calls to question the accuracy of soil maps to represent the spatial distribution of surficial geologic materials. Therefore, the purpose of this research was to test the agreement between maps from these two sources.
Results suggest that models with limited predictor pools can substitute other predictors to compensate for unavailable variables. However, a better performing model was always found by considering predictor variables at multiple scales. Although the scale effect of the modifiable area unit problem is generally well known, this study suggests digital soil mapping efforts would be enhanced by the greater consideration of predictor variables at multiple analysis scales.
This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map.
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.
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.
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.
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.
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.
We introduce, evaluate, and apply a new ordinally based soil Productivity Index (PI). The index has a wide application generally at landscape scales. Unlike competing indexes, it does not require copious amounts of soil data, for example, pH, organic matter, or cation exchange capacity, in its derivation. Geographic information system applications of the PI, in particular, have great potential. For regionally extensive applications, the PI may be as useful and robust as other indexes that have much more exacting data requirements.
Wetland hydrologic class change from prior to European settlement to present on the Des Moines Lobe, Iowa
The water regimes of contemporary wetlands when compared to their historic regimes suggest that many of today’s wetlands have different water regimes than they did prior to the onset of drainage. Because of the regional lowering of the groundwater table, many of today’s wetlands have drier water regimes, but some have wetter water regimes because they receive drainage tile inputs. Our results indicate that restoration has favored the wettest classes of wetlands and that temporarily to saturated wetland classes have not been restored in proportion to their relative abundance in the pre-drainage landscape.