Author: Bradley Miller
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.
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.