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Krista A. Stensvold

Publications and source records attributed to Krista A. Stensvold.

2 recordsLinked to original sources

Distribution and variation of arsenic in Wisconsin surface soils, with data on other trace elements

A total of 664 soil samples distributed among different geographic regions and soil types were collected across Wisconsin to describe the distribution of arsenic relative to parent material, soil texture, and drainage class. Soils from 6 inches in depth were composited, digested in aqua regia, and analyzed for 17 trace elements. Observed soil arsenic concentrations range from a high of 39 milligrams per kilogram (mg/kg) to less than the laboratory detection limit of 1 mg/kg. Ten samples with soil arsenic concentrations greater than 8.5 mg/kg were determined to be significantly separate from the main cluster of the dataset. With these outliers removed, overall soil arsenic concentrations in Wisconsin have a median value of 1.8 mg/kg, and the 95-percent upper confidence limit of the mean is 2.4 mg/kg. Soils with sandy glacial outwash as a parent material have a lower median arsenic concentration (1.0 mg/kg) than soils forming in other parent materials (1.5 to 3.0 mg/kg). Soil texture and drainage category also influence median arsenic concentration. Finer grained soils have a higher observed range of concentrations. For loamy and loess-dominated soil groups, drainage category influences the median arsenic concentration and observed range of values, but a consistent relationship within the data is not apparent. Statistical analysis of the 16 other elements are presented in this report, but the relationships of concentrations to soil properties or geographic areas were not examined.

Wisconsin

Determination of biologically significant hydrologic condition metrics in urbanizing watersheds: an empirical analysis over a range of environmental settings

We investigated the relations among 83 hydrologic condition metrics (HCMs) and changes in algal, invertebrate, and fish communities in five metropolitan areas across the continental United States. We used a statistical approach that employed Spearman correlation and regression tree analysis to identify five HCMs that are strongly associated with observed biological variation along a gradient of urbanization. The HCMs related to average flow magnitude, high-flow magnitude, high-flow event frequency, high-flow duration, and rate of change of stream cross-sectional area were most consistently associated with changes in aquatic communities. Although our investigation used an urban gradient design with short hydrologic periods of record (≤1 year) of hourly cross-sectional area time series, these five HCMs were consistent with previous investigations using long-term daily-flow records. The ecological sampling day often was included in the hydrologic period. Regression tree models explained up to 73, 92, and 79% of variance for specific algal, invertebrate, and fish community metrics, respectively. National models generally were not as statistically significant as models for individual metropolitan areas. High-flow event frequency, a hydrologic metric found to be transferable across stream type and useful for classifying habitat by previous research, was found to be the most ecologically relevant HCM; transformation by precipitation increased national-scale applicability. We also investigated the relation between measures of stream flashiness and land-cover indicators of urbanization and found that land-cover characteristic and pattern variables, such as road density, percent wetland, and proximity of developed land, were strongly related to HCMs at both a metropolitan and national scale and, therefore, may be effective land-use management options in addition to wholesale impervious-area reduction.

Milwaukee-Green Bay; Boston; Raleigh; Atlanta; Bir