Estimation of Efficiency of Processing Soil Samples for Pesticide Residues Analysis

The efficiency of four sample processing methods was tested with eight different types of soils representing the major proportion of cultivated soils. The principle of sampling constant was applied for characterizing the efficiency of the procedures and testing the well-mixed status of the prepared soil. The test material was 14C-labeled atrazine that enabled keeping the random error of analyses ≤ about 1%. Adding water to the soil proved to be the most efficient and generally applicable procedure resulting in about 6% relative sample processing uncertainty for 20 g test portions. The expected error is inversely proportional to the mass of test portion. Smashing and manual mixing of soil resulted in about four times higher uncertainty than mixing with water. Grinding of soil is applicable for dry soils only, but the test procedure applied was not suitable for estimating a typical uncertainty of processing dry soil samples. Adding dry ice did not improve the efficiency of sample processing.     

Integrated Measures of Anthropogenic Stress in the U.S. Great Lakes Basin

Integrated, quantitative expressions of anthropogenic stress over large geographic regions can be valuable tools in environmental research and management. Despite the fundamental appeal of a regional approach, development of regional stress measures remains one of the most important current challenges in environmental science. Using publicly available, pre-existing spatial datasets, we developed a geographic information system database of 86 variables related to five classes of anthropogenic stress in the U.S. Great Lakes basin: agriculture, atmospheric deposition, human population, land cover, and point source pollution. The original variables were quantified by a variety of data types over a broad range of spatial and classification resolutions. We summarized the original data for 762 watershed-based units that comprise the U.S. portion of the basin and then used principal components analysis to develop overall stress measures within each stress category. We developed a cumulative stress index by combining the first principal component from each of the five stress categories. Maps of the stress measures illustrate strong spatial patterns across the basin, with the greatest amount of stress occurring on the western shore of Lake Michigan, southwest Lake Erie, and southeastern Lake Ontario. We found strong relationships between the stress measures and characteristics of bird communities, fish communities, and water chemistry measurements from the coastal region. The stress measures are taken to represent the major threats to coastal ecosystems in the U.S. Great Lakes. Such regional-scale efforts are critical for understanding relationships between human disturbance and ecosystem response, and can be used to guide environmental decision-making at both regional and local scales.     

Estimating Sediment and Nutrient Loads in Four Western Lake Superior Streams

Total suspended solids (TSS) and total phosphorus (TP) have been shown to be strongly correlated with turbidity in watersheds. High‐frequency in situ turbidity can provide estimates of these potential pollutants over a wide range of hydrologic conditions. Concentrations and loads were estimated in four western Lake Superior trout streams from 2005 to 2010 using regression models relating continuous turbidity data to grab sample measures of TSS and TP during differing flow regimes. TSS loads estimated using the turbidity surrogate were compared with those made using FLUX software, a standard assessment technique based on discharge and grab sampling for TSS. More traditional rating curve methodology was not suitable because of the high variability in the particulates vs. discharge relationship. Stream‐specific turbidity and TSS data were strongly correlated (r² = 0.5 to 0.8; p < 0.05) and less so for TP (r² = 0.3 to 0.7; p < 0.05). Near‐continuous turbidity monitoring (every 15 min) provided a good method for estimating both TSS and TP concentration, providing information when manual sample collection was unlikely, and allowing for detailed analyses of short‐term responses of flashy Lake Superior tributaries to highly variable weather and hydrologic conditions while the FLUX model typically resulted in load estimates greater than those determined using the turbidity surrogate, with 17/23 stream years having greater FLUX estimates for TSS and 18/23 for TP.     

Human Influences on Water Quality in Great Lakes Coastal Wetlands

A better understanding of relationships between human activities and water chemistry is needed to identify and manage sources of anthropogenic stress in Great Lakes coastal wetlands. The objective of the study described in this article was to characterize relationships between water chemistry and multiple classes of human activity (agriculture, population and development, point source pollution, and atmospheric deposition). We also evaluated the influence of geomorphology and biogeographic factors on stressor-water quality relationships. We collected water chemistry data from 98 coastal wetlands distributed along the United States shoreline of the Laurentian Great Lakes and GIS-based stressor data from the associated drainage basin to examine stressor-water quality relationships. The sampling captured broad ranges (1.5–2 orders of magnitude) in total phosphorus (TP), total nitrogen (TN), dissolved inorganic nitrogen (DIN), total suspended solids (TSS), chlorophyll a (Chl a), and chloride; concentrations were strongly correlated with stressor metrics. Hierarchical partitioning and all-subsets regression analyses were used to evaluate the independent influence of different stressor classes on water quality and to identify best predictive models. Results showed that all categories of stress influenced water quality and that the relative influence of different classes of disturbance varied among water quality parameters. Chloride exhibited the strongest relationships with stressors followed in order by TN, Chl a, TP, TSS, and DIN. In general, coarse scale classification of wetlands by morphology (three wetland classes: riverine, protected, open coastal) and biogeography (two ecoprovinces: Eastern Broadleaf Forest [EBF] and Laurentian Mixed Forest [LMF]) did not improve predictive models. This study provides strong evidence of the link between water chemistry and human stress in Great Lakes coastal wetlands and can be used to inform management efforts to improve water quality in Great Lakes coastal ecosystems.     

Evaluation of a fluorometric screening method for predicting total PAH concentrations in contaminated sediments

A fluorometric screening method was used to estimate total polycyclic aromatic hydrocarbon (t-PAH) concentrations in sediments collected from the St. Louis River Area of Concern (AOC) in northeastern Minnesota. Sediments were collected as part of a Regional Environmental Monitoring and Assessment Program (R-EMAP) study to assess sediment quality in the AOC. The screening method was calibrated using a PAH surrogate standard consisting of eight PAHs commonly found in the St. LouisRiver system, at their approximate proportions. Estimated PAHconcentrations were compared to GC/MS measured `true' PAH concentrations to evaluate the overall predictive power of thescreening method. Regression analysis of log transformed estimated versus true PAH concentration yielded an r² of 0.72 (n = 86). In addition, the rates of false positive and false negative predictions associated with the screening methodwere determined relative to different sediment effects concentrations (SECs) for total PAHs. In general, the rate of false positive predictions was shown to increase as the SEC criteria value decreased, while false negative rates remainedconsistently low (below 7%). Methodological recommendations which led to a three-fold reduction in false negatives, and theimproved prediction of both high and low PAH samples, are presented.