Geological Survey National Water Quality Research Articles

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 (m/z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r2 = 0.93), praseodymium (Pr) (r2 = 0.94) and samarium (Sm) (r2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Evaluation of Bioconcentration of Organophosphate Pesticides Monocrotophos and Quinalphos in Freshwater Fish Channa striatus

Fish bioconcentration factors (BCF) are used for the prediction of the environmental effects of new chemicals and some studies have suggested that they can be predicted from the Physico-chemical properties of the chemical. The rigorous use of pesticides resulted in the dispersal and persistence of pollutants throughout the ecosystem. Pesticides contamination in the aquatic ecosystem has become one of the most staggering issues due to their detrimental effect on public health and the environment. This study aimed to investigate the bioconcentration factor of pesticides monocrotophos and quinalphos in three tissues (skin, muscles, gills) of the fish Channa striatus for 21 days, of the three analyzed tissues of monocrotophos exposed fish, gill accumulated highest concentration of (0.033 mg kg-1) while muscles (0.012 mg kg-1) at the lowest, whereas the concentration of quinalphos was maximum (0.98mg kg-1) in liver and minimum (0.074 mg kg-1) in muscle. Results showed that the effect of pesticide differs from tissue to tissue. However, the levels exceeded maximum detection limits as recommended by U.S. Geological Survey National Water Quality Laboratory, Denver, Colo. Hence it is suggested that the fish containing pesticide residues beyond permissible limit should be avoided for food purposes

Climate extremes as drivers of surface-water-quality trends in the United States

Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic matter on the landscape. Many studies predict future changes in water-quality related to climate changes; however, fewer studies specifically document changes in water quality related to changes in climate, and they are usually limited in geographic scope. Recently, the U.S. Geological Survey's National Water-Quality Program reported nearly 12,000 trends in concentration and load for numerous water-quality constituents, including nutrients, sediment, major ions, and carbon. The results provide an unprecedented opportunity to examine sites across the conterminous United States for changes in water quality related to climate changes. We used published water-quality trends, modeled using the method of Weighted Regressions on Time, Season and Discharge, and calculated trends in climate extremes indices, using a modified Mann-Kendall trend method. The water-quality and the climate extremes trends were combined to identify areas in the conterminous United States where changes in climate extremes may have changed water quality. We investigated the water-quality trends in these areas to determine whether the trends related to changes in climate. We found that it was important to go beyond spatial correlation and examine trends on a watershed scale to investigate key drivers of trends. We found successful management practices in Iowa to reduce chloride concentrations, despite increases in icing days. For sediment, it appeared that management practices were having a larger effect than climate changes. For nutrients, complex forces affecting water quality make it difficult to unequivocally attribute water-quality change to climate change.

A Fix for Fixtures: Addressing Lead Contamination in West African Drinking Water.

A Fix for Fixtures: Addressing Lead Contamination in West African Drinking Water.

Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures

Spike- and blank-based procedures were applied to estimate the detection limits (DLs) for example analytes from inorganic and organic methods for water samples to compare with the U.S. Environmental Protection Agency's (EPA) Method Detection Limit (MDL) procedures (revisions 1.11 and 2.0). The multi-concentration spike-based procedures ASTM Within-laboratory Critical Level (DQCALC) and EPA's Lowest Concentration Minimum Reporting Level were compared in one application, with DQCALC further applied to many methods. The blank-based DLs, MDLb99 (99th percentile) or MDLbY (= mean blank concentration + s × t), estimated using large numbers (>100) of blank samples often provide DLs that better approach or achieve the desired ≤1% false positive risk level compared to spike-based DLs. For primarily organic methods that do not provide many uncensored blank results, spike-based DQCALC or MDL rev. 2.0 are needed to simulate the blank distribution and estimate the DL. DQCALC is especially useful for estimating DLs for multi-analyte methods having very different analyte response characteristics. Time series plots of DLs estimated using different procedures reveal that DLs are dependent on the applied procedure, should not be expected to be static over time, and seem best viewed as falling over a range versus being a single value. Use of both blank- and spike-based DL procedures help inform this DL range. Data reporting conventions that censor data at a threshold and report “less than” that threshold concentration as the reporting level have unknown and potentially high false negative risk. The U.S. Geological Survey National Water Quality Laboratory's Laboratory Reporting Level (LRL) convention (applied primarily to organic methods) attempts to simultaneously minimize both the false positive and false negative risk when <LRL is reported and data between DL and the higher LRL are allowed to be reported.

Assessment of multi-stressors on compositional turnover of diatom, invertebrate and fish assemblages along an urban gradient in Pacific Northwest streams (USA)

• Gradient forest (GF) models evaluate taxon specific responses to stressors. • GF diatom, invertebrate, fish models showed several consistent variables selected. • Variables included substrate size, dissolved oxygen, and various contaminant measures. • Nitrogen and phosphorus important in both diatom and invertebrate models but not fish. • Taxa responded to multiple stressors following patterns of sensitive versus tolerance. This study is part of the regional stream-quality assessment (RSQA) conducted by the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) project. The purpose of this study is to examine small streams along land-use and stressor gradients at the regional scale and to evaluate the relative importance of instream stressors on diatom, macroinvertebrate, and fish assemblages. In 2015, the RSQA project assessed stream quality in 82 wadeable streams that were selected along an urban land-use gradient in the Pacific Northwest Region (PNW) of the United States. This study evaluates the effects of four major categories of measured instream stressors – flow (i.e. alteration), water quality, habitat, and contaminants (in water and sediment) – on stream biota. We used gradient forest (GF) models to evaluate taxon specific responses to the various stressors for the three biotic assemblages. Results for diatom, invertebrate and fish assemblages showed that several environmental variables including substrate size, dissolved oxygen, and two or more different contaminants were selected in each of the GF models. In general, all three assemblages were negatively associated with any contaminant measures above zero, except the more tolerant taxa in each assemblage, which responded positively to contaminants. Total nitrogen (TN) and total phosphorus (TP) were important in both the diatom and invertebrate GF models but not in the fish models, which were related to temperature and stream flow. TP and TN were the top two variables for diatom GF models and various taxa responded at a range of nutrient concentrations; however, some taxa responded at low concentrations, for example around 0.02 for TP and 0.5 mg/L for TN. In general, the three biotic assemblages responded to multiple stressors following general patterns of known sensitive versus tolerant taxa for each of the biotic groups studied, yet the GF models allow us to explore taxon specific responses. For example, most of the sensitive Ephemeroptera, Plecoptera, Trichoptera invertebrate taxa (EPT) responded negatively when any contaminant increased above zero; yet some taxa such as the tolerant Trichoptera Cheumatopsyche responded positively to contaminants and many of the other stressors. The findings of this study demonstrate the value of using multiple assemblages to monitoring stressor gradients associated with urban stream systems and the importance of evaluating the responses of individual taxa to stressors.

A Novel Method to Characterise Levels of Pharmaceutical Pollution in Large-Scale Aquatic Monitoring Campaigns

Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r2) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was &lt;20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.

Linking the Agricultural Landscape of the Midwest to Stream Health with Structural Equation Modeling.

Multiple physical and chemical stressors can simultaneously affect the biological condition of streams. To better understand the complex interactions of land-use practices, water quality, and ecological integrity of streams, the U.S. Geological Survey National Water Quality Assessment Project is conducting regional-scale assessments of stream condition across the United States. In the summer of 2013, weekly water samples were collected from 100 streams in the Midwestern United States. Employing watershed theory, we used structural equation modeling (SEM) to represent a general hypothesis for how 16 variables (previously identified to be important to stream condition) might be inter-related. Again, using SEM, we evaluated the ability of this "stressor network" to explain variations in multimetrics of algal, invertebrate, and fish community health, trimming away any environmental variables not contributing to an explanation of the ecological responses. Seven environmental variables-agricultural and urban land use, sand content of soils, basin area, percent riparian area as forest, channel erosion, and relative bed stability-were found to be important for all three-community metrics. The algal and invertebrate models included water-chemistry variables not included in the fish model. Results suggest that ecological integrity of Midwest streams are affected by both agricultural and urban land uses and by the natural geologic setting, as indicated by the sand content of soils. Chemicals related to crops (pesticides and nutrients) and residential uses (pyrethroids) were found to be more strongly related to ecological integrity than were natural factors (riparian forest, watershed soil character).

Metamodels to Bridge the Gap Between Modeling and Decision Support.

Insights from process-based models are a mainstay of many groundwater investigations; however, long runtimes often preclude their use in the decision-making process. Screening-level predictions are often needed in areas lacking time or funding for rigorous process-based modeling. The U.S. Geological Survey (USGS) Groundwater Resources and National Water Quality Assessment Programs are addressing these issues by evaluating the “metamodel” to bridge these gaps. A metamodel is a statistical model founded on a computationally expensive model. Although faster, the question remains: Can a statistical model provide similar insights to a numerical model with faster results? Metamodeling was developed to overcome long runtimes for sensitivity analysis (Blanning 1975); our focus is decision support applications. Two representative groundwater applications are: (1) the contribution of surface water to wells in shallow groundwater systems (e.g., Fienen and Plant 2014), and (2) unsaturated zone nitrate flux to groundwater (e.g., Nolan et al. 2012). The first step is to generate a representative sample of input/output combinations from the numerical model over a range of conditions. This variability is especially important when propagating uncertainty to predictions. Variability can be represented by many model runs using different input values or by few model runs with samples scattered in space/time experiencing the range of natural system variability. In the second step, a statistical learning technique is selected with which a predictive model can be “learned” from the data derived from the model. Techniques include

Elucidation of Contaminant-Induced Toxic Responses in the Biota of Lake Vembanad, Kerala, India

ABSTRACTThis study investigates the spatial distribution of various organochlorine insecticides (OCIs) and heavy metals in both sediment and a bivalve, Villorita cyprinoides var. Cochinensis, collected from three pristine areas of Lake Vembanad. The detected concentrations of OCIs in the bivalve and sediment are in the order DDT > Heptachlor > BHC and BHC > DDD > heptachlor, respectively. However the DDT concentration (28.5 ng/g) in the bivalve at Chambakkara exceeded the limit suggested by the U.S. Geological Survey's National Water-Quality Assessment Program (NWQAP) and indicated an anthropogenic input source for the parent DDT. The maximum potential contamination indices for Zn and Ni in the bivalve were 267.8 mg/kg and 22.3 mg/kg, respectively. The Enrichment Factor (EF) and geoaccumulation index (Igeo) values of sediment indicated that Cd showed high pollution status and the Biota Sediment Accumulation Factor value of heavy metals suggested that Zn, Cu, and Cd were bioaccumulated in the bivalve's tissue. The concentrations of Zn and Cd were above the threshold levels and regarded as harmful according to the international standard for metals in mollusc compiled by the Food and Agriculture Organization. Therefore, they create great health risk for mussel consumers.

Abiotic Factors Affecting the Persistence of Avian Influenza Virus in Surface Waters of Waterfowl Habitats

Avian influenza (AI) virus can remain infectious in water for months, and virus-contaminated surface water is considered to be a source of infection within wild waterfowl populations. Previous work has characterized the effects of pH, salinity, and temperature on viral persistence in water, but most of that work was done with modified distilled water. The objective of this study was to identify the abiotic factors that influence the duration of AI virus persistence in natural surface water. Surface water samples were collected from 38 waterfowl habitats distributed across the United States. Samples were submitted to the U.S. Geological Survey National Water Quality Laboratory for chemical analysis and the University of Georgia for viral reduction time analysis. Samples were filtered with 0.22-μm filters, and the durations of persistence of three wild-bird-derived influenza A viruses within each water sample at 10, 17, and 28°C were determined. The effects of the surface water physicochemical factors on the duration of AI viral persistence in laboratory experiments were evaluated by multivariable linear regression with robust standard errors. The duration of AI virus persistence was determined to be longest in filtered surface water with a low temperature (<17°C), a neutral-to-basic pH (7.0 to 8.5), low salinity (<0.5 ppt), and a low ammonia concentration (<0.5 mg/liter). Our results also highlighted potential strain-related variation in the stability of AI virus in surface water. These results bring us closer to being able to predict the duration of AI virus persistence in surface water of waterfowl habitats.

Risks of carbamate and organophosphate pesticide mixtures to salmon in the Pacific Northwest

Salmon populations in the Pacific Northwest are being affected by a variety of environmental stressors including intense fishing pressure, parasites and disease, climatic variability and change, land development, hatchery production, hydropower operations, stormwater runoff, and exposure to toxic contaminants. In recent years, there has been much concern that mixtures of pesticides are causing toxic effects to Pacific salmon. In this study, we compared measured stream water concentrations from 2 monitoring studies conducted in the Pacific Northwest with concentration-response curves derived for inhibition of brain acetylcholinesterase activity in juvenile coho salmon (Oncorhynchus kisutch) for mixtures of organophosphate (OPs) and carbamate (CBs) pesticides. In the first monitoring study, samples were collected from 2003 to 2007 in salmonid-bearing waters of 5 urban or agricultural watersheds in Washington State. This study was targeted to areas of high pesticide use and generally involved weekly sampling during the pesticide use season. The second monitoring study was the United States Geological Survey National Water Quality Assessment that included samples taken from 2003 to 2010 in California, Idaho, Oregon, and Washington. OPs and CBs were frequently detected in both studies. The available monitoring data collected since 2003, however, demonstrates that mixtures of OPs and CBs in surface waters rarely occur at levels capable of producing significant physiological and behavioral effects in Pacific salmon. The observed mixtures never reached concentrations capable of causing mortality. We conclude that mixtures of organophosphates and carbamates do not pose a significant direct risk to Pacific salmon.

Vulnerability of Recently Recharged Groundwater in Principle Aquifers of the United States To Nitrate Contamination

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

Short‐term macroinvertebrate recruitment and sediment accumulation: A novel field chamber approach

Stream-deposited sediment is one of the major stressors affecting stream biota. Several methods exist to quantify stream sediment embeddedness, but they are relatively qualitative and operationally defined. The authors developed a short-term in situ embeddedness chamber method to measure aquatic insect recruitment and associated sediment accumulation in a more quantitative, better replicated manner. With sediment accumulation and aquatic insect recruitment as endpoints, three exposure periods were evaluated (4, 7, and 14 d) on a low-order stream (Honey Creek, New Carlisle, Ohio, USA) and a medium-order stream (Stillwater River, Covington, Ohio, USA). Chamber results show significant positive correlations between newly deposited fine sediment and insect recruitment. Embeddedness was also measured using the more conventional techniques of the Burns method and the U.S. Geological Survey National Water Quality Assessment Program method. This in situ chamber method allows for increased experimental options for assessing the stress of embeddedness and siltation on benthic communities and may prove useful for investigating the resilience of benthic communities after disturbances.

Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition

Stream indicators used to make assessments of biological condition are influenced by many possible sources of variability. To examine this issue, we used multiple-year and multiple-reach diatom, fish, and invertebrate data collected from 20 least-disturbed and 46 developed stream segments between 1993 and 2004 as part of the US Geological Survey National Water Quality Assessment Program. We used a variance-component model to summarize the relative and absolute magnitude of 4 variance components (among-site, among-year, site × year interaction, and residual) in indicator values (observed/expected ratio [O/E] and regional multimetric indices [MMI]) among assemblages and between basin types (least-disturbed and developed). We used multiple-reach samples to evaluate discordance in site assessments of biological condition caused by sampling variability. Overall, patterns in variance partitioning were similar among assemblages and basin types with one exception. Among-site variance dominated the relative contribution to the total variance (64–80% of total variance), residual variance (sampling variance) accounted for more variability (8–26%) than interaction variance (5–12%), and among-year variance was always negligible (0–0.2%). The exception to this general pattern was for invertebrates at least-disturbed sites where variability in O/E indicators was partitioned between among-site and residual (sampling) variance (among-site = 36%, residual = 64%). This pattern was not observed for fish and diatom indicators (O/E and regional MMI). We suspect that unexplained sampling variability is what largely remained after the invertebrate indicators (O/E predictive models) had accounted for environmental differences among least-disturbed sites. The influence of sampling variability on discordance of within-site assessments was assemblage or basin-type specific. Discordance among assessments was nearly 2× greater in developed basins (29–31%) than in least-disturbed sites (15–16%) for invertebrates and diatoms, whereas discordance among assessments based on fish did not differ between basin types (least-disturbed = 16%, developed = 17%). Assessments made using invertebrate and diatom indicators from a single reach disagreed with other samples collected within the same stream segment nearly ⅓ of the time in developed basins, compared to ⅙ for all other cases.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions1

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks.

Among‐Pass, Interregional, and Single‐ versus Multiple‐Season Comparisons of Detection Probabilities of Stream Fishes

AbstractUnequal detection of stream fishes must be accounted for when estimating assemblage composition. Detection probabilities (p) may differ among electrofishing passes, regions, and methods of estimation. We used data sets collected from (1) the middle New River basin, Virginia, using three‐pass electrofishing; (2) the upper Wabash River system of northern Indiana, using the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) protocol; and (3) the NAWQA database, collected throughout the United States. We tested for among‐pass differences in p using the New River data set. To test for interregional differences, we compared average detection probability (pavg) between the New and Wabash river data sets. We compared single‐ and multiple‐season estimates using the New River and NAWQA data sets. We found no differences among pass‐specific p for 97% of the species in the New River data set. No significant differences in pavg were found between the New and Wabash river systems for 73% of the species shared by the two data sets. Single‐season estimates of pavg did not differ from multiple‐season estimates of p for 86% of the species found in both data sets. Two of the three species for which single‐ and multiple‐season estimates of p differed also had interregional differences. Differences in pass‐specific detection probabilities may be attributable to decreased abundance or behavioral changes in subsequent passes. Interregional differences may be attributable to dissimilarities in abundance, habitat, or sampling protocols between the two systems. Similar factors may have affected single‐ versus multiple‐season comparisons. Our results show that p does not significantly differ among electrofishing passes in three‐pass samples for most species and that pavg from single‐season data is comparable to p from multiple‐season data sets. More research is needed to determine whether differences in p across regions are common. Our approach provides a relatively quick and reliable method for estimating the detection probabilities of stream fishes and will benefit managers who seek to attain accurate estimates of stream fish assemblage composition while making the best use of their time and resources.

Non-native fishes and native species diversity in freshwater fish assemblages across the United States

The proliferation of non-native species in North American freshwater ecosystems is considered a primary threat to the integrity of native community structure. However, a general understanding of consistent and predictable impacts of non-native species on native freshwater diversity is limited, in part, because of a lack of broad-scale studies including data from numerous localities across multiple drainages. This study uses data from 751 localities collected during the United States Geological Survey (USGS) National Water Quality Assessment (NAWQA) program to examine the influence of non-native fish species on native freshwater fish assemblages across the United States. In general, no significant differences in native fish richness and diversity measures were detected between sites with only native species and sites containing non-native species. However, at sites with non-native species, the number of non-native species present was negatively correlated with native species richness and Shannon diversity and positively correlated with native evenness. Non-native piscivores were negatively correlated with native species richness and Shannon diversity and positively correlated with native evenness. Native piscivores were positively correlated with native richness and diversity and negatively correlated with native evenness at sites with only native species. Our results suggest that from a superficial perspective, native species richness and diversity are not different among sites with and without non-native species. However, when patterns of native species richness and diversity are examined at sites containing non-native species, correlations between non-native and native species richness and diversity imply the expected negative effect of invasive taxa. Additionally, non-native piscivores appear to have a significant negative effect on native taxa and possibly represent a novel selective force on naive native prey.

Evaluation of Intra‐annual Variation in U.S. Geological Survey National Water Quality Assessment Ground Water Quality Data

Assessment of ground-water quality trends under the U.S. Geological Survey National Water-Quality Assessment Program (NAWQA) included the analysis of samples collected on a quarterly basis for 1 yr between 2001 and 2005. The purpose of this quarterly sampling was to test the hypothesis that variations in the concentration of water-quality parameters of selected individual wells could demonstrate that the intra-annual variation was greater or less than the decadal changes observed for a trend network. Evaluation of more than 100 wells over this period indicates that 1 yr of quarterly sampling is not adequate to address the issue of intra-annual variation because variations seem to be random and highly variable between different wells in the same networks and among networks located in different geographical areas of the USA. In addition, the data from only 1 yr makes it impossible to assess whether variations are due to univariate changes caused by land use changes, hydrologic variations due to variable recharge, or variations caused by ground-water pumping. These data indicate that funds allocated to this activity can be directed to the collection of more effective trend data, including age dating of all wells in the NAWQA network using multiple techniques. Continued evaluation of data and updating of monitoring plans of the NAWQA program is important for maintaining relevance to national goals and scientific objectives.

Health‐Based Screening Levels to Evaluate U.S. Geological Survey Ground water Quality Data

Federal and state drinking-water standards and guidelines do not exist for many contaminants analyzed by the U.S. Geological Survey's National Water-Quality Assessment Program, limiting the ability to evaluate the potential human-health relevance of water-quality findings. Health-based screening levels (HBSLs) were developed collaboratively to supplement existing drinking-water standards and guidelines as part of a six-year, multi-agency pilot study. The pilot study focused on ground water samples collected prior to treatment or blending in areas of New Jersey where groundwater is the principal source of drinking water. This article describes how HBSLs were developed and demonstrates the use of HBSLs as a tool for evaluating water-quality data in a human-health context. HBSLs were calculated using standard U.S. Environmental Protection Agency (USEPA) methodologies and toxicity information. New HBSLs were calculated for 12 of 32 contaminants without existing USEPA drinking-water standards or guidelines, increasing the number of unregulated contaminants (those without maximum contaminant levels (MCLs)) with human-health benchmarks. Concentrations of 70 of the 78 detected contaminants with human-health benchmarks were less than MCLs or HBSLs, including all 12 contaminants with new HBSLs, suggesting that most contaminant concentrations were not of potential human-health concern. HBSLs were applied to a state-scale groundwater data set in this study, but HBSLs also may be applied to regional and national evaluations of water-quality data. HBSLs fulfill a critical need for federal, state, and local agencies, water utilities, and others who seek tools for evaluating the occurrence of contaminants without drinking-water standards or guidelines.