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At least 253 records · Page 14Linked to original sources
USGS2023

Doing the same thing over and over again and getting the same result: Assessing variance in wetland invertebrate assemblages

Past efforts to explain variation of invertebrate assemblages in freshwater wetlands have been less productive than anticipated. To explore why efforts are disappointing, we assembled large invertebrate data sets from North Dakota prairie potholes, California rock pools, and Georgia Carolina bay wetlands that addressed spatial (among wetlands) and temporal (among seasons and years) variation. We anticipated that these large data-set sizes would enable robust conclusions to be drawn, and each place had unique environmental conditions that might contribute to greater explanatory power. We used statistical techniques that partitioned variation in invertebrate assemblages into spatial and/or temporal components, and that also yielded a measure of the amount of unexplained variation; Permutational Multivariate Analysis of Variation and Principal Coordinates Analysis assessed whole assemblage variation, and Analysis of Variance or Analysis of Covariance assessed variation in taxon richness, total abundances, and abundances of wide-spread individual taxa. Across all locations, variation explained by spatial and temporal factors, and unexplained variation were of comparable magnitudes (i.e., similar R 2 values of ~ 50%). Review of other published studies indicate that this pattern is widespread. The 50% or more unexplained variation is typically ignored by researchers, who instead focus on explained fractions. We argue that, besides addressing explained spatial and temporal variation in invertebrate assemblages (e.g., control by hydrology, resources, predation), efforts to understand what contributes to currently unexplained variation, that is unrelated to local spatial or temporal controls (e.g., broad climatic and biogeographic patterns, organism physiology and behavior), will lead to a fuller comprehension of how invertebrates in freshwater wetlands are controlled.

Wetlands↗
USGS2019

Simultaneous autoregressive (SAR) model

Simultaneous autoregressive (SAR) models are useful for accommodating various forms of dependence among data that have discrete support in a space of interest. These models are often specified hierarchically as mixed-effects regression models with first-moment structure controlled by a conventional linear regression term and second-moment structure induced by correlated random effects. In their general form, SAR models resemble conditional autoregressive (CAR) models, and can be made equivalent but are often parameterized differently. Importantly, SAR models can be specified by simultaneously regressing a discrete spatial process on itself. Thus, they allow one to construct statistical models for processes with directional graphical properties that pertain to data generating mechanisms. Most commonly SAR models have been used to account for structure among data with areal spatial support in applications involving ecology, epidemiology, sociology, and environmental science.

Book chapter↗
USGS2017

Status and understanding of groundwater quality in the Bear Valley and Lake Arrowhead Watershed Study Unit, 2010: California GAMA Priority Basin Project

Groundwater quality in the 112-square-mile Bear Valley and Lake Arrowhead Watershed (BEAR) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit comprises two study areas (Bear Valley and Lake Arrowhead Watershed) in southern California in San Bernardino County. The GAMA-PBP is conducted by the California State Water Resources Control Board (SWRCB) in cooperation with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The GAMA BEAR study was designed to provide a spatially balanced, robust assessment of the quality of untreated (raw) groundwater from the primary aquifer systems in the two study areas of the BEAR study unit. The assessment is based on water-quality collected by the USGS from 38 sites (27 grid and 11 understanding) during 2010 and on water-quality data from the SWRCB-Division of Drinking Water (DDW) database. The primary aquifer system is defined by springs and the perforation intervals of wells listed in the SWRCB-DDW water-quality database for the BEAR study unit. This study included two types of assessments: (1) a status assessment , which characterized the status of the quality of the groundwater resource as of 2010 by using data from samples analyzed for volatile organic compounds, pesticides, and naturally present inorganic constituents, such as major ions and trace elements, and (2) an understanding assessment , which evaluated the natural and human factors potentially affecting the groundwater quality. The assessments were intended to characterize the quality of groundwater resources in the primary aquifer system of the BEAR study unit, not the treated drinking water delivered to consumers. Bear Valley study area and the Lake Arrowhead Watershed study area were also compared statistically on the basis of water-quality results and factors potentially affecting the groundwater quality. Relative concentrations (RCs), which are sample concentration of a particular constituent divided by its associated health- or aesthetic-based benchmark concentrations, were used for evaluating the groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. An RC greater than 1.0 indicates a concentration greater than a benchmark. Organic (volatile organic compounds and pesticides) and special-interest (perchlorate) constituent RCs were classified as “high” (RC greater than 1.0), “moderate” (RC less than or equal to 1.0 and greater than 0.1), or “low” (RC less than or equal to 0.1). For inorganic (radioactive, trace element, major ion, and nutrient) constituents, the boundary between low and moderate RCs was set at 0.5. Aquifer-scale proportion was used as the primary metric in the status assessment for evaluating groundwater quality at the study-unit scale or for its component areas. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a RC greater than 1.0 for a particular constituent or class of constituents; the percentage is based on area rather than volume. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low RCs, respectively. A spatially weighted statistical approach was used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. The status assessment for the Bear Valley study area found that inorganic constituents with health-based benchmarks were detected at high RCs in 9.0 percent of the primary aquifer system and at moderate RCs in 13 percent. The high RCs of inorganic constituents primarily reflected high aquifer-scale proportions of fluoride (in 5.4 percent of the primary aquifer system) and arsenic (3.6 percent). The RCs of organic constituents with health-based benchmarks were high in 1.0 percent of the primary aquifer system, moderate in 8.1 percent, and low in 70 percent. Organic constituents were detected in 79 percent of the primary aquifer system. Two groups of organic constituents and two individual organic constituents were detected at frequencies greater than 10 percent of samples from the USGS grid sites: trihalomethanes (THMs), solvents, methyl tert -butyl ether (MTBE), and simazine. The special-interest constituent perchlorate was detected in 93 percent of the primary aquifer system; it was detected at moderate RCs in 7.1 percent and at low RCs in 86 percent. The status assessment in the Lake Arrowhead Watershed study area showed that inorganic constituents with human-health benchmarks were detected at high RCs in 25 percent of the primary aquifer system and at moderate RCs in 41 percent. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of radon‑222 (in 62 percent of the primary aquifer system) and uranium (26 percent). RCs of organic constituents with health-based benchmarks were moderate in 7.7 percent of the primary aquifer system and low in 46 percent. Organic constituents were detected in 54 percent of the primary aquifer system. The only organic constituents that were detected at frequencies greater than 10 percent of samples from the USGS grid sites were THMs. Perchlorate was detected in 62 percent of the primary aquifer system at uniformly low RCs. The second component of this study, the understanding assessment , identified the natural and human factors that could have affected the groundwater quality in the BEAR study unit by evaluating statistical correlations between water-quality constituents and potential explanatory factors. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), site type, aquifer lithology, well construction (well depth and depth to the top-of-perforated interval), elevation, aridity index, groundwater-age distribution, and oxidation-reduction condition (including pH and dissolved oxygen concentration). Results of the statistical evaluations were used to explain the distribution of constituents in groundwater of the BEAR study unit. In the Bear Valley study area, high and moderate RCs of fluoride were found in sites known to be influenced by hydrothermic conditions or that had high concentrations of fluoride historically. The high RC of arsenic can likely be attributed to desorption of arsenic from aquifer sediments saturated in old groundwater with high pH under reducing conditions. The THMs were detected more frequently at USGS grid sites that were wells, part of a large urban water system, and surrounded by urban land use. Solvents, MTBE, and simazine were all detected more frequently at USGS grid sites that were wells with a greater urban percentage of surrounding land use and that accessed older groundwater than other USGS grid sites. Comparison between the observed and predicted detection frequencies of perchlorate at USGS grid sites indicated that anthropogenic sources could have contributed to low levels of perchlorate in the groundwater of the Bear Valley study area. In the Lake Arrowhead Watershed study area, high and moderate RCs of radon-222 and uranium can be attributed to older groundwater from the granitic fractured-rock primary aquifer system. Low RCs of THMs were detected at USGS grid sites that were wells and part of small water systems. The similarities between the observed and predicted detection frequencies of perchlorate in samples from USGS grid sites indicated that the source and distribution of perchlorate were most likely attributable to precipitation (rain and snow), with minimal, if any, contribution from anthropogenic sources.

California↗
USGS1974

An assessment of areal and temporal variations in streamflow quality using selected data from the National Stream Quality Accounting Network

Streamflow chemical-quality data and stream-temperature data at 88 stations throughout the United States and Puerto Rico were analyzed to develop and to evaluate methodologies for the general assessment of the variation of the Nation's streamflow-quality conditions in space and over time. The spatial variation is described by the use of sample statistics such as minima, maxima, and means of the variables at each station. The temporal variation is described by using nonparametric statistical testing procedures to assess time trends in the data at each station. Evaluation of the coefficients (mean, amplitude, phase coefficient] derived by harmonic analysis of available daily stream-temperature records indicates adequate depiction of yearly seasonal variability and provides information relative to spatial variation in stream temperatures at most sites. Lowest harmonic amplitudes, which are indicative of little seasonal variability in stream temperature, were observed in Florida, along the eastern Gulf coast, and along the Pacific coast. Greatest annual variations in stream temperature exists in the Souris, Red (of the North), and Missouri River basins. Temporal variations in stream temperature denoted by significant changes (at the 99 percent level of confidence) in annual harmonic coefficients were indicated at 15 of 80 stations used in the evaluation. Trends in stream temperature were found to exist at one or more stations in each of the six following areas: the Atlantic coast above Florida; Florida and the eastern Gulf; the Souris River, Red River of the North, and Missouri River basins; the Texas Gulf and Rio Grande area; the Colorado River basin; and the Pacific coast area. Significant trends (at the 99 percent level of confidence) were found in the long-term streamflow chemical quality record at 15 of 88 stations analyzed. Of these stations, 10 showed an increase in levels of specific conductances while 5- showed a decrease. Trends were indicated for water-quality data from stations located in the following areas: the Atlantic coast above Florida; the Souris River, Red River of the North, and Missouri River basins; the Arkansas and Red River basins; the Texas Gulf and Rio Grande area; the Colorado River basin; and the Pacific coast area.

Open-File Report↗
USGS2018

Comparison of HSPF and PRMS model simulated flows using different temporal and spatial scales in the Black Hills, South Dakota

The hydrological simulation program Fortran ( HSPF ) [ Hydrological Simulation Program Fortran version 12.2 (Computer software). USEPA, Washington, DC] and the precipitation runoff modeling system ( PRMS ) [ Precipitation Runoff Modeling System version 4.0 (Computer software). USGS, Reston, VA] models are semidistributed, deterministic hydrological tools for simulating the impacts of precipitation, land use, and climate on basin hydrology and streamflow. Both models have been applied independently to many watersheds across the United States. This paper reports the statistical results assessing various temporal (daily, monthly, and annual) and spatial (small versus large watershed) scale biases in HSPF and PRMS simulations using two watersheds in the Black Hills, South Dakota. The Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient ( r "> r r ), and coefficient of determination ( R 2 "> R 2 R2 ) statistics for the daily, monthly, and annual flows were used to evaluate the models’ performance. Results from the HSPF models showed that the HSPF consistently simulated the annual flows for both large and small basins better than the monthly and daily flows, and the simulated flows for the small watershed better than flows for the large watershed. In comparison, the PRMS model results show that the PRMS simulated the monthly flows for both the large and small watersheds better than the daily and annual flows, and the range of statistical error in the PRMS models was greater than that in the HSPF models. Moreover, it can be concluded that the statistical error in the HSPF and the PRMS daily, monthly, and annual flow estimates for watersheds in the Black Hills was influenced by both temporal and spatial scale variability.

South Dakota↗
USGS2019

Long-term trajectories of fractional component change in the Northern Great Basin, USA

The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the northern Great Basin from 1986 to 2016 using a dense Landsat imagery time-series. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified by climate bin and assess spatial and temporal relationships with climate variables. Finally, we statistically evaluate the minimum time density needed to accurately characterize temporal patterns and relationships with climate drivers. Over the 30-year period shrub cover declined and bare ground increased. While few pixels had > 10% cover change, a large majority had at least some change. All fractional components had significant spatial relationships with water year precipitation (WYPRCP), maximum temperature (WYTMAX), and minimum temperature (WYTMIN) in all years. Shrub and sagebrush cover in particular respond positively to warming WYTMIN, resulting from the largest increases in WYTMIN being in the coolest and wettest areas, and negatively to warming WYTMAX since the largest increases in WYTMAX are in the warmest and driest areas. The trade-off of lowering temporal density against removing cloud-contaminated years is justified as temporal density appears to have only a modest impact on trends and climate relationships until n ≤ 6, but multi-year gaps are proportionally more influential. Gradual change analysis is likely to be less sensitive to n than abrupt change. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices.

California, Idaho, Nevada, Oregon, Utah↗
USGS2008

Kolmogorov-Smirnov test for spatially correlated data

The Kolmogorov-Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov-Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size. ?? Springer-Verlag 2008.

Stochastic Environmental Research and Risk Assessm↗
USGS2008

Seabed mapping and characterization of sediment variability using the usSEABED data base

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character.

Continental Shelf Research↗
USGS2019

POLARIS properties: 30-meter probabilistic maps of soil properties over the contiguous United States

Soils play a critical role in the cycling of water, energy, and carbon in the Earth system. Until recently, due primarily to a lack of soil property maps of a sufficiently high‐quality and spatial detail, a minor emphasis has been placed on providing high‐resolution measured soil parameter estimates for land surface models and hydrologic models. This study introduces Probabilistic Remapping of SSURGO (POLARIS) soil properties—a database of 30‐m probabilistic soil property maps over the contiguous United States (CONUS). The mapped variables over CONUS include soil texture, organic matter, pH, saturated hydraulic conductivity, Brooks‐Corey and Van Genuchten water retention curve parameters, bulk density, and saturated water content. POLARIS soil properties was assembled by (1) depth harmonizing and aggregating the pedons in the National Cooperative Soil Survey Soil Characterization Database and the components in Soil Survey Geographic Database into a database of 21,481 different soil series, each soil series having its own vertical profiles of different soil properties, (2) pruning the original POLARIS soil series maps using conventional soil maps to improve soil series prediction accuracy, and (3) merging the assembled soil series databases with the pruned POLARIS soil series maps to construct the soil property maps over CONUS. POLARIS soil properties includes 100‐bin histograms for each layer and variable per grid cell and a series of summary statistics at 30‐, 300‐, and 3,000‐m spatial resolution. Evaluation of POLARIS soil properties using in situ measurements shows an average R2 of 0.41, normalized root‐mean‐square error of 12%, and a normalized mean absolute error of 8.8%.

Water Resources Research↗
USGS2008

Ground-water quality data in the southeast San Joaquin Valley, 2005–2006— Results from the California GAMA program

Ground-water quality in the approximately 3,800 square-mile Southeast San Joaquin Valley study unit (SESJ) was investigated from October 2005 through February 2006 as part of the Priority Basin Assessment Project of Ground-Water Ambient Monitoring and Assessment (GAMA) Program. The GAMA Statewide Basin Assessment project was developed in response to the Ground-Water Quality Monitoring Act of 2001 and is being conducted by the California State Water Resources Control Board (SWRCB) in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory (LLNL). The SESJ study was designed to provide a spatially unbiased assessment of raw ground-water quality within SESJ, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 99 wells in Fresno, Tulare, and Kings Counties, 83 of which were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and 16 of which were sampled to evaluate changes in water chemistry along ground-water flow paths or across alluvial fans (understanding wells). The ground-water samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, and pharmaceutical compounds), constituents of special interest (perchlorate, N-nitrosodimethylamine, and 1,2,3-trichloropropane), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial indicators. Naturally occurring isotopes (tritium, and carbon-14, and stable isotopes of hydrogen, oxygen, nitrogen, and carbon), and dissolved noble gases also were measured to help identify the source and age of the sampled ground water. Quality-control samples (blanks, replicates, samples for matrix spikes) were collected at approximately 10 percent of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Assessment of the quality-control data resulted in censoring of less than 1 percent of the detections of constituents measured in ground-water samples. This study did not attempt to evaluate the quality of drinking water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, and (or) blended with other waters to maintain acceptable drinking-water quality. Regulatory thresholds apply to the treated water that is served to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with regulatory and other health-based thresholds established by the U.S. Environmental Protection Agency and California Department of Public Health (CDPH) and thresholds established for aesthetic concerns by CDPH. Two VOCs were detected above health-based thresholds: 1,2-dibromo-3-chloropropane (DBCP), and benzene. DBCP was detected above the U.S. Environmental Protections Agency’s maximum contaminant level (MCL-US) in three grid wells and five understanding wells. Benzene was detected above the CDPH’s maximum contaminant level (MCL-CA) in one grid well. All pesticide detections were below health-based thresholds. Perchlorate was detected above its maximum contaminate level for California in one grid well. Nitrate was detected above the MCL-US in six samples from understanding wells, of which one was a public supply well. Two trace elements were detected above MCLs-US: arsenic and uranium. Arsenic was detected above the MCL-US in four grid wells and two understanding wells; uranium was detected above the MCL-US in one grid well and one understanding well. Gross alpha radiation was detected above MCLs-US in five samples; four of them understanding wells, and uranium isotope activity was greater than the MCL-US for one understanding well. Radon-222 was detected above the proposed MCL-US in all wells sampled. Total coliforms were detected in two wells and somatic coliphage was detected in one well.

California↗
USGS2009

Ground-water quality data in the San Francisco Bay study unit, 2007: Results from the California GAMA Program

Ground-water quality in the approximately 620-square-mile San Francisco Bay study unit (SFBAY) was investigated from April through June 2007 as part of the Priority Basin project of the Ground-Water Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin project was developed in response to the Groundwater Quality Monitoring Act of 2001, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The study was designed to provide a spatially unbiased assessment of raw ground-water quality, as well as a statistically consistent basis for comparing water quality throughout California. Samples in SFBAY were collected from 79 wells in San Francisco, San Mateo, Santa Clara, Alameda, and Contra Costa Counties. Forty-three of the wells sampled were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells). Thirty-six wells were sampled to aid in evaluation of specific water-quality issues (understanding wells). The ground-water samples were analyzed for a large number of synthetic organic constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, pharmaceutical compounds, and potential wastewater-indicator compounds), constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]), naturally occurring inorganic constituents (nutrients, major and minor ions, trace elements, chloride and bromide isotopes, and uranium and strontium isotopes), radioactive constituents, and microbial indicators. Naturally occurring isotopes (tritium, carbon-14 isotopes, and stable isotopes of hydrogen, oxygen, nitrogen, boron, and carbon), and dissolved noble gases (noble gases were analyzed in collaboration with Lawrence Livermore National Laboratory) also were measured to help identify the source and age of the sampled ground water. Quality-control samples (blank samples, replicate samples, matrix spike samples) were collected for approximately one-third of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Assessment of the quality-control information from the field blanks resulted in applying “V” codes to approximately 0.1 percent of the data collected for ground-water samples (meaning a constituent was detected in blanks as well as the corresponding environmental data). See the Appendix section “Quality-Control-Sample Results.” This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, and (or) blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to treated water that is delivered to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. VOCs were detected in about one-half of the grid wells, while pesticides were detected in about one-fifth of the grid wells. Concentrations of all VOCs and pesticides detected in samples from all SFBAY wells were below health-based thresholds. No pharmaceutical compounds were detected in any SFBAY well. One potential wastewater-indicator compound, caffeine, was detected in one grid well in SFBAY. Concentrations of most trace elements and nutrients detected in samples from all SFBAY wells were below health-based thresholds. Exceptions include nitrate, detected above the USEPA maximum contaminant level (MCL-US) in 3samples; arsenic, above the USEPA maximum contaminant level (MCL-US) in 3 samples; cadmium, above the MCL-US in 1 sample; boron, above the CDPH notification level (NL-CA) in 2 samples; and strontium, above the USEPA lifetime health advisory level (HAL-US) in 2 samples. The radioactive constituent radon-222 was detected above the proposed MCL-US in two grid wells, but no wells had detections above the proposed alternative MCL-US. Most of the samples from all SFBAY wells had concentrations of major ions, total dissolved solids, and trace elements below the non-enforceable thresholds set for aesthetic concerns. Six or fewer samples contained chloride, sulfate, or iron at concentrations above the SMCL-CA thresholds. No microbial indicators were detected in SFBAY grid wells.

California↗
USGS2008

Ground-water quality data in the San Fernando-San Gabriel study unit, 2005— Results from the California GAMA program

Ground-water quality in the approximately 460 square mile San Fernando-San Gabriel study unit (SFSG) was investigated between May and July 2005 as part of the Priority Basin Assessment Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Assessment Project was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The San Fernando-San Gabriel study was designed to provide a spatially unbiased assessment of raw ground-water quality within SFSG, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 52 wells in Los Angeles County. Thirty-five of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (grid wells), and seventeen wells were selected to aid in the evaluation of specific water-quality issues or changes in water chemistry along a historic ground-water flow path (understanding wells). The ground-water samples were analyzed for a large number of synthetic organic constituents [volatile organic compounds (VOCs), pesticides and pesticide degradates], constituents of special interest [perchlorate, N-nitrosodimethylamine (NDMA), 1,2,3-trichloropropane (1,2,3-TCP), and 1,4-dioxane], naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial indicators. Naturally occurring isotopes (tritium, and carbon-14, and stable isotopes of hydrogen, oxygen, and carbon), and dissolved noble gases also were measured to help identify the source and age of the sampled ground water. Quality-control samples (blanks, replicates, samples for matrix spikes) were collected at approximately one-fifth (11 of 52) of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Assessment of the quality-control results showed that the data had very little bias or variability and resulted in censoring of less than 0.7 percent (32 of 4,484 measurements) of the data collected for ground-water samples. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, or blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to treated water that is served to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH) and thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. VOCs were detected in more than 90 percent (33 of 35) of grid wells. For all wells sampled for SFSG, nearly all VOC detections were below health-based thresholds, and most were less than one-tenth of the threshold values. Samples from seven wells had at least one detection of PCE, TCE, tetrachloromethane, NDMA, or 1,2,3-TCP at or above a health-based threshold. Pesticides were detected in about 90 percent (31 of 35) grid wells and all detections in samples from SFSG wells were below health-based thresholds. Major ions, trace elements, and nutrients in samples from 17 SFSG wells were all below health-based thresholds, with the exception of one detection of nitrate that was above the USEPA maximum contaminant level (MCL-US). With the exception of 14 samples having radon-222 above the proposed MCL-US, radioactive constituents were below health-based thresholds for 16 of the SFSG wells sampled. Total dissolved solids in 6 of the 24 SFSG wells that were sampled ha

California↗
USGS2009

Ground-Water Quality Data in the Upper Santa Ana Watershed Study Unit, November 2006-March 2007: Results from the California GAMA Program

Ground-water quality in the approximately 1,000-square-mile Upper Santa Ana Watershed study unit (USAW) was investigated from November 2006 through March 2007 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin project was developed in response to the Groundwater Quality Monitoring Act of 2001, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The Upper Santa Ana Watershed study was designed to provide a spatially unbiased assessment of raw ground-water quality within USAW, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 99 wells in Riverside and San Bernardino Counties. Ninety of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells). Nine wells were selected to provide additional understanding of specific water-quality issues identified within the basin (understanding wells). The ground-water samples were analyzed for a large number of organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, pharmaceutical compounds, and potential wastewater-indicator compounds), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], 1,4-dioxane, and 1,2,3-trichloropropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial indicators. Naturally occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) and dissolved noble gases also were measured to help identify sources and ages of the sampled ground water. Dissolved gases, and isotopes of nitrogen gas and of dissolved nitrate also were measured in order to investigate the sources and occurrence of nitrate in the study unit. In total, nearly 400 constituents and water-quality indicators were investigated for this study. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, and (or) blended with other waters to maintain acceptable water quality. Regulatory thresholds apply to treated water that is served to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and the California Department of Public Health (CDPH) and thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. Volatile organic compounds (VOCs) were detected in more than 80 percent of USAW grid wells. Most VOCs detected were at concentrations far less than thresholds established for drinking water to protect human health; however, six wells had VOC concentrations above health-based thresholds. Twenty-four of the 85 VOCs investigated were detected in the study unit;11 were detected in more than 10 percent of the wells. The VOCs detected above health-based thresholds in at least one well were dibromochloropropane (DBCP), tetrachloroethene (PCE), trichloroethene (TCE), carbon tetrachloride, and 1,1-dichoroethene. Pesticide compounds were detected in more than 75 percent of the grid wells. However, of the 134 different pesticide compounds investigated, 13 were detected at concentrations greater than their respective long-term method detection limits, and only 7 compounds (all herbicides or herbicide degradates) were detected in more than 10 percent of the wells. No pesticide compound was detected above its health-based threshold, although thresholds exist for fewer than half of the pesticide compounds investigat

Data Series↗
USGS2013

Limitation and facilitation of one of the world's most invasive fish: an intercontinental comparison

Purposeful species introductions offer opportunities to inform our understanding of both invasion success and conservation hurdles. We evaluated factors determining the energetic limitations of brown trout (Salmo trutta) in both their native and introduced ranges. Our focus was on brown trout because they are nearly globally distributed, considered one of the world's worst invaders, yet imperiled in much of their native habitat. We synthesized and compared data describing temperature regime, diet, growth, and maximum body size across multiple spatial and temporal scales, from country (both exotic and native habitats) and major geographic area (MGA) to rivers and years within MGA. Using these data as inputs, we next used bioenergetic efficiency (BioEff), a relative scalar representing a realized percentage of maximum possible consumption (0–100%) as our primary response variable and a multi-scale, nested, mixed statistical model (GLIMMIX) to evaluate variation among and within spatial scales and as a function of density and elevation. MGA and year (the residual) explained the greatest proportion of variance in BioEff. Temperature varied widely among MGA and was a strong driver of variation in BioEff. We observed surprisingly little variation in the diet of brown trout, except the overwhelming influence of the switch to piscivory observed only in exotic MGA. We observed only a weak signal of density-dependent effects on BioEff; however, BioEff remained <50% at densities >2.5 fish/m2. The trajectory of BioEff across the life span of the fish elucidated the substantial variation in performance among MGAs; the maximum body size attained by brown trout was consistently below 400 mm in native habitat but reached 600 mm outside their native range, where brown trout grew rapidly, feeding in part on naive prey fishes. The integrative, physiological approach, in combination with the intercontinental and comparative nature of our study, allowed us to overcome challenges associated with context-dependent variation in determining invasion success. Overall our results indicate “growth plasticity across the life span” was important for facilitating invasion, and should be added to lists of factors characterizing successful invaders.

Ecology↗
USGS2014

Predicting spatial and temporal distribution of Indo-Pacific lionfish ( Pterois volitans ) in Biscayne Bay through habitat suitability modeling

Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish ( Pterois volitans ) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.

Florida↗
USGS2008

Ground-water quality data in the coastal Los Angeles Basin study unit, 2006: Results from the California GAMA Program

Ground-water quality in the approximately 860 square-mile Coastal Los Angeles Basin study unit (CLAB) was investigated from June to November of 2006 as part of the Statewide Basin Assessment Project of the Ground-Water Ambient Monitoring and Assessment (GAMA) Program. The GAMA Statewide Basin Assessment was developed in response to the Ground-Water Quality Monitoring Act of 2001, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The Coastal Los Angeles Basin study was designed to provide a spatially unbiased assessment of raw ground-water quality within CLAB, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 69 wells in Los Angeles and Orange Counties. Fifty-five of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study area (?grid wells?). Fourteen additional wells were selected to evaluate changes in ground-water chemistry or to gain a greater understanding of the ground-water quality within a specific portion of the Coastal Los Angeles Basin study unit ('understanding wells'). Ground-water samples were analyzed for: a large number of synthetic organic constituents [volatile organic compounds (VOCs), gasoline oxygenates and their degradates, pesticides, polar pesticides, and pesticide degradates, pharmaceutical compounds, and potential wastewater-indicators]; constituents of special interest [perchlorate, N-nitrosodimethylamine (NDMA), 1,4-dioxane, and 1,2,3-trichloropropane (1,2,3-TCP)]; inorganic constituents that can occur naturally [nutrients, major and minor ions, and trace elements]; radioactive constituents [gross-alpha and gross-beta radiation, radium isotopes, and radon-222]; and microbial indicators. Naturally occurring isotopes [stable isotopic ratios of hydrogen and oxygen, and activities of tritium and carbon-14] and dissolved noble gases also were measured to help identify the sources and ages of the sampled ground water. Quality-control samples (blanks, replicates, and samples for matrix spikes) were collected at approximately one-fourth of the wells, and the results for these samples were used to evaluate the quality of the data for the ground-water samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination was not a significant source of bias. Differences between replicate samples were within acceptable ranges, indicating acceptably low variability. Matrix spike recoveries were within acceptable ranges for most compounds. Assessment of the quality-control information resulted in applying ?V? codes to approximately 0.1 percent of the data collected for ground-water samples (meaning a constituent was detected in blanks as well as the corresponding environmental data). This study did not attempt to evaluate the quality of drinking water delivered to consumers; after withdrawal from the ground, water typically is treated, disinfected, and (or) blended with other waters to maintain acceptable drinking-water quality. Regulatory thresholds are applied to the treated drinking water that is served to the consumer, not to raw ground water. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA), California Department of Public Health (CDPH, formerly California Department of Health Services [CADHS]) and thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. Comparisons between data collected for this study and drinking-water thresholds are for illustrative purposes only, and are not indicative of compliance or non-compliance with those thresholds. VOCs were detected in alm

California↗
USGS2004

Challenging the assumption of habitat limitation: An example from centrarchid fishes over an intermediate spatial scale

Habitat rehabilitation efforts are predicated on the frequently untested assumption that habitat is limiting to populations. These efforts are typically costly and will be ineffective if habitat is not limiting. Therefore it is important to assess, rather than assume, habitat limitation wherever habitat rehabilitation projects are considered. Catch-count data from a standardized probability-based stratified-random monitoring programme were examined for indirect evidence of backwater habitat limitation by centrarchid fishes in the Upper Mississippi River System. The monitoring design enabled fitting statistical models of the association between mean catch at the spatial scale of tens of river kilometres and the percentage of contiguous aquatic area in backwater at least 1 m deep by maximizing a stratum-area weighted negative binomial log-likelihood function. Statistical models containing effects for backwater limitation failed to account for substantial variation in the data. However, 95% confidence intervals on the backwater parameter estimates excluded zero, indicating that population abundance may be limited by backwater prevalence where backwaters are extremely scarce. The combined results indicate, at most, a weak signal of backwater limitation where backwaters are extremely scarce in the lower reaches, but not elsewhere in the Upper Mississippi River System. This suggests that habitat restoration projects designed to increase the area of backwaters suitable for winter survival of centrarchids are unlikely to produce measurable benefits over intermediate spatial scales in much of the Upper Mississippi River System, and indicates the importance of correct identification of limiting processes. Published in 2004 by John Wiley and Sons, Ltd.

River Research and Applications↗
USGS2020

Reptiles under the conservation umbrella of the greater sage‐grouse

In conservation paradigms, management actions for umbrella species also benefit co‐occurring species because of overlapping ranges and similar habitat associations. The greater sage‐grouse ( Centrocercus urophasianus ) is an umbrella species because it occurs across vast sagebrush ecosystems of western North America and is the recipient of extensive habitat conservation and restoration efforts that might benefit sympatric species. Biologists' understanding of how non‐target species might benefit from sage‐grouse conservation is, however, limited. Reptiles, in particular, are of interest in this regard because of their relatively high diversity in shrublands and grasslands where sage‐grouse are found. Using spatial overlap of species distributions, land cover similarity statistics, and a literature review, we quantified which reptile species may benefit from the protection of intact sage‐grouse habitat and which may be affected by recent (since about 1990) habitat restoration actions targeting sage‐grouse. Of 190 reptile species in the United States and Canadian provinces where greater sage‐grouse occur, 70 (37%) occur within the range of the bird. Of these 70 species, about a third (11 snake and 11 lizard species) have >10% of their distribution area within the sage‐grouse range. Land cover similarity indices revealed that 14 of the 22 species (8 snake and 6 lizard species) had relatively similar land cover associations to those of sage‐grouse, suggesting greater potential to be protected under the sage‐grouse conservation umbrella and greater potential to be affected, either positively or negatively, by habitat management actions intended for sage‐grouse. Conversely, the remaining 8 species are less likely to be protected because of less overlap with sage‐grouse habitat and thus uncertain effects of sage‐grouse habitat management actions. Our analyses of treatment databases indicated that from 1990 to 2014 there were at least 6,400 treatments implemented on public land that covered approximately 4 million ha within the range of the sage‐grouse and, of that, >1.5 million ha were intended to at least partially benefit sage‐grouse. Whereas our results suggest that conservation of intact sagebrush vegetation communities could benefit ≥14 reptiles, a greater number than previously estimated, additional research on each species' response to habitat restoration actions is needed to assess broader claims of multi‐taxa benefits when it comes to manipulative sage‐grouse habitat management. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.

Idaho, Montana↗