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At least 649 records · Page 36Linked to original sources
USGS2003

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine and(or) desethyl-atrazine (atrazine/DEA) at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability maps were constructed.

Colorado↗
USGS2003

Precipitation-Runoff Simulations of Current and Natural Streamflow Conditions in the Methow River Basin, Washington

Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation, were simulated reasonably well yet possessed the most uncertainty. Simulations of annual mean streamflow as a percentage of measured annual mean streamflow for the 10-year calibration period at six of the seven streamflow-gaging stations ranged from -35.2 to +26.2 percent, with 65 percent of the simulated values within 15 percent. One station was intentionally calibrated to over-simulate discharge (simulated discharge greater than measured discharge) in order to compensate for observed channel losses not simulated by the model. Simulation of water years 1960-2001 demonstrated great variability in monthly streamflow statistics. The simulated mean monthly flows for 11 streamflow-gaging stations were an average of 2.5 percent higher for water years 1992-2001 than for the entire simulation period. If water year 2001, an extreme drought year, is omitted, simulated mean monthly flows for the 11 streamflow-gaging stations were an average of 9.0 percent higher than for the entire simulation period. The calibrated model also examined the effects of irrigation-canal seepage on streamflow. Irrigation-canal seepage contributed to streamflow throughout the year, with the greatest effect during the irrigation season. Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation

Water-Resources Investigations Report↗
USGS2010

Allocating harvests among polar bear stocks in the Beaufort Sea

Recognition that polar bears are shared by hunters in Canada and Alaska prompted development of the “Polar Bear Management Agreement for the Southern Beaufort Sea.” Under this Agreement, the harvest of polar bears from the southern Beaufort Sea (SBS) is shared between Inupiat hunters of Alaska and Inuvialuit hunters of Canada. Quotas for each jurisdiction are to be reviewed annually in light of the best available scientific information. Ideal implementation of the Agreement has been hampered by the inability to quantify geographic overlap among bears from adjacent populations. We applied new analytical procedures to a more extensive radiotelemetry data set than has previously been available to quantify that overlap and thereby improve the efficacy of the Agreement. We constructed a grid over the eastern Chukchi Sea and Beaufort Sea and used twodimensional kernel smoothing to assign probabilities to the distributions of all instrumented bears. A cluster analysis of radio relocation data identified three relatively discrete groups or “populations” of polar bears: the SBS, Chukchi Sea (CS), and northern Beaufort Sea (NBS) populations. With kernel smoothing, we calculated relative probabilities of occurrence for individual members of each population in each cell of our grid. We estimated the uncertainty in probabilities by bootstrapping. Availability of polar bears from each population varied geographically. Near Barrow, Alaska, 50% of harvested bears are from the CS population and 50% from the SBS population. Nearly 99% of the bears taken by Kaktovik hunters are from the SBS. At Tuktoyaktuk, Northwest Territories, Canada, 50% are from the SBS and 50% from the NBS population. We displayed the occurrence of bears from each population as probabilities for each cell in our grid and as maps with contour lines delineating changes in relative probability. This new analytical approach will greatly improve the accuracy of allocating harvest quotas among hunting communities and jurisdictions while assuring that harvests remain within the bounds of sustainable yield.

Alaska, Northwest Territories, Yukon↗
USGS2003

Assessing water quality at large geographic scales: Relations among land use, water physicochemistry, riparian condition, and fish community structure

Data collected from 172 sites in 20 major river basins between 1993 and 1995 as part of the US Geological Survey's National Water-Quality Assessment Program were analyzed to assess relations among basinwide land use (agriculture, forest, urban, range), water physicochemistry, riparian condition, and fish community structure. A multimetric approach was used to develop regionally referenced indices of fish community and riparian condition. Across large geographic areas, decreased riparian condition was associated with water-quality constituents indicative of nonpoint source inputs-total nitrogen and suspended sediment and basin-wide urban land use. Decreased fish community condition was associated with increases in total dissolved solids and rangeland use and decreases in riparian condition and agricultural land use. Fish community condition was relatively high even in areas where agricultural land use was relatively high (>50% of the basin). Although agricultural land use can have deleterious effects on fish communities, the results of this study suggest that other factors also may be important, including practices that regulate the delivery of nutrients, suspended sediments, and total dissolved solids into streams. Across large geographic scales, measures of water physicochemistry may be better indicators of fish community condition than basinwide land use. Whereas numerous studies have indicated that riparian restorations are successful in specific cases, this analysis suggests the universal importance of riparian zones to the maintenance and restoration of diverse fish communities in streams.

Environmental Management↗
USGS2015

Digital database of channel cross-section surveys, Mount St. Helens, Washington

Stream-channel cross-section survey data are a fundamental component to studies of fluvial geomorphology. Such data provide important parameters required by many open-channel flow models, sediment-transport equations, sediment-budget computations, and flood-hazard assessments. At Mount St. Helens, Washington, the long-term response of channels to the May 18, 1980, eruption, which dramatically altered the hydrogeomorphic regime of several drainages, is documented by an exceptional time series of repeat stream-channel cross-section surveys. More than 300 cross sections, most established shortly following the eruption, represent more than 100 kilometers of surveyed topography. Although selected cross sections have been published previously in print form, we present a comprehensive digital database that includes geospatial and tabular data. Furthermore, survey data are referenced to a common geographic projection and to common datums. Database design, maintenance, and data dissemination are accomplished through a geographic information system (GIS) platform, which integrates survey data acquired with theodolite, total station, and global navigation satellite system (GNSS) instrumentation. Users can interactively perform advanced queries and geospatial time-series analysis. An accuracy assessment provides users the ability to quantify uncertainty within these data. At the time of publication, this project is ongoing. Regular database updates are expected; users are advised to confirm they are using the latest version.

Washington↗
USGS1988

Distribution and variability of precipitation chemistry in the conterminous United States, January through December 1983

Analysis of atmospheric precipitation samples, collected during the 1983 calendar year from 109 National Trends Network sites in the United States, are presented in this report. The sites were grouped into six geographical regions based on the chemical composition of the samples. Precipitation chemistry in these regions was influenced by proximity to (1) oceans, (2) major industrial and fossil-fuel consuming areas, and (3) major agricultural and livestock areas. Frequency distributions of ionic composition, determined on 10 chemical constituents and on precipitation quantities for each site, showed wide variations in chemical concentrations and precipitation quantities from site to site. Of the 109 sites, 55 had data coverage for the year sufficient to characterize precipitation quality patterns on a nationwide basis. Except for ammonium and calcium, both of which showed largest concentrations in the agricultural midwest and plains states, the largest concentrations and loads generally were in areas that include the heavily industrialized population center of the eastern United States. Except for hydrogen, all chemical ions are inversely related to the quantity of precipitation depth. Precipitation quantities generally account for less than 30% of chemical variation in precipitation samples. However, precipitation quantities account for 30 to 65% of the variations of calcium concentrations in precipitation. In regions where precipitation has a large ionic proportion of hydrogen-ion equivalents, much of the hydrogen-ion concentration could be balanced by sulfate equivalents and partly balanced by nitrite-plus-nitrate equivalents. In the regions where hydrogen-ion equivalents in precipitation were smaller, ammonion-and calcium-ion equivalents were necessary, along with the hydrogen-ion equivalents, to balance the sulfate plus nitrite-plus-nitrate equivalent. (USGS)

Open-File Report↗
USGS1996

Methods for estimating low-flow characteristics of ungaged streams in selected areas, northern Florida

Methods for estimating low-flow frequency characteristics at ungaged sites were developed for two areas in northern Florida. In the Yellow, Blackwater, Escambia, and Perdido River Basins study area (northwestern Florida), regional regression equations were developed for estimating the 7- and 30-day, 2- and 10-year low-flow characteristic (Q7,2, Q7,10, Q30,2, and Q30,10) by determining values of basin characteristics from digital Geographical Information System (GIS) coverages or hardcopy maps. A GIS, ARC-INFO, was used to quantify basin characteristics that were used in regression equations. Sources of digital data used in this analysis are elevation data, from a digital elevation model, stream length and location data from a digital hydrography coverage, and watershed boundaries digitized from topographic maps. The most accurate regression equations employed a basin characteristic that was based on a simple conceptual model of one- dimensional ground-water flow using Darcy's law. Slightly less accurate equations were obtained using drainage area as the only explanatory variable. The standard error of prediction for the Darcy and drainage area equations of Q7,2 was 65 and 74 percent, respectively; Q7,10, 58 and 62 percent, respectively; Q30,2, 51 and, 54 percent, respectively; and Q30,10, 44 and 51 percent, respectively. In the Santa Fe River Basin study area (northeastern Florida), a flow-routing method was used to estimate low-flow characteristics at ungaged sites from low stream- flow analyses based on records at gaged sites. The use of the flow-routing method is suggested for areas where regression analysis proves unsuccessful, where low-flow characteristics have been defined at a significant number of sites, and where information about the basin characteristics has been thoroughly researched. Low-flow frequency characteristics determined at 40 sites and measurements made during five synoptic runs in 1989-91 were used to develop a flow-routing method. Low-flow frequency characteristics and drainage areas were used to define river profiles for major streams within the Santa Fe River Basin. These river profiles serve as indicators of changes in a stream's low-flow characteristics with respect to change in drainage area. Unit low flows were also determined for each site where low-flow characteristics were determined. Areas of zero flow were defined for Q7,2 and Q7,10 conditions based on measurements made during synoptic runs and from low-flow frequency analyses. The flow-routing method uses the drainage areas to interpolate low-flow values between or near gaged sites on the same stream. Low-flow values are transferred from a gaged site, either upstream or downstream, to the ungaged site. A step-by-step process for flow routing must be made when tributary or other inflow enter a stream. The strength of the flow-routing method is that the values at gaged sites reflect the overall basin characteristics in the vicinity of the gaged sites. However, the accuracy of low-flow estimates may be less in areas of decreasing and increasing flow if sufficient data are not available to assess changing hydraulic and hydrologic conditions.

Florida↗
USGS2006

Interpreting map art with a perspective learned from J.M. Blaut

Map art has been mentioned only briefly in geographic or cartographic literature, and has been analyzed almost entirely at the interpretive level. This paper attempts to define and evaluate the cartographic value of contemporary map-like art by placing the body of work as a whole in the theoretical concepts proposed by J.M. Blaut and his colleagues about mapping as a cognitive and cultural universal. This paper discusses how map art resembles mapping characteristics similar to those observed empirically in very young children as described in the publications of Blaut and others. The theory proposes that these early mapping skills are later structured and refined by their social context and practice. Diverse cultural contexts account for the varieties, types, and degrees of mapping behavior documented with time and geographic place. The dynamics of early mapping are compared to mapping techniques employed by artists. The discipline of fine art serves as the context surrounding map artists and their work. My visual analysis, research about the art and the artists, and interviews with artists and curators form the basis of my interpretation of these works within varied and multiple contexts of late 20th century map art.

Cartographic Perspectives↗
USGS2010

Quantifying landscape ruggedness for animal habitat analysis: A case study using bighorn sheep in the Mojave Desert

Terrain ruggedness is often an important variable in wildlife habitat models. Most methods used to quantify ruggedness are indices derived from measures of slope and, as a result, are strongly correlated with slope. Using a Geographic Information System, we developed a vector ruggedness measure (VRM) of terrain based on a geomorphological method for measuring vector dispersion that is less correlated with slope. We examined the relationship of VRM to slope and to 2 commonly used indices of ruggedness in 3 physiographically different mountain ranges within the Mojave Desert of the southwestern United States. We used VRM, slope, distance to water, and springtime bighorn sheep (Ovis canadensis nelsoni) adult female locations to model sheep habitat in the 3 ranges. Using logistic regression, we determined that the importance of ruggedness in habitat selection remained consistent across mountain ranges, whereas the relative importance of slope varied according to the characteristic physiography of each range. Our results indicate that the VRM quantifies local variation in terrain more independently of slope than other methods tested, and that VRM and slope distinguish 2 different components of bighorn sheep habitat.

Journal of Wildlife Management↗
USGS2007

Variation in northern bobwhite demography along two temporal scales

Quantification and understanding of demographic variation across intra- and inter-annual temporal scales can benefit from the development of theoretical models of evolution and applied conservation of species. We used long-term survey data for northern bobwhites (Colinus virginianus) collected at the northern and southern extent of its geographic range to develop matrix population models which would allow investigation of intra- and inter-annual patterns in bobwhite population dynamics. We first evaluated intra-annual patterns in the importance of a seasonal demographic rate to asymptotic population growth rate with prospective perturbation analysis (elasticity analysis). We then conducted retrospective analysis (life table response experiments) of inter-annual patterns in the contribution of observed changes in demography to the observed change in population growth rate. Survival in the earliest age class during the nonbreeding season had the greatest potential influence in both the northern and southern populations. Examination of inter-annual variation in demography indicated that variation in nonbreeding season survival in the earliest age class contributed the most to observed changes in population growth rate in the northern population. In contrast, changes in fertility in the earliest age class in the southern population had the greatest influence on changes in population growth rate. Prospective elasticity analyses highlight the similarities in bobwhite demography throughout different parts of its geographic range, while retrospective life table response experiments revealed important patterns in the temporal differences of bobwhite life history at the northern and southern extent of its geographic range. ?? 2007 The Society of Population Ecology and Springer.

Population Ecology↗
USGS2026

Multivariate spatio-temporal clustering of wind–wave variability across European seas

This study presents a multivariate spatio-temporal clustering framework to characterise joint wind–wave regimes across European seas using the fifth-generation atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5; 1979–2014). Seasonal and annual statistics of significant wave height, mean wave period, wind speed, and wave/wind direction were computed at 0.5° resolution. Principal component analysis was used to reduce dimensionality, retaining 30 components that captured 99% of the variance. K-means clustering was then used to identify nine coherent dynamical regimes with persistent spatio-temporal signatures. These regimes were grouped into open-ocean, transitional, and enclosed/semi-enclosed categories based on internal variability, directional spread, and geographic exposure. Open-Atlantic regimes are found to be energy-rich, exhibiting clear December–February maxima in significant wave height ( 𝐻 𝑠 ), mean wave period ( 𝑇 02 ), and 10 m wind speed ( 𝑊 𝑠 10 ); enclosed and semi-enclosed basins show lower amplitudes and reduced variability, while transitional shelves and the southern Mediterranean display intermediate conditions, characterised by moderate 𝑇 02 levels and seasonal rotation of wave and wind directions, reflecting a mixed influence of locally generated seas and remotely forced swell. Dispersion analysis highlights a clear Atlantic–Mediterranean partition, with transitional shelves forming a dynamical bridge between open-ocean and enclosed basins. Teleconnection analysis shows that the North Atlantic Oscillation and Arctic Oscillation dominate Atlantic regimes, while the Scandinavia, East Atlantic, and Polar/Eurasia patterns modulate variability and directional persistence in transitional and enclosed seas. The classification defines a climatological framework of European wind–wave conditions and establishes a practical basis for renewable energy assessment, engineering design, and long-term change analysis, with methods transferable to other basins.

Atmosphere↗
USGS2014

Virtual Beach 3: user's guide

Virtual Beach version 3 (VB 3 ) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches. VB 3 is primarily designed for beach managers responsible for making decisions regarding beach closures or the issuance of swimming advisories due to pathogen contamination. However, researchers, scientists, engineers, and students interested in studying relationships between water quality indicators and ambient environmental conditions will find VB 3 useful. VB 3 reads input data from a text file or Excel document, assists the user in preparing the data for analysis, enables automated model selection using a wide array of possible model evaluation criteria, and provides predictions using a chosen model parameterized with new data. With an integrated mapping component to determine the geographic orientation of the beach, the software can automatically decompose wind/current/wave speed and magnitude information into along-shore and onshore/offshore components for use in subsequent analyses. Data can be examined using simple scatter plots to evaluate relationships between the response and independent variables (IVs). VB 3 can produce interaction terms between the primary IVs, and it can also test an array of transformations to maximize the linearity of the relationship The software includes search routines for finding the "best" models from an array of possible choices. Automated censoring of statistical models with highly correlated IVs occurs during the selection process. Models can be constructed either using previously collected data or forecasted environmental information. VB 3 has residual diagnostics for regression models, including automated outlier identification and removal using DFFITs or Cook's Distances.

Report↗
USGS2012

The population structure of Escherichia coli isolated from subtropical and temperate soils

While genotypically-distinct naturalized Escherichia coli strains have been shown to occur in riparian soils of Lake Michigan and Lake Superior watersheds, comparative analyses of E. coli populations in diverse soils across a range of geographic and climatic conditions have not been investigated. The main objectives of this study were to: (a) examine the population structure and genetic relatedness of E. coli isolates collected from different soil types on a tropical island (Hawaii), and (b) determine if E. coli populations from Hawaii and temperate soils (Indiana, Minnesota) shared similar genotypes that may be reflective of biome-related soil conditions. DNA fingerprint and multivariate statistical analyses were used to examine the population structure and genotypic characteristics of the E. coli isolates. About 33% (98 of 293) of the E. coli from different soil types and locations on the island of Oahu, Hawaii, had unique DNA fingerprints, indicating that these bacteria were relatively diverse; the Shannon diversity index for the population was 4.03. Nearly 60% (171 of 293) of the E. coli isolates from Hawaii clustered into two major groups and the rest, with two or more isolates, fell into one of 22 smaller groups, or individual lineages. Multivariate analysis of variance of 89, 21, and 106 unique E. coli DNA fingerprints for Hawaii, Indiana, and Minnesota soils, respectively, showed that isolates formed tight cohesive groups, clustering mainly by location. However, there were several instances of clonal isolates being shared between geographically different locations. Thus, while nearly identical E. coli strains were shared between disparate climatologically- and geographically-distinct locations, a vast majority of the soil E. coli strains were genotypically diverse and were likely derived from separate lineages. This supports the hypothesis that these bacteria are not unique and multiple genotypes can readily adapt to become part of the soil autochthonous microflora.

Hawai'i, Indiana, Minnesota↗
USGS2001

Mean and modal ϵ in the deaggregation of probabilistic ground motion

An important element of probabilistic seismic-hazard analysis (PSHA) is the incorporation of ground-motion uncertainty from the earthquake sources. The standard normal variate ϵ measures the difference between any specified spectral-acceleration level, or SA 0 , and the estimated median spectral acceleration from each probabilistic source. In this article, mean and modal values of ϵ for a specified SA 0 are defined and computed from all sources considered in the USGS 1996 PSHA maps. Contour maps of ϵ are presented for the conterminous United States for 1-, 0.3-, and 0.2-sec SA 0 and for peak horizontal acceleration, PGA 0 corresponding to a 2% probability of exceedance (PE) in 50 yr, or mean annual rate of exceedance, r , of 0.000404. Mean and modal ϵ exhibit a wide variation geographically for any specified PE. Modal ϵ for the 2% in 50 yr PE exceeds 2 near the most active western California faults, is less than –1 near some less active faults of the western United States (principally in the Basin and Range), and may be less than 0 in areal fault zones of the central and eastern United States (CEUS). This geographic variation is useful for comparing probabilistic ground motions with ground motions from scenario earthquakes on dominating faults, often used in seismic-resistant provisions of building codes. An interactive seismic-hazard deaggregation menu item has been added to the USGS probabilistic seismic-hazard analysis Web site, http://geohazards.cr.usgs.gov/eq/ , allowing visitors to compute mean and modal distance, magnitude, and ϵ corresponding to ground motions having mean return times from 250 to 5000 yr for any site in the United States.

Bulletin of the Seismological Society of America↗
USGS2009

New light on a dark subject: On the use of fluorescence data to deduce redox states of natural organic matter (NOM)

This paper reports the use of excitation-emission matrix fluorescence spectroscopy (EEMS), parallel factor statistical analysis (PARAFAC), and oxidation-reduction experiments to examine the effect of redox conditions on PARAFAC model results for aqueous samples rich in natural organic matter. Fifty-four aqueous samples from 11 different geographic locations and two plant extracts were analyzed untreated and after chemical treatments or irradiation were used in attempts to change the redox status of the natural organic matter. The EEMS spectra were generated and modeled using a PARAFAC package developed by Cory and McKnight (2005). The PARAFAC model output was examined for consistency with previously reported relations and with changes expected to occur upon experimental oxidation and reduction of aqueous samples. Results indicate the implied fraction of total sample fluorescence attributed to quinone-like moieties was consistent (0.64 to 0.78) and greater than that observed by Cory and McKnight (2005). The fraction of the quinone-like moieties that was reduced (the reducing index, RI) showed relatively little variation (0.46 to 0.71) despite attempts to alter the redox status of the natural organic matter. The RI changed little after reducing samples using zinc metal, oxidizing at high pH with air, or irradiating with a Xenon lamp. Our results, however, are consistent with the correlations between the fluorescence indices (FI) of samples and the ratio of PARAFAC fitting parameters suggested by Cory and McKnight (2005), though we used samples with a much narrower range of FI values.

Aquatic Sciences↗
USGS2016

Surface-air mercury fluxes across Western North America: A synthesis of spatial trends and controlling variables

Mercury (Hg) emission and deposition can occur to and from soils, and are an important component of the global atmospheric Hg budget. This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Science of the Total Environment↗
USGS2011

Isolation of Bartonella capreoli from elk

The aim of the present study was to investigate the presence of Bartonella infections in elk populations. We report the isolation of four Bartonella strains from 55 elk blood samples. Sequencing analysis demonstrated that all four strains belong to Bartonella capreoli, a bacterium that was originally described in the wild roe deer of Europe. Our finding first time demonstrated that B. capreoli has a wide geographic range, and that elk may be another host for this bacterium. Further investigations are needed to determine the impact of this bacterium on wildlife.

Veterinary Microbiology↗
USGS2003

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

Open-File Report↗