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USGS2019

Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.

North Carolina↗

USGS2014

A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide

We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.

Population and Environment↗

USGS2017

Hierarchical, quantitative biogeographic provinces for all North American turtles and their contribution to the biogeography of turtles and the continent

Our study represents the first attempt to describe biogeographic provinces for North American (México, United States, and Canada) turtles. We analyzed three nested data sets separately: (1) all turtles, (2) freshwater turtles, and (3) aquatic turtles. We georeferenced North American turtle distributions, then we created presence–absence matrices for each of the three data sets. We used watershed unit as biogeographic units. We conducted an unweighted pair-group method with arithmetic mean clustering analysis on each Jaccard index distance matrix from our watershed species matrices to delineate biogeographic provinces. Provinces were then tested for significant differences in species compositions in a global model with the use of a one-way analysis of similarity. We conducted a best subset of environmental variables with maximum (rank) correlation with community dissimilarities that determined the best model of abiotic variables explaining province delineation (i.e., climate, topography, and stream channel). To identify which species contributed the most to province delineations, we conducted an indicator species analysis and a similarity-percentage analysis. There were 16 all-turtle provinces, 15 freshwater provinces, and 13 aquatic provinces. Species compositions delineating the provinces were explained by abiotic variables, including mean annual precipitation, mean precipitation seasonality, and diversity of streams. Province delineations correspond closely with geographical boundaries, many of which have Pleistocene origins. For example, rivers with a history of carrying glacial runoff (e.g., Arkansas, Mississippi) sometimes dissect upland provinces, especially for aquatic and semiaquatic turtles. Compared with freshwater fishes, turtles show greater sensitivity to decreased temperature with restriction of most taxa south of the last permafrost maximum. Turtles also exhibit higher sensitivity to climatic, geomorphic, and tectonic instability, with richness and endemism concentrated along the more stable Gulf of México and Atlantic (south of the last permafrost maximum) coasts. Although distribution data indicate two aquatic turtles are most cold tolerant (i.e., Chrysemys picta , Chelydra serpentina ), aquatic turtles overall show the most restriction to warmer, wetter climates. Sequential addition of semiaquatic and terrestrial turtles into analyses shows, as expected, that these taxa flesh out turtle faunas in climatically harsh (e.g., grasslands) or remote (e.g., California, Sonoran Desert) regions. The turtle assemblages of southwestern versus southeastern North America are distinct. But there is a transition zone across the semiarid plains of the Texas Gulf Coast, High Plains, and Chihuahuan Desert, including a strong boundary congruent with the Cochise Filter-Barrier. This is not a simple subdivision of Neotropical versus Nearctic taxa, as some lineages from both realms span the transition zone.

Herpetological Monographs↗

USGS2008

Hydrogeology and water quality of the Leetown area, West Virginia

The U.S. Geological Survey’s Leetown Science Center and the co-located U.S. Department of Agriculture’s National Center for Cool and Cold Water Aquaculture both depend on large volumes of cold clean ground water to support research operations at their facilities. Currently, ground-water demands are provided by three springs and two standby production wells used to augment supplies during periods of low spring flow. Future expansion of research operations at the Leetown Science Center is dependent on assessing the availability and quality of water to the facilities and in locating prospective sites for additional wells to augment existing water supplies. The hydrogeology of the Leetown area, West Virginia, is a structurally complex karst aquifer. Although the aquifer is a karst system, it is not typical of most highly cavernous karst systems, but is dominated by broad areas of fractured rock drained by a relatively small number of solution conduits. Characterization of the aquifer by use of fluorometric tracer tests, a common approach in most karst terranes, therefore only partly defines the hydrogeologic setting of the area. In order to fully assess the hydrogeology and water quality in the vicinity of Leetown, a multi-disciplinary approach that included both fractured rock and karst research components was needed. The U.S. Geological Survey developed this multi-disciplinary research effort to include geologic, hydrologic, geophysical, geographic, water-quality, and microbiological investigations in order to fully characterize the hydrogeology and water quality of the Leetown area, West Virginia. Detailed geologic and karst mapping provided the framework on which hydrologic investigations were based. Fracture trace and lineament analysis helped locate potential water-bearing fractures and guided installation of monitoring wells. Monitoring wells were drilled for borehole geophysical surveys, water-quality sampling, water-level measurements, and aquifer tests to characterize the quality of water and the hydraulic properties of the aquifer. Surface geophysical surveys provided a 3-dimensional view of bedrock resistivity in order to assess geologic and lithologic controls on ground-water flow. Borehole geophysical surveys were conducted in monitoring wells to assess the storage and movement of water in subsurface fractures. Numerous single-well, multi-well, and straddle packer aquifer tests and step-drawdown tests were conducted to define the hydraulic properties of the aquifer and to assess the role of bedrock fractures and solution conduits in the flow of ground water. Water samples collected from wells and springs were analyzed to assess the current quality of ground water and provide a baseline for future assessment. Microbiological sampling of wells for indicator bacteria and human and animal DNA provided an analysis of agricultural and suburban development impacts on ground-water quality. Light detection and ranging (LiDAR) data were analyzed to develop digital elevation models (DEMs) for assessing sinkhole distribution, to provide elevation data for development of a ground-water flow model, and to assess the distribution of major fractures and faults in the Leetown area. The flow of ground water in the study area is controlled by lithology and geologic structure. Bedrock, especially low permeability units such as the shale Martinsburg Formation and the Conococheague Limestone, act as barriers to water flowing down gradient and across bedding. This retardation of cross-strike flow is especially pronounced in the Leetown area, where bedding typically dips at steep angles. Highly permeable fault and fracture zones that disrupt the rocks in cross-strike directions provide avenues through which ground water can flow laterally across or through strata of low primary permeability. Significant strike parallel thrust faults and cross-strike faults typically coincide with larger solution conduits and act as drains for the more pervasive network of interconnected diffuse fractures. Results of borehole geophysical surveys indicate that although numerous fractures may intersect a borehole, only one or two of the fractures typically transmit most of the water to a well. The diffuse-flow dominated network of fractures that provides the majority of storage occupies only a small proportion of the total aquifer volume but constitutes the majority of porosity within the aquifer. Solution conduits, while occupying a relatively small volume of the overall aquifer, are especially important because they serve as primary drains for the ground-water flow system. Surface resistivity maps and cross-sectionsshow anomalous areas of low resistivities coincident with the prevailing geologic strike at N. 20º E., with major cross-strike faults, and with major springs in the region. Transmissivity derived from straddle packer tests was highly variable, and ranged over three orders of magnitude (1.8 x 10 -6 to 5.9 x 10 -3 ft 2 /d) in diffuse-flow fractures. A similar large variability in transmissivity was documented by single- and multi-well aquifer tests conducted in conduit-flow dominated portions of the aquifer (2.0 x 10 3 to 1.4 x 10 4 ft 2 /d) in lowland areas immediately adjacent to the Leetown Science Center. A stream-gaging station installed on Hopewell Run near the point where the stream exits the Leetown watershed indicates average daily streamflow for the Hopewell Run of approximately 11.2 ft 3 /s, and ranged from a minimum of 1.80 ft 3 /s on September 28, 2005, to a maximum of 73.0 ft 3 /s on December 11, 2003. Base-flow (ground-water) discharge surveys identified numerous small seeps adjacent to streams in the area. Hydrographs of the stage of Balch Spring show rapid response to individual storms. Strong correlation of the flow of Hopewell Run and Balch Spring indicates the nearby losing stream reach is partly responsible for higher fluctuations in the stage of Balch Spring. A water budget for the study period (2003-2005), based on measured precipitation and hydrograph analyses, is expressed as Precipitation (38.60 in/yr) = Surface Runoff (1.36 in/yr) + Ground-Water Discharge (17.73 in/yr) + Evapotranspiration (24.23 in/yr) – Change in storage (4.72 in/yr). Flow of ground water through the epikarst, a shallow zone of intensely weathered rock and regolith, can be rapid (on the order of days or weeks) as flow is concentrated in solution conduits. Flow within the intermediate and deeper zones is typically much slower. Eight dye-tracer tests conducted in the Leetown area found ground-water flow patterns to be divergent, with velocities ranging from about 12.5 to 610 ft/day and a median velocity of 50 ft/day. Estimates of ground-water age in carbonate rocks in the region are on the order of 15 years in the shallower portions of the aquifer to 50 years or older for deeper portions of the aquifer. Shallow springs can have a significant component of fairly young water (< 5 years in age). Ground-water samples collected from 16 sites (12 wells and 4 springs) in the Leetown area were analyzed for more than 340 constituents. Only turbidity, indicator bacteria, and radon were typically present in concentrations exceeding U.S. Environmental Protection Agency (USEPA) drinking-water or aquatic life standards.

West Virginia↗

USGS1998

Mapping the Gulf of Maine with side-scan sonar: A new bottom-type classification for complex seafloors

The bedrock-framed seafloor in the northwestern Gulf of Maine is characterized by extreme changes in bathymetric relief and covered with a wide variety of surficial materials. Traditional methods of mapping cannot accurately represent the great heterogeneity of such a glaciated region. A new mapping scheme for complex seafloors, based primarily on the interpretation of side-scan sonar imagery, utilizes four easily recognized units: rock, gravel, sand and mud. In many places, however, the seafloor exhibits a complicated mixture or extremely 'patchy' distribution of the four basic units, which are too small to map individually. Twelve composite units, each a two-component mixture of the basic units, were established to represent this patchiness at a small scale (1:100,000). Using a geographic information system, these and all other available data (seismic profiles, grab samples, submersible dives and cores) were referenced to a common geographic base, superimposed on bathymetric contours and then integrated into surficial geologic maps of the regional inner continental shelf. This digital representation of the seafloor comprises a multidimensional, interactive model complete with explicit attributes (depth, bottom type) that allow for detailed analysis of marine environments.

Journal of Coastal Research↗

USGS2021

Establishment of a microsatellite genetic baseline for North American Atlantic sturgeon (Acipenser o. oxyrhinchus) and range-wide analysis of population genetics

Atlantic sturgeon ( Acipenser oxyrinchus oxyrinchus ) is a long-lived, anadromous species that is broadly distributed along the Atlantic coast of North America. Historic overharvest and habitat degradation resulted in significant declines to Atlantic sturgeon populations and, following decades of limited recovery, the species was listed under the Endangered Species Act of the United States in 2012. Given continued threats to recovery and limited information about population demography, there is a need for new tools to assist in Atlantic sturgeon conservation. Here, we present a range-wide microsatellite genetic baseline for North American Atlantic sturgeon that is comprised of 2510 individuals from 18 genetically distinct groups collected in 13 rivers and one estuary. Analysis of this baseline suggested that populations from the northern range of Atlantic sturgeon were more highly differentiated than those from the southern extent, where patterns of differentiation were complicated by rivers with genetically distinct spring and fall spawning runs and less geographic distance separating populations. Despite significant demographic bottleneck events, all populations showed at least moderate levels of genetic diversity across a suite of metrics. Additionally, individual-based assignment tests had over 80% accuracy for assigning individuals to their river of origin, highlighting the utility of this baseline for characterizing the composition of mixed-stock aggregations and understanding stock-specific vulnerability and recovery. The expanded spatial coverage of this baseline dataset enabled novel inferences about patterns of genetic differentiation and spawning phenology in Atlantic sturgeon which can be used to support conservation and management efforts.

Atlantic Coast↗

USGS2023

Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) to perform these checks and estimate probabilities that an analyst would publish or reject a site-specific trend model from a multi-site study. We trained these “model-checking models” (MCMs) using a national study of over 6000 trend models and tested the MCMs using a smaller set of novel trend models. Although the MCMs did not perform well enough to bypass analyst review entirely, we found incorporating an MCM into a larger evaluation workflow can reduce the number of trend models needing an analyst review by more than half.

Environmental Modeling and Software↗

USGS2014

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work – for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

Journal of Volcanology and Geothermal Research↗

USGS2007

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the Indian epidemic, the disease disappeared and reappeared several times at most locations; in Western Europe, once the disease entered a place, it lasted a time proportional to the population and then disappeared for several years (this on-and-off situation lasted more than three centuries); and (6) on average, Black Death moved much faster than bubonic plague to reach virgin territories, despite the fact that India is only slightly larger in area than Western Europe and had a railroad network almost instantly moving infected rats, fleas, and people from one end of the subcontinent to the other. Conclusions: These findings throw new light on the spatiotemporal characteristics of the epidemics and need to be taken into consideration in the scientific discussion concerning the two devastating diseases and the lessons learned from them. ?? 2007 The Royal Institute of Public Health.

Public Health↗

USGS2012

Pyrethroid insecticides in bed sediments from urban and agricultural streams across the United States

Pyrethroid insecticides are hydrophobic compounds that partition to streambed sediments and have been shown to cause toxicity to non-target organisms; their occurrence is well documented in parts of California, but there have been limited studies in other urban and agricultural areas across the United States. To broaden geographic understanding of pyrethroid distributions, bed sediment samples were collected and analyzed from 36 streams in 25 states, with about 2/3 of the sites in urban areas and 1/3 in agricultural areas. At least one pyrethroid (of the 14 included in the analysis) was detected in 78% of samples. Seven pyrethroids were detected in one or more samples. Bifenthrin was the most frequently detected (58% of samples), followed by permethrin (31%), resmethrin (17%), and cyfluthrin (14%). The other three detected pyrethroids (cyhalothrin, cypermethrin and delta/tralomethrin) were found in two or fewer of the samples. Concentrations ranged from 0.3 to 180 ng g -1 dry weight. The number of pyrethroids detected were higher in the urban samples than in the agricultural samples, but the highest concentrations of individual pyrethroids were split between urban and agricultural sites. The pyrethroids detected in the agricultural areas generally followed use patterns. Predicted toxicity was greater for urban areas and attributed to bifenthrin, cyfluthrin and cypermethrin, while in agricultural areas the toxicity was mainly attributed to bifenthrin.

Journal of Environmental Monitoring↗

USGS2021

USGS National Water Quality Monitoring Network

What is the U.S. Geological Survey National Water Quality Monitoring Network? Understanding the water quality of U.S. streams and rivers requires consistent data collection and analysis over decades. The U.S. Geological Survey’s (USGS) National Water Quality Network (NWQN) was established to facilitate national-scale understanding of surface-water quality conditions through the collection of comparable data in large rivers and small streams in different geographic and land-use settings. Data collected by the NWQN support the needs of Federal, State, and local stakeholders tasked with managing our Nation’s water resources.

Fact Sheet↗

USGS1988

Benthic macrofauna and ancillary data for San Francisco Bay, California, March to November 1987

Benthic macrofauna and ancillary data were collected during 1987 as part of the U.S. Geological Survey Regional Effects Monitoring Program in San Francisco Bay, California. Data were collected during five cruises at 2-month intervals from March through November. Benthic macrofauna for identification of species and sediment for size analysis were sampled at eight stations. Ancillary data, which consisted of salinity, temperature, dissolved-oxygen concentrations, and suspended sediment, were collected at 12 stations. Salinity and temperature were measured at three stations that coincided with continuous water quality monitors. Abundances and geographical distributions of a newly introduced species of clam were measured. (USGS)

Open-File Report↗

USGS2004

Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire

This report presents regression equations to estimate generalized annual and seasonal ground-water-recharge rates in drainage basins in New Hampshire. The ultimate source of water for a ground-water withdrawal is aquifer recharge from a combination of precipitation on the aquifer, ground-water flow from upland basin areas, and infiltration from streambeds to the aquifer. An assessment of ground-water availability in a basin requires that recharge rates be estimated under `normal' conditions and under assumed drought conditions. Recharge equations were developed by analyzing streamflow, basin characteristics, and precipitation at 55 unregulated continuous record stream-gaging stations in New Hampshire and in adjacent states. In the initial step, streamflow records were analyzed to estimate a series of annual and seasonal ground-water-recharge components of streamflow in each drainage basin evaluated in this study. Regression equations were then developed relating the series of annual and seasonal ground-water-recharge values to the corresponding series of annual and seasonal precipitation values as determined at the centroid of each drainage basin. This resulted in one equation for each of the 55 basins for each of the four seasonal periods and the annual period, or a total of 275 regression equations. Average annual and seasonal precipitation data for 1961-90 were then used to compute a set of normalized ground-water-recharge values that reflected the long-term average annual and seasonal variations (normalized) and mean recharge characteristics of each drainage basin. Ordinary-least-squares regression was applied in the process of selecting 10 out of 93 possible basin and climatic characteristics for further testing in the development of the equations for computing the generalized estimate of annual and seasonal ground-water recharge based on the set of normalized recharge values. Generalized-least-squares regression was used for the final parameter estimation and error evaluation. The following basin and climatic characteristics were found to be statistically significant predictors for at least one of the dependent variables: average annual, summer, and spring precipitation as determined at U.S. Geological Survey stream-gaging stations; average annual basin-centroid precipitation; average mean annual basin temperature; average minimum winter basin temperature; percent coniferous forest in a basin; percent mixed coniferous and deciduous forest in a basin; average fall basin-centroid precipitation; and average annual snowcover. These 10 basin and climatic characteristics were selected because they were statistically significant based on several statistical parameters that evaluated which combination of characteristics contributed the most to the predictive accuracy of the regression-equation models. A geographic information system is required to measure the values of the predictor variables for the equations developed in the study. The average annual normalized ground-water recharge was 21.0 in. This value was determined by generalized-least-squares (GLS) regression analysis for all of the basins used in the normalized ground-water recharge analysis for precipitation from 1961-90. The average winter (January 1-March 15) ground-water recharge was 4.3 in., average spring (March 16-May 31) ground-water recharge was 9.0 in., average summer (June 1-October 31) ground-water recharge was 4.0 in., and average fall (November 1-December 31) ground-water recharge was 3.6 in. Normalized ground-water recharge ranged annually from 12.3 to 31.8 in., for winter from 2.30 to 7.82 in., for spring from 5.16 to 13.7 in., for summer from 1.45 to 10.2 in., and for fall from 2.21 to 6.06 in.

New Hampshire↗

USGS2018

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

River Research and Applications↗

USGS1987

Trend analysis of monthly sulfur dioxide emissions in the conterminous United States, 1975-1984

Trends in monthly sulfur dioxide emissions for the 48 conterminous United States during the decade 1975-1984 are identified using a robust nonparametric procedure. Statistically significant downward trends are indicated in 32 States, upward trends appear in 10 States, and no significant trend is apparent in six States. Geographically, a distinct regional pattern of emission increases and decreases is evident with declines dominating the Eastern and Western States; increases aligning longitudinally from border to border in most of the Great Plains States, in several New England States, and in Georgia; and no trends frequently occurring in proximity to the upward trending emissions in the Plains States. A time-series decomposition of the monthly values indicates that one distinct emissions pattern commonly occurred through the period of record. This pattern is characterized by an initial emissions increase that peaks between 1977 and 1978, followed by a shallow and undulating decrease though the end of 1984. It is suggested that this signature represents the 'national' trend for the period. In addition, five regions of coherent sulfur dioxide emissions behavior are defined on the basis of seasonal occurrence of maximum and minimum emission loadings. A winter-summer, latitudinal opposition is apparent in the timing of emissions maxima, whereas an equinox-summer, longitudinal opposition is apparent in the timing of emissions minima.Trends in monthly sulfur dioxide emissions for the 48 conterminous United States during the decade 1975-1984 are identified using a robust nonparametric procedure. Statistically significant downward trends are indicated in 32 States, upward trends appear in 10 States, and no significant trend is apparent in six States. Geographically, a distinct regional pattern of emission increases and decreases is evident with declines dominating the Eastern and Western States; increases aligning longitudinally from border to border in most of the Great Plains States, in several New England States, and in Georgia; and no trends frequently occurring in proximity to the upward trending emissions in the Plains States. A time-series decomposition of the monthly values indicates that one distinct emissions pattern commonly occurred through the period of record. This pattern is characterized by an initial emissions increase that peaks between 1977 and 1978, followed by a shallow and undulating decrease through the end of 1984. It is suggested that this signature represents the 'national' trend for the period. Additional study results are discussed.

Atmospheric Environment↗

USGS2022

The socioecology of fear: A critical geographical consideration of human-wolf-livestock conflict

Animal fear can be an important driver of ecological community structure: predators affect prey not only through predation, but by inducing changes in behavior and distribution—a phenomenon evocatively called the “ecology of fear.” The return of wolves to the western United States is a notable instance of such dynamics, yet plays out in a complex socio-ecological system where efforts to mitigate impacts on livestock rely on manipulating wolves’ fear of people. Examining Washington state’s efforts to affect wolf behavior to reduce livestock predation, we argue that this approach to coexistence with wolves is predicated on relations of fear: people, livestock, and wolves can arguably share landscapes with minimal conflict, as long as wolves are adequately afraid. We introduce the “socioecology of fear” as an interdisciplinary framework for examining the interwoven social and ecological processes of human-wildlife conflict management. Beyond frequently-voiced ideas about wolves’ “innate” fear, we examine how fear is (re)produced through human-wolf interactions and deeply shaped by human social processes. We contribute to the Critical Physical Geography project by integrating critical social analysis with ecological theory, conducted through collaborative interdisciplinary dialogue. Such integrative practice is essential for understanding the complex challenges of managing wildlife in the Anthropocene.

Washington↗

USGS2015

Methods for estimating the magnitude and frequency of peak streamflows at ungaged sites in and near the Oklahoma Panhandle

This report presents the results of a cooperative study by the U.S. Geological Survey and the Oklahoma Department of Transportation to estimate the magnitude and frequency of peak streamflows from regional regression equations for ungaged stream sites in and near the Oklahoma Panhandle. These methods relate basin characteristics (physiographic and climatic attributes) to selected peak streamflow frequency statistics with the 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities. These relations were developed based on data from 32 selected streamflow-gaging stations in the Oklahoma Panhandle and in neighboring parts of Colorado, Kansas, New Mexico, and Texas. The basin characteristics for the selected streamflow-gaging stations were determined by using a geographic information system and the Oklahoma StreamStats application. Peak-streamflow frequency statistics were computed from annual peak-streamflow records from the irrigated period of record from water year 1978 through water year 2014. Generalized-least-squares multiple-linear regression analysis was used to formulate regression relations between peak-streamflow frequency statistics and basin characteristics. Contributing drainage area was the only basin characteristic determined to be statistically significant for all percentage of annual exceedance probabilities and was the only basin characteristic used in regional regression equations for estimating peak-streamflow frequency statistics on unregulated streams in and near the Oklahoma Panhandle. The regression model pseudo-coefficient of determination, converted to percent, for the Oklahoma Panhandle regional regression equations ranged from about 38 to 63 percent. The standard errors of prediction and the standard model errors for the Oklahoma Panhandle regional regression equations ranged from about 84 to 148 percent and from about 76 to 138 percent, respectively. These errors were comparable to those reported for regional peak-streamflow frequency regression equations for the High Plains areas of Texas and Colorado. The root mean square errors for the Oklahoma Panhandle regional regression equations (ranging from 3,170 to 92,000 cubic feet per second) were less than the root mean square errors for the Oklahoma statewide regression equations (ranging from 18,900 to 412,000 cubic feet per second); therefore, the Oklahoma Panhandle regional regression equations produce more accurate peak-streamflow statistic estimates for the irrigated period of record in the Oklahoma Panhandle than do the Oklahoma statewide regression equations. The regression equations developed in this report are applicable to streams that are not substantially affected by regulation, impoundment, or surface-water withdrawals. These regression equations are intended for use for stream sites with contributing drainage areas less than or equal to about 2,060 square miles, the maximum value for the independent variable used in the regression analysis.

Colorado, Kansas, New Mexico, Oklahoma, Texas↗

USGS2002

Factors controlling storm impacts on coastal barriers and beaches - A preliminary basis for near real-time forecasting

Analysis of ground conditions and meteorological and oceanographic parameters for some of the most severe Atlantic and Gulf Coast storms in the U.S. reveals the primary factors affecting morphological storm responses of beaches and barrier islands. The principal controlling factors are storm characteristics, geographic position relative to storm path, timing of storm events, duration of wave exposure, wind stress, degree of flow confinement, antecedent topography and geologic framework, sediment textures, vegetative cover, and type and density of coastal development. A classification of commonly observed storm responses demonstrates the sequential interrelations among (1) land elevations, (2) water elevations in the ocean and adjacent lagoon (if present), and (3) stages of rising water during the storm. The predictable coastal responses, in relative order from high frequency beach erosion to low frequency barrier inundation, include: beach erosion, berm migration, dune erosion, washover terrace construction, perched fan deposition, sheetwash, washover channel incision, washout formation, and forced and unforced ebb flow. Near real-time forecasting of expected storm impacts is possible if the following information is available for the coast: a detailed morphological and topographic characterization, accurate storm-surge and wave-runup models, the real-time reporting of storm parameters, accurate forecasts of the storm position relative to a particular coastal segment, and a conceptual model of geological processes that encompasses observed morphological changes caused by extreme storms.

Journal of Coastal Research↗