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At least 595 records · Page 33Linked to original sources

USGS1999

A possible link between Balkan endemic nephropathy and the leaching of toxic organic compounds from Pliocene lignite by groundwater: Preliminary investigation

Balkan endemic nephropathy (BEN) is a fatal kidney disease that is known to occur only in clusters of villages in alluvial valleys of tributaries of the Danube River in Bulgaria, Romania, Yugoslavia, Bosnia, and Croatia. The confinement of this disease to a specific geographic area has led to speculation that an environmental factor may be involved in the etiology of BEN. Numerous environmental factors have been suggested as causative agents for producing BEN, including toxic metals in drinking water, metal deficiency in soils of BEN areas, and environmental mycotoxins to name a few. These hypotheses have either been disproved or have failed to conclusively demonstrate a connection to the etiology of BEN, or the clustering of BEN villages. In previous work, we observed a distinct geographic relationship between the distribution of Pliocene lignites in the Balkans and BEN villages. We hypothesized that the long-term consumption of well water containing toxic organic compounds derived from the leaching of nearby Pliocene lignites by groundwater was a primary factor in the etiology of BEN. In our current work, chemical analysis using 13C nuclear magnetic resonance (13CNMR) spectroscopy indicated a high degree of organic functionality in Pliocene lignite from the Balkans, and suggested that groundwater can readily leach organic matter from these coal beds. Semi-quantitative gas chromatography/mass spectroscopy analysis of solvent extracts of groundwater from shallow wells in BEN villages indicated the presence of potentially toxic aromatic compounds, such as napthalene, fluorene, phenanthrene, and pyrene at concentrations in the ppb range. Laboratory leaching of Balkan Pliocene lignites with distilled water yielded soluble organic matter (> 500 MW) containing large amounts of aromatic structures similar to the simple/discrete aromatic compounds detected in well water from BEN villages. These preliminary results are permissive of our hypothesis and suggest that further work on the possible relationship between the etiology of BEN and toxic aromatic substances leached from Pliocene lignites in well water is warranted.A distinct geographic relationship between the distribution of Pliocene lignites in the Balkans and villages where Balkan endemic nephropathy (BEN) occurs has been observed, indicating a possible link between BEN and the long-term consumption of well water containing toxic organic compounds derived from the leaching of nearby Pliocene lignites. Preliminary investigations by NMR spectroscopy, gas chromatography/mass spectroscopy and leaching experiments show a high degree of organic functionality in the Pliocene lignites, high-leachability by groundwater of organic matter from these beds, and the presence of toxic aromatic compounds.

International Journal of Coal Geology↗

USGS2012

Spatial analysis of geologic and hydrologic features relating to sinkhole occurrence in Jefferson County, West Virginia

In this study the influence of geologic features related to sinkhole susceptibility was analyzed and the results were mapped for the region of Jefferson County, West Virginia. A model of sinkhole density was constructed using Geographically Weighted Regression (GWR) that estimated the relations among discrete geologic or hydrologic features and sinkhole density at each sinkhole location. Nine conditioning factors on sinkhole occurrence were considered as independent variables: distance to faults, fold axes, fracture traces oriented along bedrock strike, fracture traces oriented across bedrock strike, ponds, streams, springs, quarries, and interpolated depth to groundwater. GWR model parameter estimates for each variable were evaluated for significance, and the results were mapped. The results provide visual insight into the influence of these variables on localized sinkhole density, and can be used to provide an objective means of weighting conditioning factors in models of sinkhole susceptibility or hazard risk.

West Virginia↗

USGS2015

Combining NLCD and MODIS to create a land cover-albedo database for the continental United States

Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14 years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500 m × 500 m) from the NLCD product (30 m × 30 m), and provides an albedo data record per 500 m × 500 m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥ 50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.

Remote Sensing of Environment↗

USGS1998

Caribou distribution during the post-calving period in relation to infrastructure in the Prudhoe Bay oil field, Alaska

There is concern that caribou ( Rangifer tarandus ) may avoid roads and facilities (i.e., infrastructure) in the Prudhoe Bay oil field (PBOF) in northern Alaska, and that this avoidance can have negative effects on the animals. We quantified the relationship between caribou distribution and PBOF infrastructure during the post-calving period (mid-June to mid-August) with aerial surveys from 1990 to 1995. We conducted four to eight surveys per year with complete coverage of the PBOF. We identified active oil field infrastructure and used a geographic information system (GIS) to construct ten 1 km wide concentric intervals surrounding the infrastructure. We tested whether caribou distribution is related to distance from infrastructure with a chi-squared habitat utilization-availability analysis and log-linear regression. We considered bulls, calves, and total caribou of all sex/age classes separately. The habitat utilization-availability analysis indicated there was no consistent trend of attraction to or avoidance of infrastructure. Caribou frequently were more abundant than expected in the intervals close to infrastructure, and this trend was more pronounced for bulls and for total caribou of all sex/age classes than for calves. Log-linear regression (with Poisson error structure) of numbers of caribou and distance from infrastructure were also done, with and without combining data into the 1 km distance intervals. The analysis without intervals revealed no relationship between caribou distribution and distance from oil field infrastructure, or between caribou distribution and Julian date, year, or distance from the Beaufort Sea coast. The log-linear regression with caribou combined into distance intervals showed the density of bulls and total caribou of all sex/age classes declined with distance from infrastructure. Our results indicate that during the post-calving period: 1) caribou distribution is largely unrelated to distance from infrastructure; 2) caribou regularly use habitats in the PBOF; 3) caribou often occur close to infrastructure; and 4) caribou do not appear to avoid oil field infrastructure.

Alaska↗

USGS2024

Potentially toxic elements in wild Agassiz’s desert tortoises: Tissue concentrations and association with disease

Background: Desert tortoise ( Gopherus agassizii ) populations have continued to decline due to infectious and other diseases, predation, and habitat alteration. The potential contribution of minerals and heavy metals to tortoise health and susceptibility to disease remains uncertain. Objective: The objective of this study was to evaluate the results of elemental analysis of trace minerals and macrominerals in scute keratin, kidney, and liver tissue from ill and dying desert tortoises salvaged for necropsy between 1993 and 2000. Methods: Salvaged tortoises were categorized by age (adult, juvenile), geographic location, and primary disease based on necropsy findings. A subset of tortoises that were injured or killed by vehicular trauma or predation but with no notable pathologic abnormalities were used as controls. A panel of 21 trace minerals and 6 macrominerals was analyzed in scute keratin, kidney, and liver tissue samples by inductively-coupled plasma spectrometry and atomic absorption spectrophotometry. Results: Necropsies were done on 46 tortoises, including 9 juveniles salvaged from 5 regions in the Colorado and Mojave deserts of California. Primary diseases were cutaneous dyskeratosis (n=9), infection/ inflammation (n=8), malnutrition (n=7), mycoplasmosis (n=5), and urolithiasis (n=3); 14 tortoises were classified as controls. Concentrations of elements differed significantly by tissue, age, desert region, and disease (P < 0.05). Tortoises with cutaneous dyskeratosis had significantly higher Se concentrations, primarily in keratin and liver, than tortoises with other diseases (P < 0.001). Juveniles were more likely than adults to have high Pb, Sn, and Zn levels (P < 0.05). All tortoises had detectable levels of more than one potentially toxic heavy metal, including As, Cd, Cr, Hg, Ni, Pb, Sn and V. Conclusions: Potentially toxic elements are frequently found in tissue from tortoises in desert regions of California, with significantly higher concentrations in diseased tortoises. Metal exposure from soils, mining, historic and ongoing military activities, and other human activities could increase susceptibility to disease in desert tortoises.

California↗

USGS2014

Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010

Flooding is among the worst natural disasters responsible for loss of life and property in Arizona, underscoring the importance of accurate estimation of flood magnitude for proper structural design and floodplain mapping. Twenty-four years of additional peak-flow data have been recorded since the last comprehensive regional flood frequency analysis conducted in Arizona. Periodically, flood frequency estimates and regional regression equations must be revised to maintain the accurate estimation of flood frequency and magnitude. Annual peak-flow data collected through water year 2010 were compiled from 448 unregulated streamflow-gaging stations, hereafter referred to as streamgages, in Arizona having a minimum of 10 years of record. Flood frequency estimates were first computed with station (or at-site) skew using the Expected Moments Algorithm with a multiple Grubbs-Beck test to identify multiple potentially influential low flows to fit a Pearson Type III distribution. Next, a multiple step Bayesian least-squares-regression approach was used to determine a new statewide regional skew of −0.09. No basin characteristics analyzed were statistically significant in explaining the variation in skew and as a result, the constant model was chosen as the best regional skew model for the Arizona study area. The mean square error used in Bulletin 17B (B17B) of the Interagency Advisory Committee on Water Data is used to describe the precision of the regional skew. The constant model had a mean square error equal to 0.08, which corresponds to an effective record length of 85 years. This is a marked improvement over a previous Arizona regional skew analysis, with a reported mean square error of 0.31, for a corresponding effective record length of around 17 years. Thus the new regional model had almost five times the information content (as measured by effective record length) of that calculated in USGS Water Supply Paper 2433, published in 1997, or the value of 0.302 reported in the B17B generalized skew map. The flood frequency estimates were recalculated using a weighted skew of the station and regional skew. Station flood frequency estimates for each streamgage are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities. Geographical information systems were used to compute basin characteristic information for each streamgage for the purpose of developing regional equations to estimate flood statistics at ungaged basins. Five hydrologic flood regions in Arizona were defined in a multivariate regionalization process based on mean basin elevation, mean annual precipitation, and soil permeability. A regional generalized least-squares-regression analysis was used to develop five sets of equations from 344 nonredundant streamgages, corresponding to five regions, for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities at ungaged basins in Arizona. The regression equations developed for these five regions were based on one or more of the statistically significant explanatory variables: drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression regions for the five regions ranged from 27 to 122 percent and the pseudo-coefficients of determination (pseudo-R 2 ), a measure of the proportion of peak-flow variation that is explained by the basin characteristics, ranged from 68 to 98 percent. Regression equations for Central Highlands (region 4) had the lowest model error and the greatest pseudo-R 2 metrics. The equations for Colorado Plateau (region 2) regression equations generally had greater model error and lower pseudo-R 2 metrics. The improvement of regional regression equation model error and pseudo-R 2 metrics was related to higher numbers of streamgages, longer period of record, and even spatial coverage within a region. The regional regression equations were integrated into the U.S. Geological Survey’s StreamStats program. The StreamStats program is a national map-based web application that allows the public to easily access published flood frequency and basin characteristic statistics. The interactive web application allows a user to select a point within a watershed (gaged or ungaged) and retrieve flood-frequency estimates derived from the current regional regression equations and geographic information system data within the selected basin. StreamStats provides users with an efficient and accurate means for retrieving the most up to date flood frequency and basin characteristic data. StreamStats is intended to provide consistent statistics, minimize user error, and reduce the need for large datasets and costly geographic information system software.

Arizona↗

USGS2026

Riverine pesticide trends in the United States: Assessing a decade of national-scale monitoring

Pesticides in freshwater systems can compromise water availability by degrading water quality, with implications for human health and aquatic life. Despite recognition of the need for national-scale monitoring and analysis, few studies have documented long-term trends in surface water pesticide contamination across the US. This study addresses that need by analyzing temporal trends and acute and chronic benchmark exceedances for aquatic life and human health from 81 river sites sampled from 2013 to 2022 using an analytical method targeting 80 pesticides. The majority (79%) of single site and pesticide combinations had too few pesticide detections to estimate trends. When detections were more frequent, increasing trends in concentration were twice as common as decreasing trends. Increasing pesticide concentrations were common in primary drainages of the Mississippi River Basin. Aquatic life benchmarks were exceeded by 19 pesticides, and exceedances were geographically widespread, with both acute and chronic aquatic life benchmark exceedances at 62% of sites. The herbicides atrazine and metolachlor and the insecticide imidacloprid were identified as the greatest threats to surface water availability based on their trends and aquatic life benchmark exceedances. These findings demonstrate the need for continued monitoring and trend analysis, driver investigation, and management strategies to protect freshwater resources.

conterminous United States↗

USGS2023

A 37 K SNP array for the management and conservation of Golden Eagles (Aquila chrysaetos)

We describe the development of a custom 37 K Affymetrix Axiom myDesign single nucleotide polymorphism (SNP) array for a culturally and ecologically important apex predator, the golden eagle ( Aquila chrysaetos ). Using this SNP array, we performed population genomic analysis on 154 individuals of known natal localities and detected three genetic clusters that we designated as Taiga/High Arctic, Great Basin, and Rocky Mountains/Great Plains. Each of these clusters appears to display clinal variation within these geographic regions. After determining genetic structure, we performed an assignment test of 32 individuals, five of which were siblings of individuals used in the assessment of genetic structure, three had associated telemetry data, and the remaining individuals were of unknown natal locations. Using this array, four siblings were correctly assigned to the same geographic region as their sibling and the genetic assignment of the radio telemetered birds agreed with the expected movement patterns displayed by these individuals. For the remaining individuals, we were able to assign all but five individuals to one of the three genetic clusters. Our genetic assignments illustrates the utility of this SNP array to accurately assign most individuals to predesignated geographical regions. While further compiling genetic and other data types, we can increase the power of this tool for identifying those breeding populations that may need assistance due to anthropogenic stressors that negatively impact their population viability. The use of this genetic resource will help substantiate decisions by multiple conservation groups that seek to preserve the natural population structure of the golden eagle.

Conservation Genetics↗

USGS2000

Lagtime relations for urban streams in Georgia

Urban flood hydrographs are needed for the design of many highway drainage structures, embankments, and entrances to detention ponds. The three components that are needed to simulate urban flood hydrographs at ungaged sites are the design flood, the dimensionless hydrograph, and lagtime. The design flood and the dimensionless hydrograph have been presented in earlier studies for urban streams in Georgia. The objective of this study was to develop equations for estimating lagtime for urban streams in Georgia. Lagtimes were computed for 329 floods at 69 urban gaging stations in 11 cities in Georgia. These data were used to compute an average lagtime for each gaging station. Multiple regression analysis was then used to define relations between lagtime and certain physical basin characteristics, of which drainage area, slope, and impervious area were found to be significant. A qualitative variable was used to account for a geographical bias in flood-frequency region 4, a small area of southwestern Georgia. Information from this report can be used to simulate a flood hydrograph using a dimensionless hydrograph, the design flood, and the lagtime obtained from regression equations for any urban site with less than a 25-square-mile drainage area in Georgia.

Georgia↗

USGS1995

Delineating bird populations using ring recoveries

We delineate bird populations using cluster analysis to group ringing sites based on pairwise comparisons of recoveries. Clustering provides a quantitative (but non-unique) grouping that can be used to examine the relationships of bird distributions at both local and regional geographic scales. Clustering is based on similarity matrices composed of pairwise comparisons of recovery distributions from ringing sites. We demonstrate the method using mallard (Anas platyrhynchos) ring recoveries to group ringing sites in south-central Canada, and discuss the possibilities for these analyses for non-hunted species with few recoveries.

Book chapter↗

USGS2007

Design and implementation of estimation-based monitoring programs for flora and fauna: A case study on the Cherokee National Forest

Science-based monitoring of biological resources is important for a greater understanding of ecological systems and for assessment of the target population using theoretic-based management approaches. When selecting variables to monitor, managers first need to carefully consider their objectives, the geographic and temporal scale at which they will operate, and the effort needed to implement the program. Generally, monitoring can be divided into two categories: index and inferential. Although index monitoring is usually easier to implement, analysis of index data requires strong assumptions about consistency in detection rates over time and space, and parameters are often biasednot accounting for detectability and spatial variation. In most cases, individuals are not always available for detection during sampling periods, and the entire area of interest cannot be sampled. Conversely, inferential monitoring is more rigorous because it is based on nearly unbiased estimators of spatial distribution. Thus, we recommend that detectability and spatial variation be considered for all monitoring programs that intend to make inferences about the target population or the area of interest. Application of these techniques is especially important for the monitoring of Threatened and Endangered (T&E) species because it is critical to determine if population size is increasing or decreasing with some level of certainty. Use of estimation-based methods and probability sampling will reduce many of the biases inherently associated with index data and provide meaningful information with respect to changes that occur in target populations. We incorporated inferential monitoring into protocols for T&E species spanning a wide range of taxa on the Cherokee National Forest in the Southern Appalachian Mountains. We review the various approaches employed for different taxa and discuss design issues, sampling strategies, data analysis, and the details of estimating detectability using site occupancy. These techniques provide a science-based approach for monitoring and can be of value to all resource managers responsible for management of T&E species.

Proceedings of the Annual Conference of the Southe↗

USGS1991

Survey of rural, private wells. Statistical design

Half of Illinois' 38 million acres were planted in corn and soybeans in 1988. On the 19 million acres planted in corn and soybeans, approximately 1 million tons of nitrogen fertilizer and 50 million pounds of pesticides were applied. Because groundwater is the water supply for over 90 percent of rural Illinois, the occurrence of agricultural chemicals in groundwater in Illinois is of interest to the agricultural community, the public, and regulatory agencies. The occurrence of agricultural chemicals in groundwater is well documented. However, the extent of this contamination still needs to be defined. This can be done by randomly sampling wells across a geographic area. Key elements of a random, water-well sampling program for regional groundwater quality include the overall statistical design of the program, definition of the sample population, selection of wells to be sampled, and analysis of survey results. These elements must be consistent with the purpose for conducting the program; otherwise, the program will not provide the desired information. The need to carefully design and conduct a sampling program becomes readily apparent when one considers the high cost of collecting and analyzing a sample. For a random sampling program conducted in Illinois, the key elements, as well as the limitations imposed by available information, are described.

Conference Paper↗

USGS2026

Accounting for biases in the analysis of building damage data for the 2023 M7.8 Türkiye/Syria earthquake sequence

In the aftermath of a large earthquake, several practical constraints affect the systematic collection of data for assessing building damage. The available data are therefore typically incomplete, frequently missing key information such as the type of construction, age and geographic location. Moreover, the observations often favour certain locations and damage grades. In the absence of robust methods, using such data directly for characterising the building stock or conducting fragility assessments can introduce systematic bias. Using the 2023 M7.8 Türkiye/Syria earthquake sequence as a case study, we propose a statistical model that enables joint inference over the inventory and fragility of the building stock while explicitly accounting for sources of data error and missing information. The results show higher-than-expected vulnerability amongst several building types, particularly mid- and high-rise reinforced concrete buildings, which performed extremely poorly during the 2023 earthquake sequence. The proposed Bayesian framework provides rigorous uncertainty quantification that can be propagated to future applications.

Earthquake Spectra↗

USGS2010

Analysis of California Condor (Gymnogyps californianus) use of six management units using location data from global positioning system transmitters, southern California, 2004-09-Initial report

This report provides an analysis of California Condor (Gymnogyps californianus) space use of six management units in southern California (Hopper Mountain and Bitter Creek National Wildlife Refuges, Wildlands Conservancy-Wind Wolves Preserve, Tejon Mountain Village Specific Plan, California Condor Study Area, and the Tejon Ranch excluding Tejon Mountain Village Specific Plan and California Condor Study Area). Space use was analyzed to address urgent management needs using location data from Global Positioning System transmitters. The U.S. Fish and Wildlife Service provided the U.S. Geological Survey with location data (2004-09) for California Condors from Global Positioning System transmitters and Geographic Information System data for the six management units in southern California. We calculated relative concentration of use estimates for each management unit for each California Condor (n = 21) on an annual basis (n = 39 annual home ranges) and evaluated resource selection for the population each year using the individual as our sampling unit. The most striking result from our analysis was the recolonization of the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units during 2008. During 2004-07, the home range estimate for two (25 percent) California Condors overlapped the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units (n = 8), and use within the annual home range generally was bimodal and was concentrated on the Bitter Creek and Hopper Mountain National Wildlife Refuges. However, 10 (77 percent) California Condor home ranges overlapped the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units during 2008 (n = 13), and by 2009, the home range of every condor carrying a Global Positioning System transmitter (n = 14) overlapped these management units. Space use was multimodal within the home range during 2008-09 and was concentrated on Hopper Mountain Refuge in the south, Bittercreek Refuge and the Wind Wolves Preserve in the northwest, and the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units in the northeast. Recolonization of the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units reestablished traditional condor movement and foraging patterns in southern California and provides the travel corridor (approximately 20 kilometers wide) for recolonization of the northeastern part of the species historical range.

Open-File Report↗

USGS1998

Analysis of the sensitivity of soils to the leaching of agricultural pesticides in Ohio

Pesticides have not been found frequently in the ground waters of Ohio even though large amounts of agricultural pesticides are applied to fields in Ohio every year. State regulators, including representatives from Ohio Environmental Protection Agency and Departments of Agriculture, Health, and Natural Resources, are striving to limit the presence of pesticides in ground water at a minimum. A proposed pesticide management plan for the State aims at protecting Ohio's ground water by assessing pesticide-leaching potential using geographic information system (GIS) technology and invoking a monitoring plan that targets aquifers deemed most likely to be vulnerable to pesticide leaching. The U.S. Geological Survey, in cooperation with Ohio Department of Agriculture, assessed the sensitivity of mapped soil units in Ohio to pesticide leaching. A soils data base (STATSGO) compiled by U.S. Department of Agriculture was used iteratively to estimate soil units as being of high to low sensitivity on the basis of soil permeability, clay content, and organic-matter content. Although this analysis did not target aquifers directly, the results can be used as a first estimate of areas most likely to be subject to pesticide contamination from normal agricultural practices. High-sensitivity soil units were found in lakefront areas and former lakefront beach ridges, buried valleys in several river basins, and parts of central and south- central Ohio. Medium-high-sensitivity soil units were found in other river basins, along Lake Erie in north-central Ohio, and in many of the upland areas of the Muskingum River Basin. Low-sensitivity map units dominated the northwestern quadrant of Ohio.

Water-Resources Investigations Report↗

USGS2015

Shift in Global Tantalum Mine Production, 2000–2014

Introduction Tantalum has a unique set of properties that make it useful in a number of diverse applications. The ability of the metal to store and release electrical energy makes it ideally suited for use in certain types of capacitors that are widely used in modern electronics. Approximately 60 percent of global tantalum consumption is in the electronics industry. The ductility and corrosion resistance of the metal lends itself to application in the chemical processing industry, and its high melting point and high strength retention at elevated temperatures make it an important component of super alloys used in aircraft engines. As a major industrialized nation, the United States is a leading consumer of tantalum and tantalum-containing products. Domestic deposits typically are of low grade, and no tantalum has been recovered from mining activities in the United States since 1959. Consequently, the United States is nearly completely reliant on imports to meet its domestic consumption of tantalum for economic and national security needs. The recovery of tantalum from mine production is economically viable in only a few countries. Although developed countries dominated tantalum mine production in the early 2000s, production today is dominated by countries in the Great Lakes Region of Africa. There is concern that the sales of minerals, including columbite-tantalite or “coltan,” a mineral from which tantalum is derived, have helped finance rebel groups accused of violating human rights as part of the continuing armed conflict in the Democratic Republic of the Congo (DRC) and neighboring countries. These accusations have prompted the passage of legislation in the United States to curb the procurement of these mineral commodities, referred to as “conflict minerals,” from the DRC. Specifically, section 1502 of the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act (Public Law 111–203, 124 Stat. 2213–2218) requires companies that source tantalum, tin, tungsten, and gold (3TG) to perform due diligence on their supply chains to determine if the materials they use originate from the DRC or adjoining countries (defined as sharing a border with the DRC). The DRC, Rwanda, and surrounding countries are not globally significant sources of tin, tungsten, or gold, accounting for only about 2 percent of the mined world supply for each of these elements. The region has, however, evolved to become the world’s largest producer of mined tantalum. A further complication of the production of tantalum stems from the opacity of the tantalum market. Unlike most base and precious metals, tantalum concentrates are not publicly traded through commodities exchanges but are bought and sold through networks of dealers and on contract between producers and consumers, some of whom may not provide accurate statistical data concerning the amounts, origins, and destination of the concentrates. Some price data can be found in trade journals or in other publications; however, there are no recognized official set exchange prices for either concentrate or tantalum metal. Because price is determined by negotiation between buyer and seller, published prices for concentrate are probably not representative of global prices paid for concentrate. The development of a mine-to-market supply-chain analysis is complicated and difficult because many of the industry participants that produce, trade, and consume tantalum do not publish statistical information, contracts are long term between miners and buyers, and much of the industry is vertically integrated. As a result of these and other considerations, tantalum is considered by many to be a “critical” commodity. This fact sheet identifies and addresses the major geographic shifts in the source of mine production of tantalum which have occurred over the past 15 years, some of the factors that drove this shift, and some of the related consequences. One of the activities of the U.S. Geological Survey National Minerals Information Center (USGS-NMIC) is to analyze global supply chains and characterize major components of mineral and material flows from ore extraction through processing to first tier products. These analyses support the core mission of the USGS-NMIC as the Federal entity responsible for the collection, analysis, and dissemination of objective, unbiased, factual information on minerals essential to the U.S. economy and national security.

Fact Sheet↗

USGS2019

A hydrogeomorphic classification of connectivity of large rivers of the Upper Midwest, United States

River connectivity is defined as the water-mediated exchange of matter, energy, and biota between different elements of the riverine landscape. Connectivity is an especially important concept in large-river corridors (channel plus floodplain ) because large rivers integrate fluxes of water, sediment, nutrients, contaminants, and other transported constituents emanating from large contributing drainage basins, and thereby contribute to the complexity of large-river ecosystems. Large rivers are also highly valued for socioeconomic goods and services, which has led to historical fragmentation, lack of connectivity, and contentiousness about best policies for managing large-river corridors. The classification is intended to serve as a template for understanding geographic variation in large rivers within the Midwest, to aid in designing scientific studies of large river ecological processes, and to match specific river-management and restoration objectives to specific river reaches. The focus of the classification is on measuring river connectivity from available hydrological and geomorphic data. We provide a multiscale assessment and classification for segments of 15 rivers that meet various criteria for largeness. All rivers are tributaries to the Mississippi River system. The 11,600 kilometers (km) that qualified as large were classified by major alterations (unimpounded, navigation pools, storage reservoir) and additionally assessed for their network continuity as a function of numbers and heights of dams. Among the 15 rivers, 55 percent of segment length was unimpounded, 30 percent was in navigation pools, and 15 percent was under storage reservoirs. Assessment of network longitudinal connectivity among river segments documented the contrast between river segments with low-head navigation dams (Upper Mississippi, Illinois, Ohio, Green, and Cumberland Rivers) and those segments with high-head dams (mostly in the Upper Missouri River). The longest unimpounded river pathways exist in the Lower Missouri River and connected tributaries where nearly 1,300 km of the Missouri River connect to an additional 1,800 km of the Middle and Lower Mississippi Rivers. At our finest scale, we present a statistically based, component classification based on 10-km segments. Cluster analysis of hydrologic variables from 66 streamflow-gaging stations yielded 5 clusters calculated from 5 ecohydrological metrics related to lateral connectivity with the floodplain. A separate cluster analysis of 5 geomorphologic variables associated with each of the 1,172 river segments also yielded 5 clusters. When the hydrologic variables were associated with corresponding segments, the cluster analysis yielded 8 hydrogeomorphic clusters that could be explained in terms of their contribution to floodplain connectivity. Although the clusters overlap considerably in principal component space, the resulting hydrogeomorphic classification leads to a physically reasonable distribution of classes. The resulting classification is intended to increase geographic awareness of the range of variation of connectivity potential among large rivers of the Upper Midwest, to increase understanding of the extent of alteration of these rivers, and potentially to serve as a template for stratifying study designs of large-river corridor ecological processes.

Colorado, Illinois, Indiana, Iowa, Kansas, Kentuck↗

USGS2002

A palynological biozonation for the Maastrichtian Stage (Upper Cretaceous) of South Carolina, USA

Three palynological biozones are proposed for the Maastrichtian Stage of South Carolina. In ascending stratigraphic order, the biozones are the Carolinapollis triangularis (Ct) Interval Biozone, the Holkopollenites chemardensis (Hc) Interval Biozone, and the Sparganiaceaepollenites uniformis (Su) Interval Biozone. Integration of the biostratigraphy with lithologic and geophysical log data suggests that within the study area, the upper and lower boundaries of each zone are bounded by regional unconformities, and that a three-fold subdivision of the Maastrichtian Stage is warranted. The biozonation is based on the analysis of 114 samples from 24 subsurface and three outcrop sections from the Coastal Plain of South Carolina; samples from an additional seven subsurface and 18 outcrop sections from North Carolina and Georgia were examined to evaluate the geographic extent of the biozones. One new genus and five new species of pollen are described, and emendations are presented for two genera and one species of pollen. ?? 2003 Published by Elsevier Science Ltd.

Cretaceous Research↗