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USGS2000

Mapping and converting essential Federal Geographic Data Committee (FGDC) metadata into MARC21 and Dublin Core: towards an alternative to the FGDC Clearinghouse

The purpose of this article is to raise and address a number of issues related to the conversion of Federal Geographic Data Committee metadata into MARC21 and Dublin Core. We present an analysis of 466 FGDC metadata records housed in the National Biological Information Infrastructure (NBII) node of the FGDC Clearinghouse, with special emphasis on the length of fields and the total length of records in this set. One of our contributions is a 34 element crosswalk, a proposal that takes into consideration the constraints of the MARC21 standard as implemented in OCLC's World Cat and the realities of user behavior.

D-Lib↗

USGS2001

Preliminary evaluation of the importance of existing hydraulic-head observation locations to advective-transport predictions, Death Valley regional flow system, California and Nevada

When a model is calibrated by nonlinear regression, calculated diagnostic statistics and measures of uncertainty provide a wealth of information about many aspects of the system. This report presents a method of ranking the likely importance of existing observation locations using measures of prediction uncertainty. It is suggested that continued monitoring is warranted at more important locations, and unwarranted or less warranted at less important locations. The report develops the methodology and then demonstrates it using the hydraulic-head observation locations of a three-layer model of the Death Valley regional flow system. The predictions of interest are subsurface transport from beneath Yucca Mountain and 14 Underground Test Areas. The advective component of transport is considered because it is the component most affected by the system dynamics represented by the scale model being used. The problem is addressed using the capabilities of the U.S. Geological Survey computer program MODFLOW-2000, with its ADVective-Travel Observation (ADV) Package, and an additional computer program developed for this work. The methods presented in this report are used in three ways. (1) The ratings for individual observations are obtained by manipulating the measures of prediction uncertainty, and do not involve recalibrating the model. In this analysis, observation locations are each omitted individually and the resulting increase in uncertainty in the predictions is calculated. The uncertainty is quantified as standard deviations on the simulated advective transport. The increase in uncertainty is quantified as the percent increase in the standard deviations caused by omitting the one observation location from the calculation of standard deviations. In general, observation locations associated with larger increases are rated as more important. (2) Ratings for largely geographically based groups are obtained using a straightforward extension of the method used for individual observation locations. This analysis is needed where observations are clustered to determine whether the area is important to the predictions of interest. (3) Finally, the method is used to evaluate omitting a set of 100 observation locations. The locations were selected because they had low individual ratings and were not one of the few locations at which hydraulic heads from deep in the system were measured. The major results of the three analyses, when applied to the three-layer DVRFS ground-water flow system, are described in the following paragraphs. The discussion is labeled using the numbers 1 to 3 to clearly relate it to the three ways the method is used, as listed above. (1) The individual observation location analysis indicates that three observation locations are most important. They are located in Emigrant Valley, Oasis Valley, and Beatty. Of importance is that these and other observations shown to be important by this analysis are far from the travel paths considered. This displays the importance of the regional setting within which the transport occurs, the importance of including some sites throughout the area in the monitoring network, and the importance of including sites in these areas in particular. The method considered in this report indicates that the 19 observation locations that reflect hydraulic heads deeper in the system (in model layers 1, 2, and 3) are not very important. This appears to be because the locations of these observations are in the vicinity of shallow observation locations that also generally are rated as low importance, and because the model layers are hydraulically well connected vertically. The value of deep observations to testing conceptual models, however, is stressed. As a result, the deep observations are rated higher than is consistent with the results of the analysis presented, and none of these observations are omitted in the scenario discussed under (3) below. (2) The geographic grouping of th

California, Nevada↗

USGS2018

Digital Shoreline Analysis System (DSAS) version 5.0 user guide

Overview The Digital Shoreline Analysis System (DSAS) is a freely available software application that works within the Esri Geographic Information System (ArcGIS) software. DSAS computes rate-of-change statistics for a time series of shoreline vector data. DSAS version 5.0 (v5.0) was released in December 2018 and has been tested for compatibility with ArcGIS versions 10.4 and 10.5. It is supported on Windows 7 and Windows 10 operating systems. If you use it, please cite it as follows and make note of the current version: Himmelstoss, E.A., Farris, A.S., Henderson, R.E., Kratzmann, M.G., Ergul, Ayhan, Zhang, Ouya, Zichichi, J.L., Thieler, E. R., 2018, Digital Shoreline Analysis System (version 5.0): U.S. Geological Survey software release, https://code.usgs.gov/cch/dsas . This user guide describes the system requirements, installation procedures, and necessary inputs to establish measurement locations with DSAS-generated transects and compute rate-of-change calculations. Although the nomenclature for this software utility is based on use in a coastal environment, the DSAS application could be used to compute rates of change for any boundary-change problem that incorporates a clearly identified feature position at discrete times, such as glacier limits, river banks, or land use/cover boundaries.

Open-File Report↗

USGS2001

Statistical analysis of sand and gravel aggregate deposits of late Pleistocene Lake Bonneville, Utah

Sedimentary deposits of pluvial Lake Bonneville are an important source of sand and gravel suitable for aggregate and construction in Utah. Data on Lake Bonneville basin sand and gravel deposit thickness, volume, grain size, percent of fines, and durability were statistically analyzed to detect variations associated with geologic domains, geographic location, Lake Bonneville shorelines, and sand and gravel deposit type, and to construct quantitative deposit models. Analysis showed several trends; (1) sand and gravel in younger shorelines was slightly more durable and the deposits considerably larger in volume, (2) younger shorelines are also more likely to contain more than one genetic deposit type, (3) the volume of terrace deposits is larger than beach deposits, (4) terraces and beaches are generally thicker than spits and bars, (5) the northern part of the Bonneville Basin contains slightly more durable sand and gravel than the southern part of the basin and is more likely to contain deposits composed of more than one genetic deposit type, and (6) the Wasatch domain deposits are composed of more than one genetic deposit type more often than deposits of the Basin and Range domain. Three additional conclusions with immediate economic significance are; (1) the median sand and gravel deposit in the Wasatch domain, 360,000 m 3 (275,000 yd 3 ), is three times larger than that of the Basin and Range domain (120,000 m 3 [90,000 yd 3 ]), (2) the median deposit thickness in the Wasatch domain, 5.8 m (19.0 ft), is nearly twice that of the Basin and Range domain (3 m [10 ft]), and (3) the Wasatch domain also contains slightly larger diameter gravel. These three conclusions are significant because the trend for sand and gravel development in the Bonneville Basin is to move from the Wasatch domain to the Basin and Range domain. Smaller, thinner deposits with smaller diameter gravel will require more surface area to mine than would have been necessary in the Wasatch domain. The result is a higher cost for sand and gravel in construction projects in the Salt Lake City area, especially since the gravel must also be hauled further.

Idaho;Nevada;Utah↗

USGS2009

Methodology for Estimation of Flood Magnitude and Frequency for New Jersey Streams

Methodologies were developed for estimating flood magnitudes at the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for unregulated or slightly regulated streams in New Jersey. Regression equations that incorporate basin characteristics were developed to estimate flood magnitude and frequency for streams throughout the State by use of a generalized least squares regression analysis. Relations between flood-frequency estimates based on streamflow-gaging-station discharge and basin characteristics were determined by multiple regression analysis, and weighted by effective years of record. The State was divided into five hydrologically similar regions to refine the regression equations. The regression analysis indicated that flood discharge, as determined by the streamflow-gaging-station annual peak flows, is related to the drainage area, main channel slope, percentage of lake and wetland areas in the basin, population density, and the flood-frequency region, at the 95-percent confidence level. The standard errors of estimate for the various recurrence-interval floods ranged from 48.1 to 62.7 percent. Annual-maximum peak flows observed at streamflow-gaging stations through water year 2007 and basin characteristics determined using geographic information system techniques for 254 streamflow-gaging stations were used for the regression analysis. Drainage areas of the streamflow-gaging stations range from 0.18 to 779 mi2. Peak-flow data and basin characteristics for 191 streamflow-gaging stations located in New Jersey were used, along with peak-flow data for stations located in adjoining States, including 25 stations in Pennsylvania, 17 stations in New York, 16 stations in Delaware, and 5 stations in Maryland. Streamflow records for selected stations outside of New Jersey were included in the present study because hydrologic, physiographic, and geologic boundaries commonly extend beyond political boundaries. The StreamStats web application was developed cooperatively by the U.S. Geological Survey and the Environmental Systems Research Institute, Inc., and was designed for national implementation. This web application has been recently implemented for use in New Jersey. This program used in conjunction with a geographic information system provides the computation of values for selected basin characteristics, estimates of flood magnitudes and frequencies, and statistics for stream locations in New Jersey chosen by the user, whether the site is gaged or ungaged.

Scientific Investigations Report↗

USGS2002

Estimating the magnitude of peak flows at selected recurrence intervals for streams in Idaho

Methods for estimating magnitudes of peak flows at various recurrence intervals, needed for highway-structure and water-control design and planning, were developed for gaged and ungaged sites on streams throughout Idaho. Recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years were selected for analysis of peak flows. For gaged sites in Idaho, peak-flow estimates were calculated by fitting a log-Pearson Type III distribution to the annual peak-flow data for each site. Annual peak flows through 1997 were used in the analysis. Basin and climatic characteristics for these gaged sites were calculated from 1:24,000 digitalelevation models and various thematic data coverages using a geographic information system. Peak- flow data and basin and climatic characteristics for 333 gaged sites were combined to develop a database that was used for the analysis. To estimate the magnitude of peak flows at ungaged sites near gaged sites on the same stream, a method was developed on the basis of drainage-area ratios. To estimate the magnitude of peak flows for ungaged sites on unregulated and undiverted streams, two regional regression methods were developed. The first regression method, termed the regional regression method, used generalized least-squares regression to develop a set of predictive equations for estimating peak flows at selected recurrence intervals for seven hydrologic regions in Idaho. These regional regression equations related basin and climatic characteristics to peak flows. The regional regression equations were all functions of drainage area plus one or two other basin characteristics. Average errors of prediction for these regression equations ranged from +143 percent to 58.8 percent. The range of errors was narrowest, from about +51.9 to about 34.2, for region 5. Error ranges were usually narrower for the middle recurrence intervals than for the lower and upper recurrence intervals. A computer program was developed to calculate the magnitude of peak flows at each recurrence interval, the average error of prediction, and the 90-percent confidence interval for each ungaged site. The second regression method, termed the region-of-influence method, was used to develop a unique regression equation for each estimate that is based on a subset of gaged sites with values of basin and climatic characteristics similar to those for the ungaged sites. All 333 gages in the database were used to select the subset. Root-mean-squared errors for this method ranged from 55.5 percent to 72.4 percent. Differences in root-mean-squared errors between regional regression equations and the region-of-influence method were quite large. The average difference in root-mean-squared errors for the region-of-influence method was more than 10 percent greater than the average differences for the regional regression equations. For region 5, the average difference was greater than 20 percent. However, for region 8, the root-mean-squared errors were, in general, only slightly smaller for the region-of-influence method than for the regional regression equations. The region-of-influence method is not recommended for use in determining flood-frequency estimates for ungaged sites in Idaho because the results, overall, are less accurate and the calculations are more complex than those of regional regression equations. The regional regression equations were considered to be the primary method of estimating the magnitude and frequency of peak flows for ungaged sites in Idaho.

Idaho;Montana;Nevada;Oregon;Washington;Wyoming↗

USGS2015

The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls

Estimates of species' vital rates and an understanding of the factors affecting those parameters over time and space can provide crucial information for management and conservation. We used mark–recapture, reproductive output, and territory occupancy data collected during 1985–2013 to evaluate population processes of Northern Spotted Owls ( Strix occidentalis caurina ) in 11 study areas in Washington, Oregon, and northern California, USA. We estimated apparent survival, fecundity, recruitment, rate of population change, and local extinction and colonization rates, and investigated relationships between these parameters and the amount of suitable habitat, local and regional variation in meteorological conditions, and competition with Barred Owls ( Strix varia ). Data were analyzed for each area separately and in a meta-analysis of all areas combined, following a strict protocol for data collection, preparation, and analysis. We used mixed effects linear models for analyses of fecundity, Cormack-Jolly-Seber open population models for analyses of apparent annual survival (ϕ), and a reparameterization of the Jolly-Seber capture–recapture model (i.e. reverse Jolly-Seber; RJS) to estimate annual rates of population change (λ RJS ) and recruitment. We also modeled territory occupancy dynamics of Northern Spotted Owls and Barred Owls in each study area using 2-species occupancy models. Estimated mean annual rates of population change (λ) suggested that Spotted Owl populations declined from 1.2% to 8.4% per year depending on the study area. The weighted mean estimate of λ for all study areas was 0.962 (± 0.019 SE; 95% CI: 0.925–0.999), indicating an estimated range-wide decline of 3.8% per year from 1985 to 2013. Variation in recruitment rates across the range of the Spotted Owl was best explained by an interaction between total winter precipitation and mean minimum winter temperature. Thus, recruitment rates were highest when both total precipitation (29 cm) and minimum winter temperature (−9.5°C) were lowest. Barred Owl presence was associated with increased local extinction rates of Spotted Owl pairs for all 11 study areas. Habitat covariates were related to extinction rates for Spotted Owl pairs in 8 of 11 study areas, and a greater amount of suitable owl habitat was generally associated with decreased extinction rates. We observed negative effects of Barred Owl presence on colonization rates of Spotted Owl pairs in 5 of 11 study areas. The total amount of suitable Spotted Owl habitat was positively associated with colonization rates in 5 areas, and more habitat disturbance was associated with lower colonization rates in 2 areas. We observed strong declines in derived estimates of occupancy in all study areas. Mean fecundity of females was highest for adults (0.309 ± 0.027 SE), intermediate for 2-yr-olds (0.179 ± 0.040 SE), and lowest for 1-yr-olds (0.065 ± 0.022 SE). The presence of Barred Owls and habitat covariates explained little of the temporal variation in fecundity in most study areas. Climate covariates occurred in competitive fecundity models in 8 of 11 study areas, but support for these relationships was generally weak. The fecundity meta-analysis resulted in 6 competitive models, all of which included the additive effects of geographic region and annual time variation. The 2 top-ranked models also weakly supported the additive negative effects of the amount of suitable core area habitat, Barred Owl presence, and the amount of edge habitat on fecundity. We found strong support for a negative effect of Barred Owl presence on apparent survival of Spotted Owls in 10 of 11 study areas, but found few strong effects of habitat on survival at the study area scale. Climate covariates occurred in top or competitive survival models for 10 of 11 study areas, and in most cases the relationships were as predicted; however, there was little consistency among areas regarding the relative importance of specific climate covariates. In contrast, meta-analysis results suggested that Spotted Owl survival was higher across all study areas when the Pacific Decadal Oscillation (PDO) was in a warming phase and the Southern Oscillation Index (SOI) was negative, with a strongly negative SOI indicative of El Niño events. The best model that included the Barred Owl covariate (BO) was ranked 4 th and also included the PDO covariate, but the BO effect was strongly negative. Our results indicated that Northern Spotted Owl populations were declining throughout the range of the subspecies and that annual rates of decline were accelerating in many areas. We observed strong evidence that Barred Owls negatively affected Spotted Owl populations, primarily by decreasing apparent survival and increasing local territory extinction rates. However, the amount of suitable owl habitat, local weather, and regional climatic patterns also were related to survival, occupancy (via colonization rate), recruitment, and, to a lesser extent, fecundity, although there was inconsistency in regard to which covariates were important for particular demographic parameters or across study areas. In the study areas where habitat was an important source of variation for Spotted Owl demographics, vital rates were generally positively associated with a greater amount of suitable owl habitat. However, Barred Owl densities may now be high enough across the range of the Northern Spotted Owl that, despite the continued management and conservation of suitable owl habitat on federal lands, the long-term prognosis for the persistence of Northern Spotted Owls may be in question without additional management intervention. Based on our study, the removal of Barred Owls from the Green Diamond Resources (GDR) study area had rapid, positive effects on Northern Spotted Owl survival and the rate of population change, supporting the hypothesis that, along with habitat conservation and management, Barred Owl removal may be able to slow or reverse Northern Spotted Owl population declines on at least a localized scale.

California, Oregon, Washington↗

USGS2007

USGS national surveys and analysis projects: Preliminary compilation of integrated geological datasets for the United States

The growth in the use of Geographic nformation Systems (GS) has highlighted the need for regional and national digital geologic maps attributed with age and rock type information. Such spatial data can be conveniently used to generate derivative maps for purposes that include mineral-resource assessment, metallogenic studies, tectonic studies, human health and environmental research. n 1997, the United States Geological Survey’s Mineral Resources Program initiated an effort to develop national digital databases for use in mineral resource and environmental assessments. One primary activity of this effort was to compile a national digital geologic map database, utilizing state geologic maps, to support mineral resource studies in the range of 1:250,000- to 1:1,000,000-scale. Over the course of the past decade, state databases were prepared using a common standard for the database structure, fields, attributes, and data dictionaries. As of late 2006, standardized geological map databases for all conterminous (CONUS) states have been available on-line as USGS Open-File Reports. For Alaska and Hawaii, new state maps are being prepared, and the preliminary work for Alaska is being released as a series of 1:500,000-scale regional compilations. See below for a list of all published databases.

Conference Paper↗

USGS1998

Geographic, temporal, and age-specific variation in diets of Glaucous Gulls in western Alaska

We collected boluses and food remains of adult Glaucous Gulls (Larus hyperboreus) at or near nests and chicks, and digestive tracts from adults at three sites on the Yukon-Kuskokwim Delta, Alaska that differed in proximity to marine and terrestrial foods. We observed both geographic and temporal variation in diet; gulls consumed proportionately more terrestrial prey after peak hatch in late June, and gulls near the coast consumed proportionately more marine prey than gulls at two inland areas. Goslings occurred in > 60% of all samples from these inland areas. We compared these data to those from a previous study in western Alaska and found no marked differences. Evidence for similar patterns of geographic and temporal variation in diet was found using measurements of stable-carbon and nitrogen isotopes in gull and prey tissues. Stable isotope analysis further revealed that adult gulls consumed proportionately more marine prey (saffron cod, Eleginus gracilis) than they fed to their young. Using isotopic models, we estimated that 7-22% and 10-23% of the diet of adult and juvenile Glaucous Gulls, respectively, was comprised of terrestrial species. In addition to significant age-related variation, dietary estimates varied among geographic areas and between pre- and post-hatch periods. Overall, our isotopic estimates of the contribution of terrestrial prey to the diet of Glaucous Gulls was less than what may be inferred from conventional methods of diet analysis. Our study emphasizes the benefit of combining stable-isotope and conventional analyses to infer temporal and geographic changes in diet of wild birds and other organisms.

Condor↗

USGS2022

Characteristics and sources of intense geoelectric fields in the United States: Comparative analysis of multiple geomagnetic storms

Intense geoelectric fields during geomagnetic storms drive geomagnetically induced currents in power grids and other infrastructure, yet there are limited direct measurements of these storm-time geoelectric fields. Moreover, most previous studies examining storm-time geoelectric fields focused on single events or small geographic regions, making it difficult to determine the typical source(s) of intense geoelectric fields. We perform the first comparative analysis of (a) the sources of intense geoelectric fields over multiple geomagnetic storms, (b) using 1-s cadence geoelectric field measurements made at (c) magnetotelluric survey sites distributed widely across the United States. Temporally localized intense perturbations in measured geoelectric fields with prominences (a measure of the relative amplitude of geoelectric field enhancement above the surrounding signal) of at least 500 mV/km were detected during geomagnetic storms with Dst minima ( Dst min ) of less than −100 nT from 2006 to 2019. Most of the intense geoelectric fields were observed in resistive regions with magnetic latitudes greater than 55° even though we have 167 sites located at lower latitudes during geomagnetic storms of −200 nT ≤ Dst min < −100 nT . Our study indicates intense short-lived (<1 min) and geoelectric field perturbations with periods on the order of 1–2 min are common. Most of these perturbations cannot be resolved with 1-min data because they correspond to higher frequency or impulsive phenomena that vary on timescales shorter than that sampling interval. The sources of geomagnetic perturbations inducing these intense geoelectric fields include interplanetary shocks, interplanetary magnetic field turnings, substorms, and ultralow frequency waves.

Space Weather↗

USGS2016

Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012

Estimates of the magnitude and frequency of floods are needed across Alaska for engineering design of transportation and water-conveyance structures, flood-insurance studies, flood-plain management, and other water-resource purposes. This report updates methods for estimating flood magnitude and frequency in Alaska and conterminous basins in Canada. Annual peak-flow data through water year 2012 were compiled from 387 streamgages on unregulated streams with at least 10 years of record. Flood-frequency estimates were computed for each streamgage using the Expected Moments Algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows. A multiple Grubbs-Beck test was used to identify potentially influential low floods in the time series of peak flows for censoring in the flood frequency analysis. For two new regional skew areas, flood-frequency estimates using station skew were computed for stations with at least 25 years of record for use in a Bayesian least-squares regression analysis to determine a regional skew value. The consideration of basin characteristics as explanatory variables for regional skew resulted in improvements in precision too small to warrant the additional model complexity, and a constant model was adopted. Regional Skew Area 1 in eastern-central Alaska had a regional skew of 0.54 and an average variance of prediction of 0.45, corresponding to an effective record length of 22 years. Regional Skew Area 2, encompassing coastal areas bordering the Gulf of Alaska, had a regional skew of 0.18 and an average variance of prediction of 0.12, corresponding to an effective record length of 59 years. Station flood-frequency estimates for study sites in regional skew areas were then recomputed using a weighted skew incorporating the station skew and regional skew. In a new regional skew exclusion area outside the regional skew areas, the density of long-record streamgages was too sparse for regional analysis and station skew was used for all estimates. Final station flood frequency estimates for all study streamgages are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities. Regional multiple-regression analysis was used to produce equations for estimating flood frequency statistics from explanatory basin characteristics. Basin characteristics, including physical and climatic variables, were updated for all study streamgages using a geographical information system and geospatial source data. Screening for similar-sized nested basins eliminated hydrologically redundant sites, and screening for eligibility for analysis of explanatory variables eliminated regulated peaks, outburst peaks, and sites with indeterminate basin characteristics. An ordinary least‑squares regression used flood-frequency statistics and basin characteristics for 341 streamgages (284 in Alaska and 57 in Canada) to determine the most suitable combination of basin characteristics for a flood-frequency regression model and to explore regional grouping of streamgages for explaining variability in flood-frequency statistics across the study area. The most suitable model for explaining flood frequency used drainage area and mean annual precipitation as explanatory variables for the entire study area as a region. Final regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability discharge in Alaska and conterminous basins in Canada were developed using a generalized least-squares regression. The average standard error of prediction for the regression equations for the various annual exceedance probabilities ranged from 69 to 82 percent, and the pseudo-coefficient of determination (pseudo-R 2 ) ranged from 85 to 91 percent. The regional regression equations from this study were incorporated into the U.S. Geological Survey StreamStats program for a limited area of the State—the Cook Inlet Basin. StreamStats is a national web-based geographic information system application that facilitates retrieval of streamflow statistics and associated information. StreamStats retrieves published data for gaged sites and, for user-selected ungaged sites, delineates drainage areas from topographic and hydrographic data, computes basin characteristics, and computes flood frequency estimates using the regional regression equations.

Alaska↗

USGS2006

Chapter 4: The GIS Project for the Geologic Assessment of Undiscovered Oil and Gas in the Upper Cretaceous Navarro and Taylor Groups, Western Gulf Province, Texas

A geographic information system (GIS) focusing on the Upper Cretaceous Navarro and Taylor Groups in the Gulf Coast region was developed as a visual-analysis tool for the U.S. Geological Survey's 2003 assessment of undiscovered, technically recoverable oil and natural gas resources in the Western Gulf Province. The Central Energy Resources Team of the U.S. Geological Survey has also developed an Internet Map Service to deliver the GIS data to the general public. This mapping tool utilizes information from a database about the oil and natural gas endowment of the United States - including physical locations of geologic and geographic data - and converts the data into visual layers. Portrayal and analysis of geologic features on an interactive map provide an excellent tool for understanding domestic oil and gas resources for strategic planning, formulating economic and energy policies, evaluating lands under the purview of the Federal Government, and developing sound environmental policies. Assessment results can be viewed and analyzed or downloaded from the internet web site.

Data Series↗

USGS1991

Hydrogeologic information in the Great Lakes basin, United States, and application of a geographic information system to public supply wells and hazardous-waste sites

A computerized data base has been established to facilitate analysis and interpretation of potential for ground-water contamination in the Great Lakes basin. The computerized data base is being used in conjunction with a geogrpahic information system (GIS). Locations of public-supply wells were obtained from Federal and State agencies and stored in the system. Well locations are displayed using the Albers equal-area projection. A GIS was used to create a map of public-supply wells and a map of combined waste sites and public-supply wells. A comprehensive bibliography of 1,114 references, published during the period 1960-86, pertaining to hydrogeologic studies in the Great Lakes basin and geographic information systems, has been compiled using a relational data-base program. Where possible, references are indexed by State and county to assist in determining areas where additional study is necessary.

Great Lakes basin↗

USGS2006

Expressed MHC class II genes in sea otters (Enhydra lutris) from geographically disparate populations

The major histocompatibility complex (MHC) is central to maintaining the immunologic vigor of individuals and populations. Classical MHC class II genes were targeted for partial sequencing in sea otters ( Enhydra lutris ) from populations in California, Washington, and Alaska. Sequences derived from sea otter peripheral blood leukocyte mRNAs were similar to those classified as DQA , DQB , DRA , and DRB in other species. Comparisons of the derived amino acid compositions supported the classification of these as functional molecules from at least one DQA , DQB , and DRA locus and at least two DRB loci. While limited in scope, phylogenetic analysis of the DRB peptide‐binding region suggested the possible existence of distinct clades demarcated by geographic region. These preliminary findings support the need for additional MHC gene sequencing and expansion to a comprehensive study targeting additional otters.

Tissue Antigens↗

USGS2021

Genetic and morphological characterization of the freshwater mussel clubshell species complex (Pleurobema clava and Pleurobema oviforme) to inform conservation planning

The shell morphologies of the freshwater mussel species Pleurobema clava (federally endangered) and Pleurobema oviforme (species of concern) are similar, causing considerable taxonomic confusion between the two species over the last 100 years. While P. clava was historically widespread throughout the Ohio River basin and tributaries to the lower Laurentian Great Lakes, P. oviforme was confined to the Tennessee and the upper Cumberland River basins. We used two mitochondrial DNA (mtDNA) genes, 13 novel nuclear DNA microsatellite markers, and shell morphometrics to help resolve this taxonomic confusion. Evidence for a single species was apparent in phylogenetic analyses of each mtDNA gene, revealing monophyletic relationships with minimal differentiation and shared haplotypes. Analyses of microsatellites showed significant genetic structuring, with four main genetic clusters detected, respectively, in the upper Ohio River basin, the lower Ohio River and Great Lakes, and upper Tennessee River basin, and a fourth genetic cluster, which included geographically intermediate populations in the Ohio and Tennessee river basins. While principal components analysis (PCA) of morphometric variables (i.e., length, height, width, and weight) showed significant differences in shell shape, only 3% of the variance in shell shape was explained by nominal species. Using Linear Discriminant and Random Forest (RF) analyses, correct classification rates for the two species' shell forms were 65.5% and 83.2%, respectively. Random Forest classification rates for some populations were higher; for example, for North Fork Holston (HOLS), it was >90%. While nuclear DNA and shell morphology indicate that the HOLS population is strongly differentiated, perhaps indicative of cryptic biodiversity, we consider the presence of a single widespread species the most likely biological scenario for many of the investigated populations based on our mtDNA dataset. However, additional sampling of P. oviforme populations at nuclear loci is needed to corroborate this finding.

Indiana, Kentucky, Ohio, Pennsylvania, Tennessee, ↗

USGS2014

Regional differentiation among populations of the Diamondback terrapin ( Malaclemys terrapin )

The Diamondback terrapin (Malaclemys terrapin) is a brackish-water turtle species whose populations have been fragmented due to anthropogenic activity such as development of coastal habitat and entrapment in commercial blue crab (Callinectes sapidus) fishing gear. Genetic analyses can improve conservation efforts for the long-term protection of the species. We used microsatellite DNA analysis to investigate levels of gene flow among and genetic variability within 21 geographically separate collections of the species distributed from Massachusetts to Texas. Quantified levels of genetic variability (allelic diversity, genotypic frequencies, and heterozygosity) revealed three zones of genetic discontinuity, resulting in four discrete populations: Northeast Atlantic, Coastal Mid-Atlantic, Florida and Texas/Louisiana. The average number of alleles and expected heterozygosity for the four genetic clusters were N A = 6.54 and H E = 0.050, respectively. However, the geographic boundaries of the populations did not correspond to accepted terrapin subspecies limits. Our results illuminate not only the need to sample terrapins in additional sites, specifically in the southeast, but also the necessity for allowing uninterrupted gene flow among population groupings to preserve current levels of genetic diversity.

Conservation Genetics↗

USGS2021

Assessment of peak flow scaling and Its effect on flood quantile estimation in the United Kingdom

Regional flood frequency analysis (RFFA) methods are essential tools to assess flood hazard and plan interventions for its mitigation. They are used to estimate flood quantiles when the at‐site record of streamflow data is not available or limited. One commonly used RFFA method is the index flood method (IFM), which assumes that peak floods satisfy the simple scaling hypothesis. In this work we present an integrated approach to assess the spatial scaling behavior of floods in the United Kingdom (UK) for 540 catchments, where the IFM is currently used operationally. This assessment employs product moments, probability weighted moments, and quantile analysis, and is applied to two different types of “hydrologically homogeneous” UK regions: geographical regions as defined in the Flood Studies Report (NERC, 1975) and pooling‐groups as defined in the updated Flood Estimation Handbook (FEH; Institute of Hydrology, 1999). To understand which variables play a significant role in the flood‐peak generating mechanism, the assessment approach considers scaling not only of drainage area alone but also of other hydro‐geomorphological variables. Results provided by the different methodologies consistently showed that only part (ranging from 30% to 70%) of the peak flow variability is explained by drainage area alone; this fraction increases (up to 80%–95%) when multiple regression is used. Supported by the peak flow spatial scaling assessment, we compared the proposed approach for peak flow quantile estimation with the current FEH method in ungauged catchments. The quantile regression method based on the pooling‐group outperforms the current FEH‐ungauged method, providing a 14% relative improvement in root mean square error over the entire country.

Water Resources Research↗

USGS2007

Land-Cover Change in the Southern Lake Tahoe Basin, California and Nevada, 1940-2002

The Lake Tahoe basin has been subject to significant landscape-altering human activity since the mid-1850s; in particular, widespread timber harvest from the 1850s to 1920s and urban development from the 1950s to the present. The consequences of changes such as impacted water quality, degraded biotic communities, and increased fire hazard resulting from modern activity have prompted rising levels of concern for the ecological integrity of the region. The goal of this project is to map, quantify, and describe the spatial and temporal distribution and variability of historical changes in land use and land cover in the southern Lake Tahoe basin for the period from 1940 to 2002 in an effort to establish an understanding of regional landscape change. This map shows areas of land-use/land-cover change in a 279-km2 portion of the Lake Tahoe basin identified using change-detection analysis of multitemporal land-use/land-cover datasets for four dates (1940, 1969, 1987, and 2002), which yielded three periods for analysis. Land use/land cover was mapped using manual (visual) interpretation techniques in a geographic information system (GIS) from multiple imagery sources: black-and-white digital orthophotos for 1940 and 1969, natural-color digital orthophotos for 1987, and IKONOS multispectral satellite imagery for 2002. The landscape was classified using a 0.4-hectare (1-acre) minimum mapping unit and a hierarchical classification system. Impervious-surface data was derived directly from the 2002 IKONOS imagery on a per-pixel basis using digital image processing and GIS data integration.

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