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At least 667 records · Page 37Linked to original sources
USGS2009

TerraLook: A GIS-ready time-series of satellite imagery

The goal of TerraLook is to provide satellite images that anyone can use to see changes in the Earth's surface over time. Landsat and other satellites have been collecting images of the Earth from Space for more than 35 years. TerraLook allows users to create their own collections of georeferenced simulated natural-color JPEG images from Landsat (circa 1975, 1990, 2005) and ASTER (2000 to present) at no charge. The simulated natural colors in TerraLook images are consistently processed so that images from these time periods can be easily compared. TerraLook images are bundled with stands- compliant metadata, a world file, and an outline of each image's ground footprint, enabling their use in Geographic Information Systems and Web mapping applications. Different ArcGIS solutions were developed to use with TerraLook Collections. For ArcGIS and ArcGIS Explorer users, project files are available to permit TerraLook Collections to be easily integrated into GIS projects of educational curricula for visual analysis. A Pythion Script is available to extract vector data, such as country boundaries, protected areas, hydrography, and populated places, from global datasets to create extended TerraLook collections. Users can add local data, included ground photography, to the TerraLook Collections, These localized collections can be easily shared. An ArcGIS Publisher tool is provided with the ArcMap project file for publishing documents for use with the free ArcReader application.

Conference Paper↗
USGS2014

Accounting for imperfect detection and survey bias in statistical analysis of presence-only data

Aim During the past decade ecologists have attempted to estimate the parameters of species distribution models by combining locations of species presence observed in opportunistic surveys with spatially referenced covariates of occurrence. Several statistical models have been proposed for the analysis of presence-only data, but these models have largely ignored the effects of imperfect detection and survey bias. In this paper I describe a model-based approach for the analysis of presence-only data that accounts for errors in the detection of individuals and for biased selection of survey locations. Innovation I develop a hierarchical, statistical model that allows presence-only data to be analysed in conjunction with data acquired independently in planned surveys. One component of the model specifies the spatial distribution of individuals within a bounded, geographic region as a realization of a spatial point process. A second component of the model specifies two kinds of observations, the detection of individuals encountered during opportunistic surveys and the detection of individuals encountered during planned surveys. Main conclusions Using mathematical proof and simulation-based comparisons, I demonstrate that biases induced by errors in detection or biased selection of survey locations can be reduced or eliminated by using the hierarchical model to analyse presence-only data in conjunction with counts observed in planned surveys. I show that a relatively small number of high-quality data (from planned surveys) can be used to leverage the information in presence-only observations, which usually have broad spatial coverage but may not be informative of both occurrence and detectability of individuals. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. In addition, since the point-process model is formulated at the level of an individual, it can be extended to account for biological interactions between individuals and temporal changes in their spatial distributions.

Global Ecology and Biogeography↗
USGS2017

Elevation Difference and Bouguer Anomaly Analysis Tool (EDBAAT) User's Guide

This report describes a software tool that imports gravity anomaly point data from the Gravity Database of the United States (GDUS) of the National Geospatial-Intelligence Agency and University of Texas at El Paso along with elevation data from The National Map (TNM) of the U.S. Geological Survey that lie within a user-specified geographic area of interest. Further, the tool integrates these two sets of data spatially and analyzes the consistency of the elevation of each gravity station from the GDUS with TNM elevation data; it also evaluates the consistency of gravity anomaly data within the GDUS data repository. The tool bins the GDUS data based on user-defined criteria of elevation misfit between the GDUS and TNM elevation data. It also provides users with a list of points from the GDUS data, which have Bouguer anomaly values that are considered outliers (two standard deviations or greater) with respect to other nearby GDUS anomaly data. “Nearby” can be defined by the user at time of execution. These outputs should allow users to quickly and efficiently choose which points from the GDUS would be most useful in reconnaissance studies or in augmenting and extending the range of individual gravity studies.

Open-File Report↗
USGS2025

Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management

Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.

Hydrological Processes↗
USGS2020

Exploring the potential value of satellite remote sensing to monitor chlorophyll-a for U.S. lakes and reservoirs

Assessment of chlorophyll-a, an algal pigment, typically measured by field and laboratory in situ analyses, is used to estimate algal abundance and trophic status in lakes and reservoirs. In situ-based monitoring programs can be expensive, may not be spatially, and temporally comprehensive and results may not be available in the timeframe needed to make some management decisions, but can be more accurate, precise, and specific than remotely sensed measures. Satellite remotely sensed chlorophyll-a offers the potential for more geographically and temporally dense data collection to support estimates when used to augment or substitute for in situ measures. In this study, we compare available chlorophyll-a data from in situ and satellite imagery measures at the national scale and perform a cost analysis of these different monitoring approaches. The annual potential avoided costs associated with increasing the availability of remotely sensed chlorophyll-a values were estimated to range between $5.7 and $316 million depending upon the satellite program used and the timeframe considered. We also compared sociodemographic characteristics of the regions (both public and private lands) covered by both remote sensing and in situ data to check for any systematic differences across areas that have monitoring data. This analysis underscores the importance of continued support for both field-based in situ monitoring and satellite sensor programs that provide complementary information to water quality managers, given increased challenges associated with eutrophication, nuisance, and harmful algal bloom events.

Environmental Monitoring and Assessment↗
USGS2009

Fall diet and bathymetric distribution of deepwater sculpin (Myoxocephalus thompsonii) in Lake Huron

Deepwater sculpin Myoxocephalus thompsonii are an important component of Great Lake's offshore benthic food webs. Recent declines in deepwater sculpin abundance and changes in bathymetric distribution may be associated with changes in the deepwater food web of Lake Huron, particularly, decreased abundance of benthic invertebrates such as Diporeia. To assess how deepwater sculpins have responded to recent changes, we examined a fifteen-year time series of spatial and temporal patterns in abundance as well as the diets of fish collected in bottom trawls during fall of 2003, 2004, and 2005. During 1992-2007, deepwater sculpin abundance declined on a lake-wide scale but the decline in abundance at shallower depths and in the southern portion of Lake Huron was more pronounced. Of the 534 fish examined for diet analysis, 97% had food in the stomach. Mysis, Diporeia, and Chironomidae were consumed frequently, while sphaerid clams, ostracods, fish eggs, and small fish were found in only low numbers. We found an inverse relationship between prevalence of Mysis and Diporeia in diets that reflected geographic and temporal trends in abundance of these invertebrates in Lake Huron. Because deepwater sculpins are an important trophic link in offshore benthic food webs, declines in population abundance and changes in distribution may cascade throughout the food web and impede fish community restoration goals.

Journal of Great Lakes Research↗
USGS2013

Modelling dendritic ecological networks in space: anintegrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Ecology Letters↗
USGS2006

Shallow-landslide hazard map of Seattle, Washington

Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency (FEMA) designated Seattle as a 'Project Impact' city with the goal of encouraging the city to become more disaster resistant to the effects of landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey (USGS) collaborate to produce a landslide hazard map of the city. An exceptional data set archived by the city, containing more than 100 years of landslide data from severe storm events, allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to shallow landslides which often mobilize into debris flows, water-laden slurries that can form from shallow failures of soil and weathered bedrock, and can travel at high velocities down steep slopes. Data used for analysis consisted of a digital slope map derived from recent Light Detection and Ranging (LIDAR) imagery of Seattle, recent digital geologic mapping, and shear-strength test data for the geologic units in the surrounding area. The combination of these data layers within a Geographic Information System (GIS) platform allowed the preparation of a shallow landslide hazard map for the entire city of Seattle.

Open-File Report↗
USGS1994

Aquifer descriptions from the U.S. Geological Survey Regional Aquifer-System Analysis Program, 1978-1993

The Regional Aquifer-System Analysis Program of the U.S. Geological Survey began in 1978. The overall purpose of this program is to define the geologic, hydrologic, and geochemical framework of the Nation's most important aquifers and aquifer systems. This report summarizes the aquifer or aquifer system name, geographic area, rock units, equivalent names, lithology, thickness, hydrologic characteristics, water quality, water use, and references for 157 aquifers in 23 areas of the United States. A .zip file containing the aquifer data and data search programs (in compressed ASCII format) is included in the report.

Open-File Report↗
USGS2001

Approach for delineation of contributing areas and zones of transport to selected public-supply wells using a regional ground-water flow model, Palm Beach County, Florida

Rapid urban development and population growth in Palm Beach County, Florida, have been accompanied with the need for additional freshwater withdrawals from the surficial aquifer system. To maintain water quality, County officials protect capture areas and determine zones of transport of municipal supply wells. A multistep process was used to help automate the delineation of wellhead protection areas. A modular ground-water flow model (MODFLOW) Telescopic Mesh Refinement program (MODTMR) was used to construct an embedded flow model and combined with particle tracking to delineate zones of transport to supply wells; model output was coupled with a geographic information system. An embedded flow MODFLOW model was constructed using input and output file data from a preexisting three-dimensional, calibrated model of the surficial aquifer system. Three graphical user interfaces for use with the geographic information software, ArcView, were developed to enhance the telescopic mesh refinement process. These interfaces include AvMODTMR for use with MODTMR; AvHDRD to build MODFLOW river and drain input files from dynamically segmented linear (canals) data sets; and AvWELL Refiner, an interface designed to examine and convert well coverage spatial data layers to a MODFLOW Well package input file. MODPATH (the U.S. Geological Survey particle-tracking postprocessing program) and MODTOOLS (the set of U.S. Geological Survey computer programs to translate MODFLOW and MODPATH output to a geographic information system) were used to map zones of transport. A steady-state, five-layer model of the Boca Raton area was created using the telescopic mesh refinement process and calibrated to average conditions during January 1989 to June 1990. A sensitivity analysis of various model parameters indicates that the model is most sensitive to changes in recharge rates, hydraulic conductivity for layer 1, and leakance for layers 3 and 4 (Biscayne aquifer). Recharge (58 percent); river (canal) leakance (29 percent); and inflow through the northern, western, and southern prescribed flux model boundaries (10 percent) represent the major inflow components. Principal outflow components in the Boca Raton well field area include well discharge (56 percent), river (canal) leakance (27 percent), and water that discharges along the coast (10 percent). A particle-tracking analysis using MODPATH was conducted to better understand well-field ground-water flow patterns and time of travel. MODTOOLS was used to construct zones-of-transport spatial data for municipal supply wells. Porosity estimates were uniformly increased to study the effect of porosity on zones of transport. Where porosity was increased, the size of the zones of transport were shown to decrease.

Water-Resources Investigations Report↗
USGS1997

Use of a spatial decision support system for analysis of habitat use by wintering northern pintails

A multi-functional spatial decision support system (SDSS) was,developed at the spatial analysis branch Of the National Wetlands Research Center, and the wildlife analysis module of the system was used to study habitat use by wintering pintail. We instrumented female pintails at Catahoula Lake, Louisiana, in October of 1992-94 and located the instrumented birds weekly through the following March. Using the SDSS developed in an ARC/INFO geographical information system (GIS) - environment. We were able to visualize movements of instrumented pintails over varied environmental conditions and landscape features to determine habitat use. Weather data were used to determine factors important in the timing of movements. The analyses indicated that female pintails dispersed from Catahoula Lake, Louisiana, in three general patterns, based upon wetland conditions. Timing of movements coincided with periods of precipitation or disturbance, primarily hunting. Pintails which arrived at Catahoula Lake in October and November remained in the agricultural areas of Louisiana and Arkansas, with very limited movements to the coastal marshes or westward into the agricultural areas of Texas. Northward movements into Arkansas occurred whenever there was substantial rainfall in the agricultural regions, and northward movements generally stopped at the frost-line. No differences in adult or juvenile female movement patterns were apparent.

Louisiana↗
USGS2017

Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy

In 2014 the U.S. Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) entered into Intra-agency agreement M13PG00037 to map an area of the Oregon Outer Continental Shelf (OCS) off of Coos Bay, Oregon, under consideration for development of a floating wind energy farm. The BOEM requires seafloor mapping and site characterization studies in order to evaluate the impact of seafloor and sub-seafloor conditions on the installation, operation, and structural integrity of proposed renewable energy projects, as well as to assess the potential effects of construction and operations on archaeological resources. The mission of the USGS is to provide geologic, topographic, and hydrologic information that contributes to the wise management of the Nation's natural resources and that promotes the health, safety, and well being of the people. This information consists of maps, databases, and descriptions and analyses of the water, energy, and mineral resources, land surface, underlying geologic structure, and dynamic processes of the earth. For the Oregon OCS study, the USGS acquired multibeam echo sounder and seafloor video data surrounding the proposed development site, which is 95 km2 in area and 15 miles offshore from Coos Bay. The development site had been surveyed by Solmar Hydro Inc. in 2013 under a contract with WindFloat Pacific. The USGS subsequently produced a bathymetry digital elevation model and a backscatter intensity grid that were merged with existing data collected by the contractor. The merged grids were published along with visual observations of benthic geo-habitat from the video data in an associated USGS data release (Cochrane and others, 2015). This report includes the results of analysis of the video data conducted by Oregon State University and the geo-habitat interpretation of the multibeam echo sounder (MBES) data conducted by the USGS. MBES data was published in Cochrane and others (2015). Interpretive data associated with this publication is published in Cochrane (2017). All the data is provided as geographic information system (GIS) files that contain both Esri ArcGIS geotiffs or shapefiles. For those who do not own the full suite of Esri GIS and mapping software, the data can be read using Esri ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed August 29, 2016). Web services, which consist of standard implementations of ArcGIS representational state transfer (REST) Service and Open Geospatial Consortium (OGC) GIS web map service (WMS), also are available for all published GIS data. Web services were created using an ArcGIS service definition file, resulting in data layers that are symbolized as shown on the associated report figures. Both the ArcGIS REST Service and OGC WMS Service include all the individual GIS layers. Data layers are bundled together in a map-area web service; however, each layer can be symbolized and accessed individually after the web service is ingested into a desktop application or web map. Web services enable users to download and view data, as well as to easily add data to their own workflows, using any browser-enabled, standalone or mobile device. Though the surficial substrate is dominated by combinations of mud and sand substrate, a diverse assortment of geomorphologic features are related to geologic processes—one anticlinal ridge where bedrock is exposed, a slump and associated scarps, and pockmarks. Pockmarks are seen in the form of fields of small pockmarks, a lineation of large pockmarks with methanogenic carbonates, and areas of large pockmarks that have merged into larger variously shaped depressions. The slump appears to have originated at the pockmark lineation. Video-supervised numerical analysis of the MBES backscatter intensity data and vector ruggedness derived from the MBES bathymetry data was used to produce a substrate model called a seafloor character raster for the study area. The seafloor character raster consists of three substrate classes: soft-flat areas, hard-flat areas, and hard-rugged areas. A Coastal and Marine Ecological Classification Standard (CMECS) geoform and substrate map was also produced using depth, slope, and benthic position index classes to delineate geoform boundaries. Seven geoforms were identified in this process, including ridges, slump scars, slump deposits, basins, and pockmarks. Statistical analysis of the video data for correlations between substrate, depth, and invertebrate assemblages resulted in the identification of seven biomes: three hard-bottom biomes and four softbottom biomes. A similar analysis of vertebrate observations produces a similar set of biomes. The biome between-group dissimilarity was very high or high. Invertebrates alone represent most of the structure of the whole benthic community into different assemblages. A biotope map was generated using the seafloor character raster and the substrate and depth values of the biomes. Hard substrate biotopes were small in size and were located primarily on the ridge and in pockmarks along the pockmark lineation. The soft-bottom bitopes consisted of large contiguous areas delimited by isobaths.

Open-File Report↗
USGS2022

Extensive species diversification and marked geographic phylogenetic structure in the Mesoamerican genus Stenopelmatus (Orthoptera: Stenopelmatidae: Stenopelmatinae) revealed by mitochondrial and nuclear 3RAD data

The Jerusalem cricket subfamily Stenopelmatinae is distributed from south-western Canada through the western half of the United States to as far south as Ecuador. Recently, the generic classification of this subfamily was updated to contain two genera, the western North American Ammopelmatus , and the Mexican, and central and northern South American Stenopelmatus . The taxonomy of the latter genus was also revised, with 5, 13 and 14 species being respectively validated, declared as nomen dubium and described as new. Despite this effort, the systematics of Stenopelmatus is still far from complete. Here, we generated sequences of the mitochondrial DNA barcoding locus and performed two distinct DNA sequence-based approaches to assess the species’ limits among several populations of Stenopelmatus , with emphasis on populations from central and south-east Mexico. We reconstructed the phylogenetic relationships among representative species of the main clades within the genus using nuclear 3RAD data and carried out a molecular clock analysis to investigate its biogeographic history. The two DNA sequence-based approaches consistently recovered 34 putative species, several of which are apparently undescribed. Our estimates of phylogeny confirmed the recent generic update of Stenopelmatinae and revealed a marked phylogeographic structure within Stenopelmatus . Based on our results, we propose the existence of four species-groups within the genus (the faulkneri , talpa , Central America and piceiventris species-groups). The geographic distribution of these species-groups and our molecular clock estimates are congruent with the geological processes that took place in mountain ranges along central and southern Mexico, particularly since the Neogene. Our study emphasises the necessity to continue performing more taxonomic and phylogenetic studies on Stenopelmatus to clarify its actual species richness and evolutionary history in Mesoamerica.

Invertebrate Systematics↗
USGS2014

A Great Lakes atmospheric mercury monitoring network: evaluation and design

As many as 51 mercury (Hg) wet-deposition-monitoring sites from 4 networks were operated in 8 USA states and Ontario, Canada in the North American Great Lakes Region from 1996 to 2010. By 2013, 20 of those sites were no longer in operation and approximately half the geographic area of the Region was represented by a single Hg-monitoring site. In response, a Great Lakes Atmospheric Mercury Monitoring (GLAMM) network is needed as a framework for regional collaboration in Hg-deposition monitoring. The purpose of the GLAMM network is to detect changes in regional atmospheric Hg deposition related to changes in Hg emissions. An optimized design for the network was determined to be a minimum of 21 sites in a representative and approximately uniform geographic distribution. A majority of the active and historic Hg-monitoring sites in the Great Lakes Region are part of the National Atmospheric Deposition Program (NADP) Mercury Deposition Network (MDN) in North America and the GLAMM network is planned to be part of the MDN. To determine an optimized network design, active and historic Hg-monitoring sites in the Great Lakes Region were evaluated with a rating system of 21 factors that included characteristics of the monitoring locations and interpretations of Hg data. Monitoring sites were rated according to the number of Hg emissions sources and annual Hg emissions in a geographic polygon centered on each site. Hg-monitoring data from the sites were analyzed for long-term averages in weekly Hg concentrations in precipitation and weekly Hg-wet deposition, and on significant temporal trends in Hg concentrations and Hg deposition. A cluster analysis method was used to group sites with similar variability in their Hg data in order to identify sites that were unique for explaining Hg data variability in the Region. The network design included locations in protected natural areas, urban areas, Great Lakes watersheds, and in proximity to areas with a high density of annual Hg emissions and areas with high average weekly Hg wet deposition. In a statistical analysis, relatively strong, positive correlations in the wet deposition of Hg and sulfate were shown for co-located NADP Hg-monitoring and acid-rain monitoring sites in the Region. This finding indicated that efficiency in regional Hg monitoring can be improved by adding new Hg monitoring to existing NADP acid-rain monitoring sites. Implementation of the GLAMM network design will require Hg-wet-deposition monitoring to be: (a) continued at 12 MDN sites active in 2013 and (b) restarted or added at 9 NADP sites where it is absent in 2013. Ongoing discussions between the states in the Great Lakes Region, the Lake Michigan Air Directors Consortium (a regional planning entity), the NADP, the U.S. Environmental Protection Agency, and the U.S. Geological Survey are needed for coordinating the GLAMM network.

Great Lakes↗
USGS2011

Recovering from the ShakeOut earthquake

Recovery from an earthquake like the M7.8 ShakeOut Scenario will be a major endeavor taking many years to complete. Hundreds of Southern California municipalities will be affected; most lack recovery plans or previous disaster experience. To support recovery planning this paper 1) extends the regional ShakeOut Scenario analysis into the recovery period using a recovery model, 2) localizes analyses to identify longer-term impacts and issues in two communities, and 3) considers the regional context of local recovery.Key community insights about preparing for post-disaster recovery include the need to: geographically diversify city procurement; set earthquake mitigation priorities for critical infrastructure (e.g., airport), plan to replace mobile homes with earthquake safety measures, consider post-earthquake redevelopment opportunities ahead of time, and develop post-disaster recovery management and governance structures. This work also showed that communities with minor damages are still sensitive to regional infrastructure damages and their potential long-term impacts on community recovery. This highlights the importance of community and infrastructure resilience strategies as well.

Earthquake Spectra↗
USGS2011

Surficial geologic map of the Gates of the Arctic National Park and Preserve, Alaska

The Gates of the Arctic National Park and Preserve (GAAR) is centered over the central Brooks Range of northern Alaska. To the west, it abuts the Noatak National Preserve; its eastern boundary is the transportation corridor occupied by the Dalton Highway and the Alyeska Pipeline. The GAAR extends northward beyond the northern flank of the Brooks Range into the southern Arctic Foothills. Its southern boundary lies beyond the south flank of the Brooks Range within foothills and depositional basins of interior Alaska. The accompanying surficial geologic map covers all of the GAAR with the addition of a 10-km (6.2-mi) belt or "buffer zone" beyond its boundaries. A narrower (5-km) buffer zone is employed where the GAAR extends farthest north and south of the Brooks Range, in the north-central and southwestern parts of the map area, respectively. The surfical geologic map incorporates parts of ten surficial geologic maps previously published at 1:250,000 scale. In addition, a small part of the buffer zone mapped in the southwest corner of the map area was compiled from unpublished surficial geologic mapping of the Shungnak 1:250,000-scale quadrangle. Each of those individual maps was developed from (1) aerial and surface observations of morphology and composition of unconsolidated deposits, (2) tracing the distribution and interrelation of terraces, abandoned meltwater channels, moraines, abandoned lake beds, and other landforms, (3) stratigraphic study of exposures along lake shores and river bluffs, (4) examination of sediments and soil profiles in auger borings and test pits, and exposed in roadcuts and placer workings, and (5) analysis of previously published geologic maps and reports. The map units used for those maps and employed in the present compilation are defined on the basis of their physical character, genesis, and age. Relative and absolute ages of the map units were determined from their geographic locations and from their stratigraphic positions and radiocarbon ages.

Alaska↗
USGS2009

Streamflow-Characteristic Estimation Methods for Unregulated Streams of Tennessee

Streamflow-characteristic estimation methods for unregulated rivers and streams of Tennessee were developed by the U.S. Geological Survey in cooperation with the Tennessee Department of Environment and Conservation. Streamflow estimates are provided for 1,224 stream sites. Streamflow characteristics include the 7-consecutive-day, 10-year recurrence-interval low flow, the 30-consecutive-day, 5-year recurrence-interval low flow, the mean annual and mean summer flows, and the 99.5-, 99-, 98-, 95-, 90-, 80-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent flow durations. Estimation methods include regional regression (RRE) equations and the region-of-influence (ROI) method. Both methods use zero-flow probability screening to estimate zero-flow quantiles. A low flow and flow duration (LFFD) computer program (TDECv301) performs zero-flow screening and calculation of nonzero-streamflow characteristics using the RRE equations and ROI method and provides quality measures including the 90-percent prediction interval and equivalent years of record. The U.S. Geological Survey StreamStats geographic information system automates the calculation of basin characteristics and streamflow characteristics. In addition, basin characteristics can be manually input to the stand-alone version of the computer program (TDECv301) to calculate streamflow characteristics in Tennessee. The RRE equations were computed using multivariable regression analysis. The two regions used for this study, the western part of the State (West) and the central and eastern part of the State (Central+East), are separated by the Tennessee River as it flows south to north from Hardin County to Stewart County. The West region uses data from 124 of the 1,224 streamflow sites, and the Central+East region uses data from 893 of the 1,224 streamflow sites. The study area also includes parts of the adjacent States of Georgia, North Carolina, Virginia, Alabama, Kentucky, and Mississippi. Total drainage area, a geology factor, a climate factor, and two soil factors were used as explanatory variables in the RRE equations. Average deleted-residual prediction errors for the West-region RRE equations were 18 and 123 percent for the 10-percent flow duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for RRE equations were 21 and 89 percent for the same respective flow quantiles in the Central+East region. The ROI method calculates unique multivariable regression equations for a site of interest using the flow and basin characteristics of 45 similar streamflow-data sites selected from the same region. These 45 sites are selected using a metric that measures similarity between the site of interest and the streamflow-data sites based on total drainage area, geology factor, and climate factor. The ROI method estimates streamflow characteristics using total drainage area, geology factor, and a soil factor as explanatory variables. Average deleted-residual prediction errors for the West-region ROI equations were 18 and 125 percent for the 10-percent duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for ROI equations were 20 and 85 percent for the same respective flow quantiles in the Central+East region. In general, when compared to the RRE equations, the ROI method performs similarly in the West region and reduces streamflow-characteristic prediction errors by an average of about 7 percent in the Central+East region of Tennessee.

Scientific Investigations Report↗
USGS2023

United States Gulf of Mexico waters provide important nursery habitat for Mexico’s green turtle nesting populations

Resolving natal populations for juvenile green turtles is challenging given their potential for extensive dispersal during the oceanic stage and ontogenetic shifts among nursery habitats. Mitochondrial DNA markers have elucidated patterns of connectivity between green turtle nesting populations (rookeries) and juvenile foraging aggregations. However, missing rookery baseline data and haplotype sharing among populations have often impeded inferences, including estimating origins of Gulf of Mexico juveniles. Here, we assessed genetic structure among seven foraging aggregations spanning southern Texas (TX) to southwestern Florida (SWFL), including Port Fourchon, Louisiana (LA); a surface-pelagic aggregation (SP) offshore of Louisiana and Florida; Santa Rosa Island, Florida (SRI); St. Joseph Bay, Florida (SJB); and the Big Bend region, Florida (BB). We estimated source contributions to aggregations with novel genetic data (excluding SP and BB) using a Bayesian many-to-one mixed stock analysis (MSA) approach. Haplotype frequencies for western (TX, LA, SP, SRI) and eastern (SJB, BB, SWFL) aggregations were significantly differentiated. The largest shift in haplotype frequencies between proximal nursery sites occurred between SRI and SJB, separated by only 150 km, highlighting the lack of a geographic yardstick for predicting genetic structure. In contrast to previous MSA results, there was no signal of Florida juveniles at any foraging site. Mexican contributions dominated in all aggregations, with strong connectivity between western Bay of Campeche (Tamaulipas/Veracruz) rookeries and western foraging aggregations. MSA indicated more diverse Mexican origins for eastern aggregations, with larger inputs from the eastern Bay of Campeche (Campeche/Yucatán), Campeche Bank, and Quintana Roo rookeries. These results demonstrate the significance of the Gulf of Mexico coast and offshore waters of the United States as important nursery habitat for green turtles of Mexican origin and highlight the need for international coordination for management of these populations.

Alabama, Florida, Louisiana, Mississippi, Texas↗