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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 847 records · Page 47Linked to original sources

USGS2009

White-nose Syndrome management: Report on structured decision making initiative

This report describes an analysis undertaken to assist state and federal natural resources managers in addressing the following question: What management measures should be taken this year within a given area to control the spread and minimize the effects of white-nose syndrome (WNS) on hibernating bats at the individual and population levels? The answer depends upon specific characteristics of the bat species, the hibernacula, and the syndrome itself, all of which could vary across the geographic extent of WNS and change over time. It also depends on a large number of agency and societal judgments concerning how to balance disease management against other objectives.

Final Report↗

USGS2013

Spatial Relation Predicates in Topographic Feature Semantics

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Book chapter↗

USGS2019

Quantitative evaluation of vitrinite reflectance in shale using Raman spectroscopy and multivariate analysis

The current research builds upon a previously published study that demonstrated the combination of Raman spectroscopy coupled with multivariate analysis (MVA) for the prediction of thermal maturity in coal by evaluating the efficacy of this method for the prediction of thermal maturity in shale. MVA techniques eliminate analyst bias in peak-fitting methods by using the full Raman spectrum, and then extricating the important spectral regions for distinguishing samples and building accurate, robust models. Partial least squares (PLS) regression models were developed using Raman spectra and VRo values (0.58–4.59%) for 53 geographically diverse shale chip samples, and 43 shale powder samples. Separate PLS models were built using Raman spectra from shale chips or powders. The calibration sets were validated using approximately one-third of the samples to rigorously assess the predictive accuracy of the models. The root mean standard error of prediction was 0.24 for the shale chip model, and 0.28 for the shale powder model. The coefficients of determination ( R 2 ) for the cross-validated data sets were identical (0.90, chips; 0.90, powders), revealing a strong linearity despite the geographic and age diversity of the samples. This study demonstrates the validity of using PLS models for the prediction of shale VRo from Raman spectra. The MVA method described herein presents a Raman alternative to the VRo industry benchmark for assessing thermal maturity in shale that is not imperiled by the shortcomings and subjectivity of peak-fitting methods.

Fuel↗

USGS2021

A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma

Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude ( ⁠ M w "> M w Mw ⁠ ) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally M w < 4 "> M w < 4 Mw<4 ⁠ ) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this, magnitudes of small earthquakes and statistics derived from them can be biased. Furthermore, because small earthquakes are much more numerous than large ones, many applications, such as seismic hazard modeling, depend critically on analysis of events characterized by magnitudes other than M w "> M w Mw ⁠ . To assess this problem, we apply coda envelope analysis to reliably determine moment magnitudes for a case study of small earthquakes from northern Oklahoma and southern Kansas. Not surprisingly, we find significant differences among M L "> M L ML ⁠ , m b L g "> m b L g mbLg ⁠ , and M w "> M w Mw for M ∼2–4 earthquakes examined here. More troublingly, we find that relations designed to convert other magnitudes to M w "> M w Mw ⁠ , which are relied upon for important applications such as seismic hazard analysis, often increase rather than decrease this bias for our dataset. In our case study, we find that converted magnitudes can result in a systematic bias sometimes exceeding 0.5 magnitude units, a difference that typically corresponds to a factor of ∼3 in seismicity rate. Moreover, we find a correspondingly large bias in Gutenberg–Richter b ‐values, controlled primarily by inaccurate magnitude scaling in the conversion relationships. Although this study focuses on a relatively small geographic area, we can expect that similar issues exist with varying severity in other regions. Therefore, magnitudes of small earthquakes and their associated statistics, including seismicity rates and b ‐values, should be treated with caution.

Kansas, Oklahoma↗

USGS2001

South Florida Everglades: satellite image map

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

IMAP↗

USGS2002

Northern Everglades, Florida, satellite image map

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Florida↗

USGS2013

Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware

Hydrogeologic regions in the fractured rock area of Maryland were classified using geographic information system tools with principal components and cluster analyses. A study area consisting of the 8-digit Hydrologic Unit Code (HUC) watersheds with rivers that flow through the fractured rock area of Maryland and bounded by the Fall Line was further subdivided into 21,431 catchments from the National Hydrography Dataset Plus. The catchments were then used as a common hydrologic unit to compile relevant climatic, topographic, and geologic variables. A principal components analysis was performed on 10 input variables, and 4 principal components that accounted for 83 percent of the variability in the original data were identified. A subsequent cluster analysis grouped the catchments based on four principal component scores into six hydrogeologic regions. Two crystalline rock hydrogeologic regions, including large parts of the Washington, D.C. and Baltimore metropolitan regions that represent over 50 percent of the fractured rock area of Maryland, are distinguished by differences in recharge, Precipitation minus Potential Evapotranspiration, sand content in soils, and groundwater contributions to streams. This classification system will provide a georeferenced digital hydrogeologic framework for future investigations of groundwater availability in the fractured rock area of Maryland.

Delaware;District of Columbia;Maryl;Pennsylvania;V↗

USGS2011

Comparative mitochondrial genetics of North American and Eurasian mergansers with an emphasis on the endangered scaly-sided merganser (Mergus squamatus)

The scaly-sided merganser, Mergus squamatus , is considered one of the most threatened sea duck species in the Palearctic with limited breeding and wintering distribution in China and Russia. To provide information for future conservation efforts, we sequenced a portion of the mitochondrial (mt) DNA control region in four species of mergansers and three additional sea duck taxa to characterize the evolutionary history of the scaly-sided merganser, infer population trends that may have led to its limited geographic distribution, and to compare indices of genetic diversity among species of mergansers. Scaly-sided mergansers exhibit substantially lower levels of mtDNA genetic diversity ( h = 0.292, π = 0.0007) than other closely related sea ducks and many other avian taxa. The four haplotypes observed differed by a single base pair suggesting that the species has not experienced a recent population decline but has instead been at a low population level for some time. A phylogenetic analysis placed the scaly-sided merganser basal to North American and European forms of the common merganser, M. merganser . Our inclusion of a small number of male samples doubled the number of mtDNA haplotypes observed, suggesting that additional genetic variation likely exists within the global population if there is immigration of males from unsampled breeding areas.

Conservation Genetics↗

USGS2007

Sequence analysis of the msp4 gene of Anaplasma ovis strains

Anaplasma ovis (Rickettsiales: Anaplasmataceae) is a tick-borne pathogen of sheep, goats and wild ruminants. The genetic diversity of A. ovis strains has not been well characterized due to the lack of sequence information. In this study, we evaluated bighorn sheep ( Ovis canadensis ) and mule deer (Odocoileus hemionus ) from Montana for infection with A. ovis by serology and sequence analysis of the msp4 gene. Antibodies to Anaplasma spp. were detected in 37% and 39% of bighorn sheep and mule deer analyzed, respectively. Four new msp4 genotypes were identified. The A. ovis msp4 sequences identified herein were analyzed together with sequences reported previously for the characterization of the genetic diversity of A. ovis strains in comparison with other Anaplasma spp. The results of these studies demonstrated that although A. ovis msp4 genotypes may vary among geographic regions and between sheep and deer hosts, the variation observed was less than the variation observed between A. marginale and A. phagocytophilum strains. The results reported herein further confirm that A. ovis infection occurs in natural wild ruminant populations in Western United States and that bighorn sheep and mule deer may serve as wildlife reservoirs of A. ovis . ?? 2006.

Veterinary Microbiology↗

USGS2011

Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

Proceedings of SPIE↗

USGS2010

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

USGS2023

Genetic mark–recapture analysis reveals large annual variation in pre-breeding sex ratio of greater sage-grouse

Sex ratio, and the extent to which it varies over time, is an important factor in the demography, management, and conservation of wildlife populations. Greater sage-grouse Centrocercus urophasianus populations in western North America are monitored using counts of males at leks in spring. Population estimates derived from lek-count data typically assume a constant, female-biased sex ratio, yet few rigorous, empirically derived estimates of sex ratio are available to test that assumption. We estimated pre-breeding sex ratio of greater sage-grouse in a peripheral, geographically isolated population in northwestern Colorado during two consecutive winters using closed-population, robust-design, multi-state, genetic mark–recapture models in program MARK. Sex ratio varied markedly between years, with estimates of 3.29 (95% CI: 2.36–4.59) females per male in winter 2012–2013 and 1.54 (95% CI: 1.22–1.95) females per male in winter 2013–2014. Rather than assuming a constant sex ratio, biologists should consider the potential for large annual variation in sex ratio of greater sage-grouse populations when estimating population size or trend from male lek-count data.

Wildlife Biology↗

USGS2012

Genetic population substructure in bison at Yellowstone National Park

The Yellowstone National Park bison herd is 1 of only 2 populations known to have continually persisted on their current landscape since pre-Columbian times. Over the last century, the census size of this herd has fluctuated from around 100 individuals to over 3000 animals. Previous studies involving radiotelemetry, tooth wear, and parturition timing provide evidence of at least 2 distinct groups of bison within Yellowstone National Park. To better understand the biology of Yellowstone bison, we investigated the potential for limited gene flow across this population using multilocus Bayesian clustering analysis. Two genetically distinct and clearly defined subpopulations were identified based on both genotypic diversity and allelic distributions. Genetic cluster assignments were highly correlated with sampling locations for a subgroup of live capture individuals. Furthermore, a comparison of the cluster assignments to the 2 principle winter cull sites revealed critical differences in migration patterns across years. The 2 Yellowstone subpopulations display levels of differentiation that are only slightly less than that between populations which have been geographically and reproductively isolated for over 40 years. The identification of cryptic population subdivision and genetic differentiation of this magnitude highlights the importance of this biological phenomenon in the management of wildlife species.

Journal of Heredity↗

USGS2009

FishTraits: a database of ecological and life-history traits of freshwater fishes of the United States

The need for integrated and widely accessible sources of species traits data to facilitate studies of ecology, conservation, and management has motivated development of traits databases for various taxa. In spite of the increasing number of traits-based analyses of freshwater fishes in the United States, no consolidated database of traits of this group exists publicly, and much useful information on these species is documented only in obscure sources. The largely inaccessible and unconsolidated traits information makes large-scale analysis involving many fishes and/or traits particularly challenging. We have compiled a database of > 100 traits for 809 (731 native and 78 nonnative) fish species found in freshwaters of the conterminous United States, including 37 native families and 145 native genera. The database, named Fish Traits, contains information on four major categories of traits: (1) trophic ecology; (2) body size, reproductive ecology, and life history; (3) habitat preferences; and (4) salinity and temperature tolerances. Information on geographic distribution and conservation status was also compiled. The database enhances many opportunities for conducting research on fish species traits and constitutes the first step toward establishing a central repository for a continually expanding set of traits of North American fishes.

Fisheries↗

USGS2004

Deposition, erosion, and bathymetric change in South San Francisco Bay: 1858-1983

Since the California Gold Rush of 1849, sediment deposition, erosion, and the bathymetry of South San Francisco Bay have been altered by both natural processes and human activities. Historical hydrographic surveys can be used to assess how this system has evolved over the past 150 years. The National Ocean Service (NOS) (formerly the United States Coast and Geodetic Survey (USCGS), collected five hydrographic surveys of South San Francisco Bay from 1858 to 1983. Analysis of these surveys enables us to reconstruct the surface of the bay floor for each time period and quantify spatial and temporal changes in deposition, erosion, and bathymetry. The creation of accurate bathymetric models involves many steps. Sounding data was obtained from the original USCGS and NOS hydrographic sheets and were supplemented with hand drawn depth contours. Shorelines and marsh areas were obtained from topographic sheets. The digitized soundings and shorelines were entered into a Geographic Information System (GIS), and georeferenced to a common horizontal datum. Using surface modeling software, bathymetric grids with a horizontal resolution of 50 m were developed for each of the five hydrographic surveys. Prior to conducting analyses of sediment deposition and erosion, we converted all of the grids to a common vertical datum and made adjustments to correct for land subsidence that occurred from 1934 to 1967. Deposition and erosion that occurred during consecutive periods was then computed by differencing the corrected grids. From these maps of deposition and erosion, we calculated volumes and rates of net sediment change in the bay. South San Francisco Bay has lost approximately 90 x 106 m3 of sediment from 1858 to 1983; however within this timeframe there have been periods of both deposition and erosion. During the most recent period, from 1956 to 1983, sediment loss approached 3 x 106 m3/yr. One of the most striking changes that occurred from 1858 to 1983 was the conversion of more than 80% of the tidal marsh to salt ponds, agricultural, and urban areas. In addition, there has been a decline of approximately 40% in intertidal mud flat area. Restoration of these features will require a detailed understanding of the morphology and sediment sources of this complex system.

California↗

USGS1996

Film cameras or digital sensors? The challenge ahead for aerial imaging

Cartographic aerial cameras continue to play the key role in producing quality products for the aerial photography business, and specifically for the National Aerial Photography Program (NAPP). One NAPP photograph taken with cameras capable of 39 lp/mm system resolution can contain the equivalent of 432 million pixels at 11 ??m spot size, and the cost is less than $75 per photograph to scan and output the pixels on a magnetic storage medium. On the digital side, solid state charge coupled device linear and area arrays can yield quality resolution (7 to 12 ??m detector size) and a broader dynamic range. If linear arrays are to compete with film cameras, they will require precise attitude and positioning of the aircraft so that the lines of pixels can be unscrambled and put into a suitable homogeneous scene that is acceptable to an interpreter. Area arrays need to be much larger than currently available to image scenes competitive in size with film cameras. Analysis of the relative advantages and disadvantages of the two systems show that the analog approach is more economical at present. However, as arrays become larger, attitude sensors become more refined, global positioning system coordinate readouts become commonplace, and storage capacity becomes more affordable, the digital camera may emerge as the imaging system for the future. Several technical challenges must be overcome if digital sensors are to advance to where they can support mapping, charting, and geographic information system applications.

Photogrammetric Engineering and Remote Sensing↗

USGS2002

Assemblages of breeding birds as indicators of grassland condition

We developed a measure of biological integrity for grasslands (GI) based on the most influential habitat types in the Prairie Pothole Region of North Dakota. GI is based on proportions of habitat types and the relationships of these habitat types to breeding birds. Habitat types were identified by digital aerial photography, verified on the ground, and quantified using GIS, We then developed an index to GI based on the presence or abundance of breeding bird species. Species abundance data were obtained from 3 min roadside point counts at 889 points in 44, 4050 ha study plots over a 2-year period. Using a modified North American Breeding Bird Survey protocol, species were recorded in each of four quadrants at each point. Fifty species selected for analysis included all grassland species that occurred in at least 15 quadrants and all other bird species that occurred in at least 1 % of quadrants. We constructed preliminary models using data from each of the 2 years, then tested their predictive ability by cross-validation with data from the other year. These cross-validation tests indicated that the index consistently predicted grassland integrity. The final four models (presence and abundance models at 200 and 400 m scales) included only those species that were statistically significant (P ??? 0.05) in all preliminary models. Finally, we interpreted the components of the indices by examining associations between individual species and habitat types. Logistic regression identified 386 statistically significant relationships between species and habitat types at 200 and 400m scales. This method, though labor-intensive, successfully uses the presence of grassland-dependent species and absence of species associated with woody vegetation or cropland to provide an index to grassland integrity. Once regional associations of species with habitat types have been identified, such indices can be applied relatively inexpensively to monitor grassland integrity over large geographic areas. Indices like the ones presented here could be applied widely using bird abundance data that are currently being collected across the United States and southern Canada through the North American Breeding Bird Survey. ?? 2002 Elsevier Science Ltd. All rights reserved.

Ecological Indicators↗

USGS2002

Global modeling of land water and energy balances. Part III: Interannual variability

The Land Dynamics (LaD) model is tested by comparison with observations of interannual variations in discharge from 44 large river basins for which relatively accurate time series of monthly precipitation (a primary model input) have recently been computed. When results are pooled across all basins, the model explains 67% of the interannual variance of annual runoff ratio anomalies (i.e., anomalies of annual discharge volume, normalized by long-term mean precipitation volume). The new estimates of basin precipitation appear to offer an improvement over those from a state-of-the-art analysis of global precipitation (the Climate Prediction Center Merged Analysis of Precipitation, CMAP), judging from comparisons of parallel model runs and of analyses of precipitation-discharge correlations. When the new precipitation estimates are used, the performance of the LaD model is comparable to, but not significantly better than, that of a simple, semiempirical water-balance relation that uses only annual totals of surface net radiation and precipitation. This implies that the LaD simulations of interannual runoff variability do not benefit substantially from information on geographical variability of land parameters or seasonal structure of interannual variability of precipitation. The aforementioned analyses necessitated the development of a method for downscaling of long-term monthly precipitation data to the relatively short timescales necessary for running the model. The method merges the long-term data with a reference dataset of 1-yr duration, having high temporal resolution. The success of the method, for the model and data considered here, was demonstrated in a series of model-model comparisons and in the comparisons of modeled and observed interannual variations of basin discharge.

Journal of Hydrometeorology↗