SEARCH · Geology Reports

Results for “Geographical Analysis”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18Linked to original sources

USGS2003

A gentic survey of Salvinia minima in the southern United States

The genetic relationships among 68 samples of Salvinia minima (Salviniaceae) were investigated using RAPD analysis. Neighbor joining, principle components, and AMOVA analyses were used to detect differences among geographically referenced samples within and outside of Florida. Genetic distances (Nei and Li) range up to 0.48, although most are under 0.30, still relatively high levels for an introduced, clonally reproducing plant. Despite the diversity AMOVA analysis yielded no indication that the Florida plants, as a group, were significantly different from the plants sampled elsewhere in its adventive, North American range. A single, genetically dissimilar population probably exists in the recent (1998) horticultural introduction to Mississippi. When the samples were grouped into 10 regional (but artificial) units and analyzed using AMOVA the between region variance was only 7.7%. Genetic similarity among these regions may indicate introduction and dispersal from common sources. The reduced aggressiveness of Florida populations (compared to other states) may be due to herbivory. The weevil Cyrtobagous salviniae , a selective feeder, is found in Florida but not other states. The genetic similarity also suggests that there are no obvious genetic obstacles to the establishment or efficacy of C. salviniae as a biological control agent on S. minima outside of Florida.

Aquatic Botany↗

USGS2018

A spatial approach to combatting wildlife crime

Poaching can have devastating impacts on animal and plant numbers, and in many countries has reached crisis levels, with illegal hunters employing increasingly sophisticated techniques. Here, we show how geographic profiling – a mathematical technique originally developed in criminology and recently applied to animal foraging and epidemiology – can be adapted for use in investigations of wildlife crime, using data from an eight-year study in Savé Valley Conservancy, Zimbabwe that in total includes more than 10,000 incidents of illegal hunting and the deaths of 6,454 wild animals. Using a subset of these data for which the illegal hunters’ identities are known, we show that the model can successfully identify the illegal hunters’ home villages using the spatial locations of hunting incidences (for example, snares) as input, and show how this can be improved by manipulating the probability surface inside the Conservancy to reflect the fact that – although the illegal hunters mostly live outside the Conservancy, the majority of hunting occurs inside (in criminology, ‘commuter crime’). The results of this analysis – combined with rigorous simulations – show for the first time how geographic profiling can be combined with GIS data and applied to situations with more complex spatial patterns – for example, where landscape heterogeneity means that some parts of the study area are unsuitable (e.g. aquatic areas for terrestrial animals, or vice versa), or where landscape permeability differs (for example, forest bats tending not to fly over open areas). More broadly, these results show how geographic profiling can be used to target anti-poaching interventions more effectively and more efficiently, with important implications for the development of management strategies and conservation plans in a range of conservation scenarios.

Conservation Biology↗

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 the observations found one major area of importance not identified by the individual observation analysis. Five of the 49 groups are categorized as most highly important. The most important groups were those that, when omitted, produced mean increases greater than 10 percent at any UGTA site or Yucca Mountain. Four of the five groups were dominated by one individual observation. However, one group, located in Ash Meadows, had no individual observations ranked of high importance but collectively, when omitted, increased uncertainty substantially. Other groups also located in Ash Meadows, including intermediate depth observations, consistently ranked as more important than all other groups. (3) To demonstrate the importance of omitting a set of low-rated observations, one scenario is considered in which the 100 individually lowest-rated shallow and intermediate-depth observation locations are omitted. The measure of overall prediction uncertainty increased by just 0.59 percent, indicating that the wells associated with these observations probably could prudently be measured less frequently.

California, Nevada↗

USGS1990

U.S. Geological Survey DLG-3 and Bureau of the Census TIGER data. Development and GIS applications

The U.S. Geological Survey has been actively developing digital cartographic and geographic data and standards since the early 1970's. One product is Digital Line Graph data, which offer a consistently accurate source of base category geographic information. The Bureau of the Census has combined their Dual Independent Map Encoding data with the Geological Survey's 1:100,000-scale Digital Line Graph data to prepare for the 1990 decennial census. The resulting Topologically Integrated Geographic Encoding and Referencing data offer a wealth of information. A major area of research using these data is in transportation analysis. The attributes associated with Digital Line Graphs can be used to determine the average travel times along each segment. Geographic information system functions can then be used to optimize routes through the network and to generate street name lists. Additional aspects of the subject are discussed.

Conference Paper↗

USGS2008

Fish assemblages of the Casiquiare River, a corridor and zoogeographical filter for dispersal between the Orinoco and Amazon basins

Aim: The aim of this study was to determine whether the Casiquiare River functions as a free dispersal corridor or as a partial barrier (i.e. filter) for the interchange of fish species of the Orinoco and Negro/Amazon basins using species assemblage patterns according to geographical location and environmental features. Location: The Casiquiare, Upper Orinoco and Upper Negro rivers in southern Venezuela, South America. Methods: Our study was based on an analysis of species presence/absence data and environmental information (11 habitat characteristics) collected by the authors and colleagues between the years 1984 and 1999. The data set consisted of 269 sampled sites and 452 fish species (> 50,000 specimens). A wide range of habitat types was included in the samples, and the collection sites were located at various points along the entire length of the Casiquiare main channel, at multiple sites on its tributary streams, as well as at various nearby sites outside the Casiquiare drainage, within the Upper Orinoco and Upper Rio Negro river systems. Most specimens and field data used in this analysis are archived in the Museo de Ciencias Naturales in Guanare, Venezuela. We performed canonical correspondence analysis (CCA) based on species presence/absence using two versions of the data set: one that eliminated sites having < 5 species and species occurring at < 5 sites; and another that eliminated sites having < 10 species and species occurring at < 10 sites. Cluster analysis was performed on sites based on species assemblage similarity, and a separate analysis was performed on species based on CCA loadings. Results: The CCA results for the two versions of the data set were qualitatively the same. The dominant environmental axis contrasted assemblages and sites associated with blackwater vs. clearwater conditions. Longitudinal position on the Casiquiare River was correlated (r2 = 0.33) with CCA axis-1 scores, reflecting clearwater conditions nearer to its origin (bifurcation of the Orinoco) and blackwater conditions nearer to its mouth (junction with the Rio Negro). The second CCA axis was most strongly associated with habitat size and structural complexity. Species associations derived from the unweighted pair-group average clustering method and pair-wise squared Euclidean distances calculated from species loadings on CCA axes 1 and 2 showed seven ecological groupings. Cluster analysis of species assemblages according to watershed revealed a stronger influence of local environmental conditions than of geographical proximity. Main conclusions: Fish assemblage composition is more consistently associated with local environmental conditions than with geographical position within the river drainages. Nonetheless, the results support the hypothesis that the mainstem Casiquiare represents a hydrochemical gradient between clearwaters at its origin and blackwaters at its mouth, and as such appears to function as a semi-permeable barrier (environmental filter) to dispersal and faunal exchanges between the partially vicariant fish faunas of the Upper Orinoco and Upper Negro rivers. ?? 2008 The Authors.

Journal of Biogeography↗

USGS2014

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

Flooding is among the costliest natural disasters in terms of loss of life and property in Arizona, which is why the accurate estimation of flood frequency and magnitude is crucial for proper structural design and accurate floodplain mapping. Current guidelines for flood frequency analysis in the United States are described in Bulletin 17B (B17B), yet since B17B’s publication in 1982 (Interagency Advisory Committee on Water Data, 1982), several improvements have been proposed as updates for future guidelines. Two proposed updates are the Expected Moments Algorithm (EMA) to accommodate historical and censored data, and a generalized multiple Grubbs-Beck (MGB) low-outlier test. The current guidelines use a standard Grubbs-Beck (GB) method to identify low outliers, changing the determination of the moment estimators because B17B uses a conditional probability adjustment to handle low outliers while EMA censors the low outliers. B17B and EMA estimates are identical if no historical information or censored or low outliers are present in the peak-flow data. EMA with MGB (EMA-MGB) test was compared to the standard B17B (B17B-GB) method for flood frequency analysis at 328 streamgaging stations in Arizona. The methods were compared using the relative percent difference (RPD) between annual exceedance probabilities (AEPs), goodness-of-fit assessments, random resampling procedures, and Monte Carlo simulations. The AEPs were calculated and compared using both station skew and weighted skew. Streamgaging stations were classified by U.S. Geological Survey (USGS) National Water Information System (NWIS) qualification codes, used to denote historical and censored peak-flow data, to better understand the effect that nonstandard flood information has on the flood frequency analysis for each method. Streamgaging stations were also grouped according to geographic flood regions and analyzed separately to better understand regional differences caused by physiography and climate. The B17B-GB and EMA-MGB RPD-boxplot results showed that the median RPDs across all streamgaging stations for the 10-, 1-, and 0.2-percent AEPs, computed using station skew, were approximately zero. As the AEP flow estimates decreased (that is, from 10 to 0.2 percent AEP) the variability in the RPDs increased, indicating that the AEP flow estimate was greater for EMA-MGB when compared to B17B-GB. There was only one RPD greater than 100 percent for the 10- and 1-percent AEP estimates, whereas 19 RPDs exceeded 100 percent for the 0.2-percent AEP. At streamgaging stations with low-outlier data, historical peak-flow data, or both, RPDs ranged from −84 to 262 percent for the 0.2-percent AEP flow estimate. When streamgaging stations were separated by the presence of historical peak-flow data (that is, no low outliers or censored peaks) or by low outlier peak-flow data (no historical data), the results showed that RPD variability was greatest for the 0.2-AEP flow estimates, indicating that the treatment of historical and (or) low-outlier data was different between methods and that method differences were most influential when estimating the less probable AEP flows (1, 0.5, and 0.2 percent). When regional skew information was weighted with the station skew, B17B-GB estimates were generally higher than the EMA-MGB estimates for any given AEP. This was related to the different regional skews and mean square error used in the weighting procedure for each flood frequency analysis. The B17B-GB weighted skew analysis used a more positive regional skew determined in USGS Water Supply Paper 2433 (Thomas and others, 1997), while the EMA-MGB analysis used a more negative regional skew with a lower mean square error determined from a Bayesian generalized least squares analysis. Regional groupings of streamgaging stations reflected differences in physiographic and climatic characteristics. Potentially influential low flows (PILFs) were more prevalent in arid regions of the State, and generally AEP flows were larger with EMA-MGB than with B17B-GB for gaging stations with PILFs. In most cases EMA-MGB curves would fit the largest floods more accurately than B17B-GB. In areas of the State with more baseflow, such as along the Mogollon Rim and the White Mountains, streamgaging stations generally had fewer PILFs and more positive skews, causing estimated AEP flows to be larger with B17B-GB than with EMA-MGB. The effect of including regional skew was similar for all regions, and the observed pattern was increasingly greater B17B-GB flows (more negative RPDs) with each decreasing AEP quantile. A variation on a goodness-of-fit test statistic was used to describe each method’s ability to fit the largest floods. The mean absolute percent difference between the measured peak flows and the log-Pearson Type 3 (LP3)-estimated flows, for each method, was averaged over the 90th, 75th, and 50th percentiles of peak-flow data at each site. In most percentile subsets, EMA-MGB on average had smaller differences (1 to 3 percent) between the observed and fitted value, suggesting that the EMA-MGB-LP3 distribution is fitting the observed peak-flow data more precisely than B17B-GB. The smallest EMA-MGB percent differences occurred for the greatest 10 percent (90th percentile) of the peak-flow data. When stations were analyzed by USGS NWIS peak flow qualification code groups, the stations with historical peak flows and no low outliers had average percent differences as high as 11 percent greater for B17B-GB, indicating that EMA-MGB utilized the historical information to fit the largest observed floods more accurately. A resampling procedure was used in which 1,000 random subsamples were drawn, each comprising one-half of the observed data. An LP3 distribution was fit to each subsample using B17B-GB and EMA-MGB methods, and the predicted 1-percent AEP flows were compared to those generated from distributions fit to the entire dataset. With station skew, the two methods were similar in the median percent difference, but with weighted skew EMA-MGB estimates were generally better. At two gages where B17B-GB appeared to perform better, a large number of peak flows were deemed to be PILFs by the MGB test, although they did not appear to depart significantly from the trend of the data (step or dogleg appearance). At two gages where EMA-MGB performed better, the MGB identified several PILFs that were affecting the fitted distribution of the B17B-GB method. Monte Carlo simulations were run for the LP3 distribution using different skews and with different assumptions about the expected number of historical peaks. The primary benefit of running Monte Carlo simulations is that the underlying distribution statistics are known, meaning that the true 1-percent AEP is known. The results showed that EMA-MGB performed as well or better in situations where the LP3 distribution had a zero or positive skew and historical information. When the skew for the LP3 distribution was negative, EMA-MGB performed significantly better than B17B-GB and EMA-MGB estimates were less biased by more closely estimating the true 1-percent AEP for 1, 2, and 10 historical flood scenarios.

Arizona↗

USGS2018

River otter distribution in Nebraska

The river otter ( Lontra canadensis ) was extirpated from Nebraska, USA, in the early 1900s and reintroduced starting in 1986. Information is needed regarding the distribution of river otters in Nebraska before decisions can be made regarding its conservation status. Understanding distribution of a species is critically important for effective management. We investigated river otter distribution in Nebraska with occupancy modeling and maximum entropy (Maxent) modeling using 190 otter sign observations on Nebraska's navigable rivers and 380 historical otter records from November 1977 to April 2014. Both methods identified the Platte River, Elkhorn River, central and eastern Niobrara River, and southern Loup River system as core areas within the distribution of otters in Nebraska. The Maxent model provided more liberal estimates of site occupancy and identified some smaller rivers as being within the distribution of otters in Nebraska, which were not identified using occupancy modeling. We recommend that multiple data sets and analysis methods be used to estimate species distribution because this allows for the broadest geographical coverage and decreases the likelihood of overlooking areas with fewer animal records. If further reintroduction efforts or translocation efforts are to take place in the future, we recommend focusing on areas with high modeled occupancy but few historical and survey records

Nebraska↗

USGS1994

Historical shoreline mapping (II): Application of the Digital Shoreline Mapping and Analysis Systems (DSMS/DSAS) to shoreline change mapping in Puerto Rico

A new, state-of-the-art method for mapping historical shorelines from maps and aerial photographs, the Digital Shoreline Mapping System (DSMS), has been developed. The DSMS is a freely available, public domain software package that meets the cartographic and photogrammetric requirements of precise coastal mapping, and provides a means to quantify and analyze different sources of error in the mapping process. The DSMS is also capable of resolving imperfections in aerial photography that commonly are assumed to be nonexistent. The DSMS utilizes commonly available computer hardware and software, and permits the entire shoreline mapping process to be executed rapidly by a single person in a small lab. The DSMS generates output shoreline position data that are compatible with a variety of Geographic Information Systems (GIS). A second suite of programs, the Digital Shoreline Analysis System (DSAS) has been developed to calculate shoreline rates-of-change from a series of shoreline data residing in a GIS. Four rate-of-change statistics are calculated simultaneously (end-point rate, average of rates, linear regression and jackknife) at a user-specified interval along the shoreline using a measurement baseline approach. An example of DSMS and DSAS application using historical maps and air photos of Punta Uvero, Puerto Rico provides a basis for assessing the errors associated with the source materials as well as the accuracy of computed shoreline positions and erosion rates. The maps and photos used here represent a common situation in shoreline mapping: marginal-quality source materials. The maps and photos are near the usable upper limit of scale and accuracy, yet the shoreline positions are still accurate ±9.25 m when all sources of error are considered. This level of accuracy yields a resolution of ±0.51 m/yr for shoreline rates-of-change in this example, and is sufficient to identify the short-term trend (36 years) of shoreline change in the study area.

Puerto Rico↗

USGS2023

Prioritizing the risk and management of introduced species in a landscape with high indigenous biodiversity

Risk analysis protocols for prioritizing the management of non-native species are numerous, yet few incorporate risk and management in the same analysis or accommodate a broad diversity of taxa outside of a specific geographic area. We adapted a protocol that accounts for these factors to address non-native animal species in the Southern California/Northern Baja California Coast Ecoregion near the international border in San Diego County, an area with high indigenous biodiversity and high numbers of species of conservation concern. This stepwise, semi-quantitative protocol is applicable to any animal group in any predefined geographic area, relies on consensus-building among taxonomic experts, and has been vetted through previous use and in peer-reviewed literature. Our results show that the final prioritization was driven mainly by management feasibility, with top-ranked species having multitrophic effects that favor other non-native invaders over native residents. Conditions within the assessment area required some modification to the protocol as it was originally designed, namely a shift in emphasis from eradication to control, given that eradication is implausible for most non-native species in the assessment area. We call attention to taxon-specific issues that surfaced during the analysis, identify areas for improvement in this first-ever risk assessment for invasive animal species in the Natural Communities Conservation Plan/Habitat Conservation Plan (NCCP/HCP) reserve system of San Diego County, and provide suggestions for further refinement of the protocol. This study builds on the effort to standardize risk analysis for invasive species globally, given that many of the same invaders present threats to indigenous biodiversity worldwide.

California↗

USGS2013

Cost-effectiveness analysis of sandhill crane habitat management

Invasive species often threaten native wildlife populations and strain the budgets of agencies charged with wildlife management. We demonstrate the potential of cost-effectiveness analysis to improve the efficiency and value of efforts to enhance sandhill crane ( Grus canadensis ) roosting habitat. We focus on the central Platte River in Nebraska (USA), a region of international ecological importance for migrating avian species including sandhill cranes. Cost-effectiveness analysis is a valuation process designed to compare alternative actions based on the cost of achieving a pre-determined objective. We estimated costs for removal of invasive vegetation using geographic information system simulations and calculated benefits as the increase in area of sandhill crane roosting habitat. We generated cost effectiveness values for removing invasive vegetation on 7 land parcels and for the entire central Platte River to compare the cost-effectiveness of management at specific sites and for the central Platte River landscape. Median cost effectiveness values for the 7 land parcels evaluated suggest that costs for creating 1 additional hectare of sandhill crane roosting habitat totaled US $1,595. By contrast, we found that creating an additional hectare of sandhill crane roosting habitat could cost as much as US $12,010 for some areas in the central Platte River, indicating substantial cost savings can be achieved by using a cost effectiveness analysis to target specific land parcels for management. Cost-effectiveness analysis, used in conjunction with geographic information systems, can provide decision-makers with a new tool for identifying the most economically efficient allocation of resources to achieve habitat management goals.

Nebraska↗

USGS2013

Band reporting probablilities of mallards, American black ducks, and wood ducks in eastern North America

Estimates of band reporting probabilities are used for managing North American waterfowl to convert band recovery probabilities into harvest probabilities, which are used to set harvest regulations. Band reporting probability is the probability that someone who has shot and retrieved a banded bird will report the band. This probability can vary relative to a number of factors, particularly the inscription on the band and the ease with which it can be reported. Other factors, such as geographic reporting region, and species and sex of the bird may also play a role. We tested whether reporting probabilities of wood ducks ( Aix sponsa ) and American black ducks (black ducks; Anas rubripes ) differed from those of mallards ( Anas platyrhynchos ) and whether band reporting varied geographically or by the sex of the banded bird. In the analysis of spatially comparable wood duck and mallard data, a band reporting probability of 0.73 (95% CI = 0.67–0.78) was appropriate for use across species, sex, and reporting region within the United States. In the black duck–mallard comparison, the band reporting probability of black ducks in Eastern Canada (0.50, 95% CI = 0.44–0.57) was lower than in the Eastern United States (0.73, 95% CI = 0.62–0.83). These estimates reflected an increase in overall band reporting probability following the addition of a toll-free telephone number to band inscriptions. Lower reporting in Eastern Canada may be because of cultural, linguistic, or logistical barriers.

Journal of Wildlife Management↗

USGS2008

Seabed mapping and characterization of sediment variability using the usSEABED data base

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character.

Continental Shelf Research↗

USGS2006

High-resolution CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites

The Visual Infrared Mapping Spectrometer (VIMS) onboard the CASSINI spacecraft obtained new spectral data of the icy satellites of Saturn after its arrival at Saturn in June 2004. VIMS operates in a spectral range from 0.35 to 5.2 ??m, generating image cubes in which each pixel represents a spectrum consisting of 352 contiguous wavebands. As an imaging spectrometer VIMS combines the characteristics of both a spectrometer and an imaging instrument. This makes it possible to analyze the spectrum of each pixel separately and to map the spectral characteristics spatially, which is important to study the relationships between spectral information and geological and geomorphologic surface features. The spatial analysis of the spectral data requires the determination of the exact geographic position of each pixel on the specific surface and that all 352 spectral elements of each pixel show the same region of the target. We developed a method to reproject each pixel geometrically and to convert the spectral data into map projected image cubes. This method can also be applied to mosaic different VIMS observations. Based on these mosaics, maps of the spectral properties for each Saturnian satellite can be derived and attributed to geographic positions as well as to geological and geomorphologic surface features. These map-projected mosaics are the basis for all further investigations. ?? 2006 Elsevier Ltd. All rights reserved.

Planetary and Space Science↗

USGS2004

Is predation on waterfowl nests density dependent? Tests at three spatial scales

We tested whether predation on duck nests ( Anas spp.) was density dependent at three spatial scales using artificial and natural nests in the Suisun Marsh, California, USA. At the largest spatial scale, we used 5 years (1998–2002) of data to examine the natural variation in duck nest success and nest densities among 8–16 fields per year, each 5–33 ha in size (n=62 fields). At an intermediate spatial scale, we deployed artificial nests (2000, n=280) within 1-ha plots at three experimental densities (5, 10, and 20 nests ha −1 ) in a complete randomized block design and examined differences in nest predation. At the smallest spatial scale, we examined nest success in relation to nearest-neighbor fates and distances for artificial (2000, n=280) and natural nests (2000, n=507). We detected no relationship between nest success and the density of natural nests among fields in any year, nor when we pooled data for all years after controlling for year effects. The proportion of artificial nests that survived also did not depend on experimental nest densities within 1-ha plots. Overall, 15.0±12.4%, 15.0±11.0%, and 6.2±4.3% of artificial nests survived the 32-day exposure period in the low, intermediate, and high nest densities, respectively. Additionally, we detected no consistent effect of nearest-neighbor fate or distance on the success of artificial or natural nests. Thus, our results provide no evidence of density-dependent predation on duck nests at any scale of analysis, in contrast to a number of previous studies. Variation among geographical locations in the degree to which predation is density-dependent may reflect the composition of the predator community and the availability of alternate prey.

Oikos↗

USGS1987

Cumulative impacts of oil fields on northern Alaskan landscapes

Proposed further developments on Alaska's Arctic Coastal Plain raise questions about cumulative effects on arctic tundra ecosystems of development of multiple large oil fields. Maps of historical changes to the Prudhoe Bay Oil Field show indirect impacts can lag behind planned developments by many years and the total area eventually disturbed can greatly exceed the planned area of construction. For example, in the wettest parts of the oil field (flat thaw-lake plains), flooding and thermokarst covered more than twice the area directly affected by roads and other construction activities. Protecting critical wildlife habitat is the central issue for cumulative impact analysis in northern Alaska. Comprehensive landscape planning with the use of geographic information system technology and detailed geobotanical maps can help identify and protect areas of high wildlife use.

Alaska↗

USGS2009

Development of a local-scale urban stream assessment method using benthic macroinvertebrates: An example from the Santa Clara Basin, California

Research that explores the biological response to urbanization on a site-specific scale is necessary for management of urban basins. Recent studies have proposed a method to characterize the biological response of benthic macroinvertebrates along an urban gradient for several climatic regions in the USA. Our study demonstrates how this general framework can be refined and applied on a smaller scale to an urbanized basin, the Santa Clara Basin (surrounding San Jose, California, USA). Eighty-four sampling sites on 14 streams in the Santa Clara Basin were used for assessing local stream conditions. First, an urban index composed of human population density, road density, and urban land cover was used to determine the extent of urbanization upstream from each sampling site. Second, a multimetric biological index was developed to characterize the response of macroinvertebrate assemblages along the urban gradient. The resulting biological index included metrics from 3 ecological categories: taxonomic composition ( Ephemeroptera, Plecoptera, and Trichoptera), functional feeding group (shredder richness), and habit ( clingers). The 90 th -quantile regression line was used to define the best available biological conditions along the urban gradient, which we define as the predicted biological potential. This descriptor was then used to determine the relative condition of sites throughout the basin. Hierarchical partitioning of variance revealed that several site-specific variables (dissolved O 2 and temperature) were significantly related to a site's deviation from its predicted biological potential. Spatial analysis of each site's deviation from its biological potential indicated geographic heterogeneity in the distribution of impaired sites. The presence and operation of local dams optimize water use, but modify natural flow regimes, which in turn influence stream habitat, dissolved O 2 , and temperature. Current dissolved O 2 and temperature regimes deviate from natural conditions and appear to affect benthic macroinvertebrate assemblages. The assessment methods presented in our study provide finer-scale assessment tools for managers in urban basins. ?? North American Benthological Society.

Journal of the North American Benthological Societ↗

USGS2007

Subspecific variation in the widespread burl-forming Arctostaphylos glandulosa

The genus Arctostaphylos consists mostly of chaparral shrubs known by the common name manzanita, and one of the widest ranging of these is A. glandulosa Eastw., distributed from Baja California to Oregon. Particularly in the southern half of its range it exhibits complex patterns of morphological variation that have long presented taxonomic challenges. Phenetic analysis of morphological traits from over 1400 individuals from throughout the range were used to examine intra- and inter-population patterns of variation. Multivariate ordination and hierarchical cluster analysis were used to determine phenetic patterns linked with ecological and geographical distributions. These analyses suggest the hypothesis that this species comprises two lineages with a common origin but divergent in the presence or absence of glandularity: A. glandulosa Eastw. subsp. glandulosa , characterized by branchlets with long glandular hairs, scabrous or pubescent leaves, and nascent inflorescences with mostly foliaceous bracts; and A. glandulosa Eastw. subsp. cushingiana (Eastw.) Keeley, Vasey and Parker comb. nov., with non-glandular tomentose branchlets, glabrate or pubescent leaves and either foliaceous or short deltoid bracts. Populations dominated by one or the other of these morphotypes occur throughout the range and tend to be separated by elevation or distance from the coast, although mixed populations occur where these taxa come together. Two other glandular subspecies are named here. One is A. glandulosa Eastw. subsp. leucophylla Keeley, Vasey and Parker, subsp. nov., with intensely glaucous leaves and commonly with foliaceous bracts. A second glandular subspecies is A. glandulosa Eastw. subsp. atumescens Keeley, Vasey & Parker, subsp. nov., a narrowly distributed Baja California endemic similar to the nominate subspecies except that it lacks a basal burl and does not resprout after fire. Of the non-glandular tomentose taxa, in addition to A. glandulosa subsp cushingiana , several others are also recognized. One is A. glandulosa Eastw. subsp. crassifolia (Jepson) Wells, a well established coastal San Diego endemic recognized by darker and thicker leaves and smaller and flatter fruits. Another is a newly described taxon A. glandulosa Eastw. subsp. erecta Keeley, Vasey & Parker, subsp. nov., an endemic to northern Baja California recognized by the erect nascent inflorescenses. Two others have glabrate leaves and highly reduced deltoid often marcescent bracts; A. glandulosa subsp. adamsii (Munz) Wells, which has intensely glaucous leaves and is distributed from interior Riverside Co. south, and A. glandulosa Eastw. subsp. gabrielensis (Wells) Keeley, Vasey and Parker comb. nov., which has bright lustrous green leaves and greater fusion of nutlets, and is distributed from the interior San Gabriel Mountains of Los Angeles Co. north to the Sierra Madre Mountains of Santa Barbara Co. All non-glandular plants with long setose or villous hairs are A. glandulosa Eastw. subsp. mollis (Adams) Wells. This taxon includes plants with foliaceous as well as reduced bracts and is distributed throughout the Transverse Ranges from Santa Barbara to San Bernardino counties, with some outlying populations further south. This taxon shows a marked tendency for reduced stomatal densities on the upper leaf surface in the westernmost populations. Although all of the A. glandulosa taxa described here are known from allopatric populations, intergradations of these closely related taxa occur and thus some populations reflect a mixture of traits and can not be assigned a unique name of practical value.

Madroño↗

USGS1998

Geology of the conterminous United States at 1:2,500,000 scale a digital representation of the 1974 P.B. King and H.M. Beikman map

This CD-ROM contains a digital version of the Geologic Map of the United States, originally published at a scale of 1:2,500,000 (King and Beikman, 1974b). It excludes Alaska and Hawaii. In addition to the graphical formats, the map key is included in ASCII text. A geographic information system (GIS) allows combining and overlaying of layers for analysis of spatial relations not readily apparent in the standard paper publication. This disc contains only geology. However, digital data on geology, geophysics, and geochemistry can be combined to create useful derivative products-- for example, see Phillips and others (1993). This CD-ROM contains a copy of the text and figures from Professional Paper 901 by King and Beikman (1974a). This text describes the historical background of the map, details of the compilation process, and limitations to interpretation. The digital version of the text can be searched for keywords or phrases.

Data Series↗