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At least 379 records · Page 21Linked to original sources

USGS2007

Flood regionalization: A hybrid geographic and predictor-variable region-of-influence regression method

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. ?? 2007 ASCE.

Journal of Hydrologic Engineering↗

USGS2003

Phylogeography of infectious haematopoietic necrosis virus in North America

Infectious hematopoietic necrosis virus (IHNV) is a rhabdoviral pathogen that infects wild and cultured salmonid fish throughout the Pacific Northwest of North America. IHNV causes severe epidemics in young fish and can cause disease or occur asymptomatically in adults. In a broad survey of 323 IHNV field isolates, sequence analysis of a 303 nucleotide variable region within the glycoprotein gene revealed a maximum nucleotide diversity of 8·6 %, indicating low genetic diversity overall for this virus. Phylogenetic analysis revealed three major virus genogroups, designated U, M and L, which varied in topography and geographical range. Intragenogroup genetic diversity measures indicated that the M genogroup had three- to fourfold more diversity than the other genogroups and suggested relatively rapid evolution of the M genogroup and stasis within the U genogroup. We speculate that factors influencing IHNV evolution may have included ocean migration ranges of their salmonid host populations and anthropogenic effects associated with fish culture.

Journal of General Virology↗

USGS2011

Assessment of mangrove forests in the Pacific region using Landsat imagery

The information on the mangrove forests for the Pacific region is scarce or outdated. A regional assessment based on a consistent methodology and data sources was needed to understand their true extent. Our investigation offers a regionally consistent, high resolution (30 m), and the most comprehensive mapping of mangrove forests on the islands of American Samoa, Fiji, French Polynesia, Guam, Hawaii, Kiribati, Marshall Islands, Micronesia, Nauru, New Caledonia, Northern Mariana Islands, Palau, Papua New Guinea, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, and Wallis and Futuna Islands for the year 2000. We employed a hybrid supervised and unsupervised image classification technique on a total of 128 Landsat scenes gathered between 1999 and 2004, and validated the results using existing geographic information science (GIS) datasets, high resolution imagery, and published literature. We also draw a comparative analysis with the mangrove forests inventory published by the Food and Agriculture Association (FAO) of the United Nations. Our estimate shows a total of 623755 hectares of mangrove forests in the Pacific region; an increase of 18% from FAO's estimates. Although mangrove forests are disproportionately distributed toward a few larger islands on the western Pacific, they are also significant in many smaller islands.

Journal of Applied Remote Sensing↗

USGS2007

Detection of viral hemorrhagic septicemia virus

Viral hemorrhagic septicemia virus (VHSV) is considered to be one of the most important viral pathogens of finfish and is listed as reportable by many nations and international organizations (Office International des Epizooties 2006). Prior to 1988, VHSV was thought to be limited to Europe (Wolf 1988; Smail 1999). Subsequently, it was shown that the virus is endemic among many marine and anadromous fish species in both the Pacific and Atlantic Oceans (Meyers and Winton 1995; Skall et al. 2005). Genetic analysis reveals that isolates of VHSV can be divided into four genotypes that generally correlate with geographic location with the North American isolates generally falling into VHSV Genotype IV (Snow et al. 2004). In 2005-2006, reports from the Great Lakes region indicated that wild fish had experienced disease or, in some cases, very large die-offs from VHSV (Elsayed et al. 2006, Lumsden et al. 2007). The new strain from the Great Lakes, now identified as VHSV Genotype IVb, appears most closely related to isolates of VHSV from mortalities that occurred during 2000-2004 in rivers and near-shore areas of New Brunswick and Nova Scotia, Canada (Gagne et al. 2007). The type IVb isolate found in the Great Lakes region is the only strain outside of Europe that has been associated with significant mortality in freshwater species.

Fact Sheet↗

USGS2005

Correlation analysis of a ground-water level monitoring network, Miami-Dade County, Florida

The U.S. Geological Survey cooperative ground-water monitoring program in Miami-Dade County, Florida, expanded from 4 to 98 continuously recording water-level monitoring wells during the 1939-2001 period. Network design was based on area specific assessments; however, no countywide statistical assessments of network coverage had been performed for the purpose of assessing network redundancy. To aid in the assessment of network redundancy, correlation analyses were performed using S-PLUS 2000 statistical analysis software for daily maximum water-level data from 98 monitoring wells for the November 1, 1973, to October 31, 2000 period. Because of the complexities of the hydrologic, water-supply, and water-management systems in Miami-Dade County and the changes that have occurred to these systems through time, spatial and temporal variations in the degree of correlation had to be considered. To assess temporal variation in correlation, water-level data from each well were subdivided by year and by wet and dry seasons. For each well, year, and season, correlation analyses were performed on the data from those wells that had available data. For selected wells, the resulting correlation coefficients from each year and season were plotted with respect to time. To assess spatial variation in correlation, the coefficients determined from the correlation analysis were averaged. These average wet- and dry-season correlation coefficients were plotted spatially using geographic information system software. Wells with water-level data that correlated with a coefficient of 0.95 or greater were almost always located in relatively close proximity to each other. Five areas were identified where the water-level data from wells within the area remained correlated with that of other wells in the area during the wet and dry seasons. These areas are located in or near the C-1 and C-102 basins (2 wells), in or near the C-6 and C-7 basins (2 wells), near the Florida Keys Aqueduct Authority Well Field (2 wells), near the Hialeah-Miami Springs Well Field (6 wells), and near the West Well Field (21 wells). Data from the remaining 65 wells (most of the wells in the network) generally were not correlated with those of other wells during both the wet and dry seasons with an average coefficient of 0.95 or greater for the comparison. Because many of the wells near the West Well Field and some near the Hialeah-Miami Springs Well Field had not been in operation for very long (most having been installed in 1994), the averaged correlation coefficients for these wells were often determined using only a few seasons of data. For the few instances where water-level data were found to be well correlated on average for a lengthy period of record, short-term declines in correlation were often identified. In general, it would be beneficial to compare data for longer periods of record than currently available.

Open-File Report↗

USGS2011

Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution

The Equidistant Cylindrical Map projection is popular with digital modelers and others for storing and processing worldwide data sets because of the simple association of latitude and longitude to cell values or pixels in the resulting grid. This projection does not accurately display area, and the diminished geographic area represented by cells at high latitudes is not often carefully considered. A simple mathematical analysis quantifies the discrepancy in area sampled by cells at different latitudes. The presence of this discrepancy indicates that the use of this projection can induce bias in data sets when both sampling and reporting data. It is demonstrated that as the resolution requirements of input data for models increase, the necessity of providing data to accurately describe smaller cells, particularly at high latitude, will be a challenge.

Techniques and Methods↗

USGS1987

New techniques for the quantification and modeling of remotely sensed alteration and linear features in mineral resource assessment studies

Linear structural features and hydrothermally altered rocks that were interpreted from Landsat data have been used by the U.S. Geological Survey (USGS) in regional mineral resource appraisals for more than a decade. In the past, linear features and alterations have been incorporated into models for assessing mineral resources potential by manually overlaying these and other data sets. Recently, USGS research into computer-based geographic information systems (GIS) for mineral resources assessment programs has produced several new techniques for data analysis, quantification, and integration to meet assessment objectives.

Pecora XI Symposium↗

USGS1974

Environmental impact analysis; the example of the proposed Trans-Alaska Pipeline

The environmental impact analysis made as required by the National Environmental Policy Act of 1969 for the proposed trans-Alaska pipeline included consideration of the (1) technologically complex and geographically extensive proposed project, (2) extremely different physical environments across Alaska along the proposed route and elsewhere in Alaska and in Canada along alternative routes, (3) socioeconomic environment of the State of Alaska, and (4) a wide variety of alternatives. The analysis was designed specifically to fit the project and environment that would be affected. The environment was divided into two general parts--natural physical systems and superposed socioeconomic systems--and those parts were further divided into discipline-oriented systems or components that were studied and analyzed by scientists of the appropriate discipline. Particular attention was given to potential feedback loops in the impact network and to linkages between the project's impacting effects and the environment. The results of the analysis as reported in the final environmental impact statement were that both unavoidable and threatened environmental impacts would result from construction, operation, and maintenance of the proposed pipeline system and the developments related to it. The principal unavoidable effects would be (1) disturbances of terrain, fish and wildlife habitat, and human environs, (2) the results of the discharge of effluent from the tanker-ballast-treatment facility into Port Valdez and of some indeterminate amount of oil released into the ocean from tank-cleaning operations at sea, and (3) the results associated with increased human pressures of all kinds on the environment. Other unavoidable effects would be those related to increase of State and Native Corporation revenues, accelerated cultural change of the Native population, and extraction of the oil and gas resource. The main threatened environmental effects would all be related to unintentional oil loss from the pipeline, from tankers, or in the oil field. Oil losses from the pipeline could be caused by direct or indirect effects of earthquakes, destructive sea waves, slope failure caused by natural or artificial processes, thaw-plug instability (in permafrost), differential settlement of permafrost terrain, and bed scour and bank erosion at stream crossings. Oil loss from tankers could be caused by accidents during transfer operations at Valdez and at destination ports and by casualties involving tankers and other ships. Comparison of alternative routes and transportation systems and of their environmental impacts provided information which indicates to the author that one corridor containing both oil and gas pipelines would have less environmental impact than would separate corridors. Considering also the threat to the marine environment that any tanker system would impose and the threat that zones of high earthquake frequency and magnitude would impose on pipelines, it is apparent to the author that environmental impact and cost would be least for a single-corridor on-land route that avoided earthquake zones. The alternative trans-Alaska-Canada routes would meet these criteria. The decisions of the U.S. Department of the Interior, the U.S. Congress, and the President of the United States in favor of the proposed trans-Alaska pipeline system indicate the relative weight given by the decision makers in balancing the importance of potential environmental consequences against the advantages to be derived from rapid resource development.

Circular↗

USGS1987

Trends in spawning populations of Pacific anadromous salmonids

Annual escapement records for 1968-1984 for five species of Pacific salmon-chinook ( Oncorhynchus tshawytscha ), coho ( O. kisutch ), sockeye (O. nerka ), pink ( O. gorbuscha ), and chum (O. keta )—and steelhead ( Salmo gairdneri ) were obtained from published and unpublished sources and organized in a computer database. More than 25,500 escapement records were obtained for more than 1,100 locations throughout Alaska, Washington, Idaho, Oregon, and California. Escapement trends for naturally reproducing populations for which data were available for at least 7 years from 1968 to 1984 and at least 4 years from 1975 to 1984 were analyzed by linear regression. Significant trends were observed in about 30% of the 886 populations examined. Trends were summarized by species for three geographic regions in Alaska and four in the Pacific Northwest (including California). For chinook, sockeye, and pink salmon, trends were predominantly increasing in the Alaska regions and either lacking or predominantly decreasing in most of the Pacific Northwest regions; for coho and chum salmon, trends were predominantly decreasing in one or more Alaska regions as well as in most of the Pacific Northwest regions. For steelhead, too few populations were examined to enable us to characterize trends throughout their range. Among the 657 salmonid populations excluded from the trend analysis because the data sets were incomplete, 13 (of which 2 were in Alaska) declined to zero during the period of analysis. For coho, sockeye, pink, and chum salmon and steelhead, major data gaps were revealed by a comparison of the geographic distribution of escapement records with the spawning distribution of the species. For chinook salmon, escapement records were more geographically representative of the spawning distribution.

Fish and Wildlife Technical Report↗

USGS2006

Chapter 7. The GIS project for the geologic assessment of undiscovered oil and gas in the Cotton Valley group and Travis Peak and Hosston formations, East Texas basin and Louisiana-Mississippi salt basins provinces

A geographic information system (GIS) focusing on the Upper Jurassic-Lower Cretaceous Cotton Valley Group and the Lower Cretaceous Travis Peak and Hosston Formations in the northern Gulf Coast region was developed as a visual-analysis tool for the U.S. Geological Survey's 2002 assessment of undiscovered, technically recoverable oil and natural gas resources in the East Texas Basin and Louisiana-Mississippi Salt Basins Provinces. The Central Energy Resources Team of the U.S. Geological Survey has also developed an Internet Map Service to deliver the GIS data to the public. This mapping tool utilizes information from a database about the oil and natural gas endowment of the United States-including physical locations of geologic and geographic data-and converts the data into visual layers. Portrayal and analysis of geologic features on an interactive map provide an excellent tool for understanding domestic oil and gas resources for strategic planning, formulating economic and energy policies, evaluating lands under the purview of the Federal Government, and developing sound environmental policies. Assessment results can be viewed and analyzed or downloaded from the internet web site, http://energy.cr.usgs.gov/oilgas/noga/ .

Alabama, Arkansas. Florida, Georgia, Louisiana, Mi↗

USGS2018

A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data

This paper introduces our research in developing a probabilistic model to extract linear terrain features from high resolution DEM (Digital Elevation Model) data. The proposed model takes full advantage of spatio-contextual information to characterize terrain changes. It first derives a quantifiable measure of spatio-contextual patterns of linear terrain feature, such as ridgelines, valley lines and crater boundaries, and then adopts multiple neighborhood analysis and a probability model to address data uncertainty in terrain surface modeling. Different from traditional approaches, the proposed model has the ability to achieve near-automated processing, and to support effective extraction of terrain features in both smooth and rough surfaces. Through a series of experiments, we demonstrate that the proposed approach outperforms existing techniques, including: thresholding, stream/drainage network analysis, visual descriptor, object-based image analysis and edge detection. We hope this work contributes to both the geospatial data science and geomorphology communities with a new way of utilizing high-resolution imagery in terrain analysis.

International Journal of Geographical Information ↗

USGS1999

Regional analysis of population trajectories from the North American Breeding Bird Survey

The North American Breeding Bird Survey (BBS) was started in 1966, and provides information on population change and distribution for most of the birds in North America. The geographic extent of the survey, and the logistical compromises needed to survey such a large area, present many challenges for estimation from BBS data. In this paper, we describe the survey and discuss some of the limitations of the survey design and implementation. Analysis of the survey has evolved over time as new statistical methods and insights into the analysis of count data are developed. Survey results and analysis tools for the BBS are now available over intemet; we present new methods that use generalized linear models for estimation of population change and empirical Bayes procedures for regional summaries.

Book chapter↗

USGS1999

Exploring factors controlling the variability of pesticide concentrations in the Willamette River Basin using tree-based models

We analyzed available concentration data of five commonly used herbicides and three pesticides collected from small streams in the Willamette River Basin in Oregon to identify factors that affect the variation of their concentrations in the area. The emphasis of this paper is the innovative use of classification and regression tree models for exploratory data analysis as well as analyzing data with a substantial amount of left-censored values. Among variables included in this analysis, land-use pattern in the watershed is the most important for all but one (simazine) of the eight pesticides studied, followed by geographic location, intensity of agriculture activities in the watershed (represented by nutrient concentrations in the stream), and the size of the watershed. The significant difference between urban sites and agriculture sites is the variability of stream concentrations. While all 16 nonurban watersheds have significantly higher variation than urban sites, the same is not necessarily true for the mean concentrations. Seasonal variation accounts for only a small fraction of the total variance in all eight pesticides.We analyzed available concentration data of five commonly used herbicides and three pesticides collected from small streams in the Willamette River Basin in Oregon to identify factors that affect the variation of their concentrations in the area. The emphasis of this paper is the innovative use of classification and regression tree models for exploratory data analysis as well as analyzing data with a substantial amount of left-censored values. Among variables included in this analysis, land-use pattern in the watershed is the most important for all but one (simazine) of the eight pesticides studied, followed by geographic location, intensity of agriculture activities in the watershed (represented by nutrient concentrations in the stream), and the size of the watershed. The significant difference between urban sites and agriculture sites is the variability of stream concentrations. While all 16 nonurban watersheds have significantly higher variation than urban sites, the same is not necessarily true for the mean concentrations. Seasonal variation accounts for only a small fraction of the total variance in all eight pesticides.

Environmental Science & Technology↗

USGS1997

New approaches to the analysis of population trends in land birds: Comment

James et al. (1996, Ecology 77:13-27) used data from the North American Breeding Bird Survey (BBS) to examine geographic variability in patterns of population change for 26 species of wood warblers. They emphasized the importance of evaluating nonlinear patterns of change in bird populations, proposed LOESS-based non-parametric and semi-parametric analyses of BBS data, and contrasted their results with other analyses, including those of Robbins et al. (1989, Proceedings of the National Academy of Sciences 86: 7658-7662) and Peterjohn et al. (1995, Pages 3-39 in T. E. Martin and D. M. Finch, eds. Ecology and management of Neotropical migratory birds: a synthesis and review of critical issues. Oxford University Press, New York.). In this note, we briefly comment on some of the issues that arose from their analysis of BBS data, suggest a few aspects of the survey that should inspire caution in analysts, and review the differences between the LOESS-based procedures and other procedures (e.g., Link and Sauer 1994). We strongly discourage the use of James et al.'s completely non-parametric procedure, which fails to account for observer effects. Our comparisons of estimators adds to the evidence already present in the literature of the bias associated with omitting observer information in analyses of BBS data. Bias resulting from change in observer abilities should be a consideration in any analysis of BBS data.

Ecology↗

USGS2020

Flood-frequency estimation for very low annual exceedance probabilities using historical, paleoflood, and regional information with consideration of nonstationarity

Streamflow estimates for floods with an annual exceedance probability of 0.001 or lower are needed to accurately portray risks to critical infrastructure, such as nuclear powerplants and large dams. However, extrapolating flood-frequency curves developed from at-site systematic streamflow records to very low annual exceedance probabilities (less than 0.001) results in large uncertainties in the streamflow estimates. Traditionally, methods for statistically estimating flood frequency have relied on the systematic streamflow record, which provides a time series of annual maximum flood peaks, often including some historical peaks. However, most peak-flow records are less than 100 years, and uncertainties are large when trying to extrapolate magnitudes of very low annual exceedance probability events. Other data may be available that extend the record beyond the systematic dataset. Historical data are defined as data from outside the period of systematic records but within the period of human records. Examples of historical information include flood estimates from other agencies and newspaper accounts that can be translated to flood magnitude point estimates, interval estimates, or perception thresholds (such as a statement that an 1880 flood was the largest since 1869). Paleoflood data, which may also extend the dataset, include a broad range of information about flood occurrence or magnitude from sources like sediment deposits or tree rings. Several assumptions are made in flood-frequency analysis, and an understanding of whether the data conform to these assumptions is desired. A particularly difficult assumption to evaluate for flood-frequency analysis is the underlying assumption that the flood series is stationary—the assumption that a time series of peak flow varies around a constant mean within a particular range of values (constant variance). As the hydrologic community’s understanding of natural systems and anthropogenic effects on streamflows has evolved, the community has come to understand that many surface-water systems exhibit one or more forms of nonstationarity, and thus the stationarity assumption is often violated to some degree. However, there is currently (2020) no consensus among hydrologists regarding the most appropriate flood-frequency-analysis methods for nonstationary systems, and this topic remains an active area of research. A literature review was completed to summarize the state of the science of flood frequency. The literature review highlights tools available to detect nonstationarities and identifies approaches that include external information to inform flood-frequency analysis. To demonstrate methods for initial data analysis and for incorporating historical and paleoflood information in flood-frequency analysis, five sites were selected: the Red River of the North at James Avenue Pumping Station, Winnipeg, Manitoba, Canada; lower reach, Rapid Creek, South Dakota; Spring Creek, South Dakota; Cherry Creek near Melvin, Colorado; and Escalante River near Escalante, Utah. The sites were chosen for the availability of published historical and paleoflood data and for their geographic diversity and unique characteristics, which highlighted issues such as autocorrelation, change points, trends, outlier peaks, or short periods of record. An initial data analysis that involved examining records for autocorrelation, change points, and trends was completed for all sites. The flood-frequency analysis completed for this study used version 7.2 of the U.S. Geological Survey PeakFQ program. Multiple analyses were done on each site documenting the change in the flood-frequency curve when additional historical or paleoflood data were added. When other flood-frequency studies were available, their results were compared to the results here. The comparisons in some cases simply show the effect of additional years of data, whereas other comparisons show results from probability distributions or fitting methods other than those used in PeakFQ. For the Red River of the North, flood-frequency analysis shows that paleoflood data appear necessary to reasonably estimate very low annual exceedance probabilities. For the analysis of the lower reach of Rapid Creek and Spring Creek, paleoflood information helped put a high outlier from the systematic period in context; however, very low annual exceedance probabilities at these sites still had extraordinarily large confidence bounds. These sites also showed that paleoflood information might be transferred from one site to another, with the caveat that this is a case where we had existing paleoflood data to test the transfer of paleoflood information—this is not the case at many sites, and transferring paleoflood information requires assumptions about the comparability of floods at the sites. The Cherry Creek analysis affirmed the result of an earlier study that showed that the generalized Pareto distribution was not a good distribution for estimating very low annual exceedance probabilities. The Escalante River analysis showed that adding paleoflood information might increase uncertainty for very low annual exceedance probabilities, compared to analysis with the systematic period of record information only, when the paleoflood peaks are of much larger magnitudes than the systematic record.

Scientific Investigations Report↗

USGS2007

Remote sensing and GIS technology in the Global Land Ice Measurements from Space (GLIMS) Project

Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyze them for glacier extent and changes, and to assess these change data in terms of forcings. The consortium is organized into a system of Regional Centers, each of which is responsible for glaciers in their region of expertise. Specialized needs for mapping glaciers in a distributed analysis environment require considerable work developing software tools: terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; change detection and analysis; visualization of images and derived data; interpretation and archival of derived data; and analysis to ensure consistency of results from different Regional Centers. A global glacier database has been designed and implemented at the National Snow and Ice Data Center (Boulder, CO); parameters have been expanded from those of the World Glacier Inventory (WGI), and the database has been structured to be compatible with (and to incorporate) WGI data. The project as a whole was originated, and has been coordinated by, the US Geological Survey (Flagstaff, AZ), which has also led the development of an interactive tool for automated analysis and manual editing of glacier images and derived data (GLIMSView). This article addresses remote sensing and Geographic Information Science techniques developed within the framework of GLIMS in order to fulfill the goals of this distributed project. Sample applications illustrating the developed techniques are also shown. ?? 2006 Elsevier Ltd. All rights reserved.

Computers & Geosciences↗

USGS2021

Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity

Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminous United States, to illustrate hotspots of biodiversity for the major taxonomic groups. This collection represents the first complete compilation of terrestrial vertebrate species models for the conterminous United States (U.S. Geological Survey (USGS), 2018a). We used the species models but not the available subspecies models; this resulted in the inclusion of 282 amphibian models, 621 bird models, 365 mammal models, and 322 reptiles in our analysis. We also used population trend information and made spatial queries to characterize species in three dimensions: geographic range (small or large), habitat breadth (narrow or wide), and population trend (decreasing vs stable or increasing). This characterization allowed us to divide the species into eight groups (A-H) with similar characteristics. Group A species (large geographic range, wide habitat breadth, and stable or increasing population trend) are species that are common now with no indication of becoming rare. Species B-H have theoretical or known characteristics that could lead them to become rare with the H species exhibiting small geographic range, narrow habitat breadth, and decreasing population trend. Finally, we evaluated the prevalence of mapped habitat on protected lands for each species, exploring the patterns of representation in the rare species groups by ecoregion. The species we identified with population and habitat use characteristics that potentially predispose them to being or becoming rare represented a large percentage of each taxon. Potentially rare species were widely distributed among ecoregions. Of the 20 ecoregions in the country, 14 have a greater number of rare species than the national average for at least one taxon. Protection of the habitat for the majority of these rare species is below that recommended (17% of available habitat) by the Convention on Biological Diversity (CBD). The Everglades ecoregion was the only ecoregion that protected more than half of its rare or potentially rare species.

Global Ecology and Conservation↗

USGS1999

Analysis of the nucleoprotein gene identifies three distinct lineages of viral haemorrhagic septicemia virus within the European marine environment

A ribonuclease (RNase) protection assay (RPA) has been used to detect nucleotide sequence variation within the nucleoprotein gene of 39 viral haemorrhagic septicaemia virus (VHSV) isolates of European marine origin. The classification of VHSV isolates based on RPA cleavage patterns permitted the identification of ten distinct groups of viruses based on differences at the molecular level. The nucleotide sequence of representatives of each of these groupings was determined and subjected to phylogenetic analysis. This revealed grouping of the European marine isolates of VHSV into three genotypes circulating within distinct geographic areas. A fourth genotype was identified comprising isolates originating from North America. Phylogenetic analyses indicated that VHSV isolates recovered from wild caught fish around the British Isles were genetically related to isolates responsible for losses in farmed turbot. Furthermore, a relationship between naturally occurring marine isolates and VHSV isolates causing mortality among rainbow trout in continental Europe was demonstrated.

British Isles↗