Recent advances in molecular genetics have proven to be extremely useful in efforts to conserve imperiled species. Genetics data are used to identify appropriate units of management (e.g., populations, metapopulations), effective sizes of breeding populations, population mixing rates, and other variables. These data help managers make decisions about which populations to preserve, whether to move individuals from one site to another, how to breed species most effectively in captivity, and even, in some cases, what taxonomic classification is most appropriate. Many U.S. Geological Survey (USGS) Science Centers and Cooperative Fish and Wildlife Research Units have developed capabilities in genetics research. The two case studies that follow illustrate how USGS geneticists are assisting managers in recovering species on the brink.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Pendleton, E., Vandergast, A.G., and King, T., 2008, Conservation genetics and species recovery: Endangered Species Bulletin, v. 33, no. 3.","productDescription":"3 p.","startPage":"59","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":332873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332872,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.fws.gov/endangered/news/pdf/bulletin_fall2008.pdf","linkFileType":{"id":1,"text":"pdf"}}],"volume":"33","issue":"3","edition":"57","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586e182ee4b0f5ce109fcb15","contributors":{"authors":[{"text":"Pendleton, Ed","contributorId":177961,"corporation":false,"usgs":false,"family":"Pendleton","given":"Ed","email":"","affiliations":[],"preferred":false,"id":657668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, T.L.","contributorId":93416,"corporation":false,"usgs":true,"family":"King","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":657670,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159338,"text":"70159338 - 2008 - Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin","interactions":[],"lastModifiedDate":"2015-10-22T11:22:18","indexId":"70159338","displayToPublicDate":"2008-08-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2289,"text":"Journal of Flood Risk Management","active":true,"publicationSubtype":{"id":10}},"title":"Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin","docAbstract":"In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.
","language":"English","publisher":"Wiley","doi":"10.1111/j.1753-318X.2008.00011.x","usgsCitation":"Shrestha, M., Artan, G.A., Bajracharya, S., and Sharma, R.R., 2008, Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin: Journal of Flood Risk Management, v. 1, no. 2, p. 89-99, https://doi.org/10.1111/j.1753-318X.2008.00011.x.","productDescription":"11 p.","startPage":"89","endPage":"99","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":310420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"2","noUsgsAuthors":false,"publicationDate":"2008-08-18","publicationStatus":"PW","scienceBaseUri":"562a08fae4b011227bf1fe06","contributors":{"authors":[{"text":"Shrestha, M.S.","contributorId":45547,"corporation":false,"usgs":true,"family":"Shrestha","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":578070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Artan, Guleid A. 0000-0001-8409-6182 gartan@usgs.gov","orcid":"https://orcid.org/0000-0001-8409-6182","contributorId":2938,"corporation":false,"usgs":true,"family":"Artan","given":"Guleid","email":"gartan@usgs.gov","middleInitial":"A.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":578071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bajracharya, S.R.","contributorId":25387,"corporation":false,"usgs":true,"family":"Bajracharya","given":"S.R.","email":"","affiliations":[],"preferred":false,"id":578072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharma, R. R.","contributorId":44363,"corporation":false,"usgs":true,"family":"Sharma","given":"R.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":578073,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":86072,"text":"ofr20081200 - 2008 - Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects","interactions":[],"lastModifiedDate":"2012-02-02T00:14:26","indexId":"ofr20081200","displayToPublicDate":"2008-07-31T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1200","title":"Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects","docAbstract":"Models based upon coastal engineering equations have been developed to quantify wind fetch length and several physical wave characteristics including significant height, length, peak period, maximum orbital velocity, and shear stress. These models, developed using Environmental Systems Research Institute's ArcGIS 9.2 Geographic Information System platform, were used to quantify differences in proposed island construction designs for three Habitat Rehabilitation and Enhancement Projects (HREPs) in the U.S. Army Corps of Engineers St. Paul District (Capoli Slough and Harpers Slough) and St. Louis District (Swan Lake). Weighted wind fetch was calculated using land cover data supplied by the Long Term Resource Monitoring Program (LTRMP) for each island design scenario for all three HREPs. Figures and graphs were created to depict the results of this analysis. The difference in weighted wind fetch from existing conditions to each potential future island design was calculated for Capoli and Harpers Slough HREPs. A simplistic method for calculating sediment suspension probability was also applied to the HREPs in the St. Paul District. This analysis involved determining the percentage of days that maximum orbital wave velocity calculated over the growing seasons of 2002-2007 exceeded a threshold value taken from the literature where fine unconsolidated sediments may become suspended. This analysis also evaluated the difference in sediment suspension probability from existing conditions to the potential island designs. Bathymetric data used in the analysis were collected from the LTRMP and wind direction and magnitude data were collected from the National Oceanic and Atmospheric Administration, National Climatic Data Center.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081200","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Rohweder, J.J., Rogala, J.T., Johnson, B.L., Anderson, D., Clark, S., Chamberlin, F., and Runyon, K., 2008, Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects: U.S. Geological Survey Open-File Report 2008-1200, vi, 43 p., https://doi.org/10.3133/ofr20081200.","productDescription":"vi, 43 p.","startPage":"0","endPage":"0","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":195378,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11627,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1200/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac6e4b07f02db67ab78","contributors":{"authors":[{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":296729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":296731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Barry L. bljohnson@usgs.gov","contributorId":608,"corporation":false,"usgs":true,"family":"Johnson","given":"Barry","email":"bljohnson@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":296730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Dennis","contributorId":96793,"corporation":false,"usgs":true,"family":"Anderson","given":"Dennis","email":"","affiliations":[],"preferred":false,"id":296734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Steve","contributorId":92769,"corporation":false,"usgs":true,"family":"Clark","given":"Steve","email":"","affiliations":[],"preferred":false,"id":296733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chamberlin, Ferris","contributorId":32635,"corporation":false,"usgs":true,"family":"Chamberlin","given":"Ferris","email":"","affiliations":[],"preferred":false,"id":296732,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runyon, Kip","contributorId":106595,"corporation":false,"usgs":true,"family":"Runyon","given":"Kip","email":"","affiliations":[],"preferred":false,"id":296735,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":86070,"text":"sir20085077 - 2008 - Determination of Baseline Periods of Record for Selected Streamflow-Gaging Stations in New Jersey for Determining Ecologically Relevant Hydrologic Indices (ERHI)","interactions":[],"lastModifiedDate":"2012-03-08T17:16:22","indexId":"sir20085077","displayToPublicDate":"2008-07-31T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-5077","title":"Determination of Baseline Periods of Record for Selected Streamflow-Gaging Stations in New Jersey for Determining Ecologically Relevant Hydrologic Indices (ERHI)","docAbstract":"Hydrologic changes in New Jersey stream basins resulting from human activity can affect the flow and ecology of the streams. To assess future changes in streamflow resulting from human activity an understanding of the natural variability of streamflow is needed. The natural variability can be classified using Ecologically Relevant Hydrologic Indices (ERHIs). ERHIs are defined as selected streamflow statistics that characterize elements of the flow regime that substantially affect biological health and ecological sustainability. ERHIs are used to quantitatively characterize aspects of the streamflow regime, including magnitude, duration, frequency, timing, and rate of change. Changes in ERHI values can occur as a result of human activity, and changes in ERHIs over time at various stream locations can provide information about the degree of alteration in aquatic ecosystems at or near those locations. New Jersey streams can be divided into four classes (A, B, C, or D), where streams with similar ERHI values (determined from cluster analysis) are assigned the same stream class.\r\n\r\nIn order to detect and quantify changes in ERHIs at selected streamflow-gaging stations, a 'baseline' period is needed. Ideally, a baseline period is a period of continuous daily streamflow record at a gaging station where human activity along the contributing stream reach or in the stream's basin is minimal. Because substantial urbanization and other development had already occurred before continuous streamflow-gaging stations were installed, it is not possible to identify baseline periods that meet this criterion for many reaches in New Jersey. Therefore, the baseline period for a considerably altered basin can be defined as a period prior to a substantial human-induced change in the drainage basin or stream reach (such as regulations or diversions), or a period during which development did not change substantially.\r\n\r\nIndex stations (stations with minimal urbanization) were defined as streamflow-gaging stations in basins that contain less than 15 percent urban land use throughout the period of continuous streamflow record. A minimum baseline period of record for each stream class was determined by comparing the variability of selected ERHIs among consecutive 5-, 10-, 15-, and 20-year time increments for index stations. On the basis of this analysis, stream classes A and D were assigned a minimum of 20 years of continuous record as a baseline period and stream classes B and C, a minimum of 10 years.\r\n\r\nBaseline periods were calculated for 85 streamflow-gaging stations in New Jersey with 10 or more years of continuous daily streamflow data, and the values of 171 ERHIs also were calculated for these baseline periods for each station. Baseline periods were determined by using historical streamflow-gaging station data, estimated changes in impervious surface in the drainage basin, and statistically significant changes in annual base flow and runoff.\r\n\r\nHistorical records were reviewed to identify years during which regulation, diversions, or withdrawals occurred in the drainage basins. Such years were not included in baseline periods of record. For some sites, the baseline period of record was shorter than the minimum period of record specified for the given stream class. In such cases, the baseline period was rated as 'poor'.\r\n\r\nImpervious surface was used as an indicator of urbanization and change in streamflow characteristics owing to increases in storm runoff and decreases in base flow. Percentages of impervious surface were estimated for 85 streamflow-gaging stations from available municipal population-density data by using a regression model. Where the period of record was sufficiently long, all years after the impervious surface exceeded 10 to 20 percent were excluded from the baseline period. The percentage of impervious surface also was used as a criterion in assigning qualitative ratings to baseline periods.\r\n\r\nChanges in trends of annual base fl","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20085077","collaboration":"Prepared in cooperation with the N.J. Department of Environmental Protection","usgsCitation":"Esralew, R.A., and Baker, R.J., 2008, Determination of Baseline Periods of Record for Selected Streamflow-Gaging Stations in New Jersey for Determining Ecologically Relevant Hydrologic Indices (ERHI): U.S. Geological Survey Scientific Investigations Report 2008-5077, viii, 72 p., https://doi.org/10.3133/sir20085077.","productDescription":"viii, 72 p.","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":190892,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11625,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5077/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76,38.75 ], [ -76,41.5 ], [ -73.5,41.5 ], [ -73.5,38.75 ], [ -76,38.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db667988","contributors":{"authors":[{"text":"Esralew, Rachel A.","contributorId":104862,"corporation":false,"usgs":true,"family":"Esralew","given":"Rachel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":296725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Ronald J. rbaker@usgs.gov","contributorId":1436,"corporation":false,"usgs":true,"family":"Baker","given":"Ronald","email":"rbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":296724,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":86066,"text":"ofr20081202 - 2008 - Assessment of Coal Geology, Resources, and Reserves in the Gillette Coalfield, Powder River Basin, Wyoming","interactions":[],"lastModifiedDate":"2012-02-02T00:14:24","indexId":"ofr20081202","displayToPublicDate":"2008-07-31T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1202","title":"Assessment of Coal Geology, Resources, and Reserves in the Gillette Coalfield, Powder River Basin, Wyoming","docAbstract":"The Gillette coalfield, within the Powder River Basin in east-central Wyoming, is the most prolific coalfield in the United States. In 2006, production from the coalfield totaled over 431 million short tons of coal, which represented over 37 percent of the Nation's total yearly production. The Anderson and Canyon coal beds in the Gillette coalfield contain some of the largest deposits of low-sulfur subbituminous coal in the world. By utilizing the abundance of new data from recent coalbed methane development in the Powder River Basin, this study represents the most comprehensive evaluation of coal resources and reserves in the Gillette coalfield to date. Eleven coal beds were evaluated to determine the in-place coal resources. Six of the eleven coal beds were evaluated for reserve potential given current technology, economic factors, and restrictions to mining. These restrictions included the presence of railroads, a Federal interstate highway, cities, a gas plant, and alluvial valley floors. Other restrictions, such as thickness of overburden, thickness of coal beds, and areas of burned coal were also considered.\r\n\r\nThe total original coal resource in the Gillette coalfield for all eleven coal beds assessed, and no restrictions applied, was calculated to be 201 billion short tons. Available coal resources, which are part of the original coal resource that is accessible for potential mine development after subtracting all restrictions, are about 164 billion short tons (81 percent of the original coal resource). \r\n\r\nRecoverable coal, which is the portion of available coal remaining after subtracting mining and processing losses, was determined for a stripping ratio of 10:1 or less. After mining and processing losses were subtracted, a total of 77 billion short tons of coal were calculated (48 percent of the original coal resource).\r\n\r\nCoal reserves are the portion of the recoverable coal that can be mined, processed, and marketed at a profit at the time of the economic evaluation. With a discounted cash flow at 8 percent rate of return, the coal reserves estimate for the Gillette coalfield is10.1 billion short tons of coal (6 percent of the original resource total) for the 6 coal beds evaluated.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081202","usgsCitation":"Luppens, J.A., Scott, D.C., Haacke, J., Osmonson, L.M., Rohrbacher, T.J., and Ellis, M.S., 2008, Assessment of Coal Geology, Resources, and Reserves in the Gillette Coalfield, Powder River Basin, Wyoming: U.S. Geological Survey Open-File Report 2008-1202, viii, 38 p., https://doi.org/10.3133/ofr20081202.","productDescription":"viii, 38 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195702,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11620,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1202/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abbe4b07f02db672af0","contributors":{"authors":[{"text":"Luppens, James A. 0000-0001-7607-8750 jluppens@usgs.gov","orcid":"https://orcid.org/0000-0001-7607-8750","contributorId":550,"corporation":false,"usgs":true,"family":"Luppens","given":"James","email":"jluppens@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":296711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, David C. 0000-0002-7925-7452 dscott@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-7452","contributorId":629,"corporation":false,"usgs":true,"family":"Scott","given":"David","email":"dscott@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":296712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haacke, Jon E.","contributorId":86054,"corporation":false,"usgs":true,"family":"Haacke","given":"Jon E.","affiliations":[],"preferred":false,"id":296715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Osmonson, Lee M.","contributorId":33322,"corporation":false,"usgs":false,"family":"Osmonson","given":"Lee","email":"","middleInitial":"M.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":false,"id":296714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohrbacher, Timothy J.","contributorId":20355,"corporation":false,"usgs":true,"family":"Rohrbacher","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":296713,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellis, Margaret S. mellis@usgs.gov","contributorId":198,"corporation":false,"usgs":true,"family":"Ellis","given":"Margaret","email":"mellis@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":296710,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":86065,"text":"fs20083055 - 2008 - Earth Resources Observation and Science (EROS) Center - Who We Are and What We Do","interactions":[],"lastModifiedDate":"2012-02-02T00:14:29","indexId":"fs20083055","displayToPublicDate":"2008-07-30T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-3055","title":"Earth Resources Observation and Science (EROS) Center - Who We Are and What We Do","docAbstract":"To understand our planet at local, regional, national, and global scales, people need information about Earth's land surfaces and how they are changing. Land remote sensing is the key to gathering this information. Satellites that capture detailed images of Earth's continents, islands, and coastlines are and have been EROS' primary source of remotely sensed data since the Center opened in 1973. EROS is probably best known as the USGS receiving station for Landsat satellite images. However, we acquire data and images from many other satellites, as well as from other kinds of remote sensing instruments.\r\n\r\nRoughly 1.5 terabytes* of information arrive at EROS every day to become part of the largest civilian archive of remotely sensed land data in the world. The archive represents a perfectly preserved 70-year record of Earth's land surfaces and serves as an invaluable resource for documenting how they have changed over time.\r\n\r\n*One terabyte = 1,000 gigabytes","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20083055","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2008, Earth Resources Observation and Science (EROS) Center - Who We Are and What We Do: U.S. Geological Survey Fact Sheet 2008-3055, 2 p., https://doi.org/10.3133/fs20083055.","productDescription":"2 p.","onlineOnly":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":121209,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2008_3055.jpg"},{"id":11618,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2008/3055/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a54e4b07f02db62c19e","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":534976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":86064,"text":"ofr20081124 - 2008 - Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado","interactions":[{"subject":{"id":86064,"text":"ofr20081124 - 2008 - Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado","indexId":"ofr20081124","publicationYear":"2008","noYear":false,"title":"Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado"},"predicate":"SUPERSEDED_BY","object":{"id":70156862,"text":"sim3342 - 2015 - Geologic map of the Alamosa 30’ × 60’ quadrangle, south-central Colorado","indexId":"sim3342","publicationYear":"2015","noYear":false,"title":"Geologic map of the Alamosa 30’ × 60’ quadrangle, south-central Colorado"},"id":1}],"supersededBy":{"id":70156862,"text":"sim3342 - 2015 - Geologic map of the Alamosa 30’ × 60’ quadrangle, south-central Colorado","indexId":"sim3342","publicationYear":"2015","noYear":false,"title":"Geologic map of the Alamosa 30’ × 60’ quadrangle, south-central Colorado"},"lastModifiedDate":"2015-10-15T08:56:18","indexId":"ofr20081124","displayToPublicDate":"2008-07-30T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1124","title":"Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado","docAbstract":"This geologic map presents new polygon (geologic map unit contacts) and line (terrace and lacustrine spit/barrier bar) vector data for a map comprised of four 7.5' quadrangles in the north-central part of the Alamosa, Colorado, 30' x 60' quadrangle. The quadrangles include Baldy, Blanca, Blanca SE, and Lasauses. The map database, compiled at 1:50,000 scale from new 1:24,000-scale mapping, provides geologic coverage of an area of current hydrogeologic, tectonic, and stratigraphic interest. The mapped area is located primarily in Costilla County, but contains portions of Alamosa and Conejos Counties, and includes the town of Blanca in its northeastern part. The map area is mainly underlain by surficial geologic materials (fluvial and lacustrine deposits, and eolian sand), but Tertiary volcanic and volcaniclastic rocks crop out in the San Luis Hills, which are in the central and southern parts of the mapped area. The surficial geology of this area has never been mapped at any scale greater than 1:250,000 (broad reconnaissance), so this new map provides important data for ground-water assessments, engineering geology, and the Quaternary geologic history of the San Luis Basin. Newly discovered shoreline deposits are of particular interest (sands and gravels) that are associated with the high-water stand of Lake Alamosa, a Pliocene to middle Pleistocene lake that occupied the San Luis basin prior to its overflow and cutting of a river gorge through the San Luis Hills. After the lake drained, the Rio Grande system included Colorado drainages for the first time since the Miocene (>5.3 Ma). In addition, Servilleta Basalt, which forms the Basaltic Hills on the east margin of the map area, is dated at 3.79+or-0.17 Ma, consistent with its general age range of 3.67-4.84 Ma. This map provides new geologic information for better understanding ground-water flow paths in and adjacent to the Rio Grande system. The map abuts U.S. Geological Survey Open File Report 2005-1392 (a map of the northwestern part of the Alamosa 30' x 60' quadrangle map) to the west and U.S. Geological Survey Scientific Investigations Map 2965 (Fort Garland 7.5' quadrangle) to the east.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20081124","usgsCitation":"Machette, M., Thompson, R.A., and Brandt, T.R., 2008, Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado (Version 1.0): U.S. Geological Survey Open-File Report 2008-1124, Map Sheet: 33 x 30 inches; Downloads Directory, https://doi.org/10.3133/ofr20081124.","productDescription":"Map Sheet: 33 x 30 inches; Downloads Directory","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":11617,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1124/","linkFileType":{"id":5,"text":"html"}},{"id":195029,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"scale":"50000","projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.75,37.25 ], [ -105.75,37.5 ], [ -105.5,37.5 ], [ -105.5,37.25 ], [ -105.75,37.25 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e6db","contributors":{"authors":[{"text":"Machette, Michael N.","contributorId":28963,"corporation":false,"usgs":true,"family":"Machette","given":"Michael N.","affiliations":[],"preferred":false,"id":296708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":296706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Theodore R. 0000-0002-7862-9082 tbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-7862-9082","contributorId":1267,"corporation":false,"usgs":true,"family":"Brandt","given":"Theodore","email":"tbrandt@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":296707,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":86062,"text":"sir20075196 - 2008 - Multiple Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California","interactions":[],"lastModifiedDate":"2012-02-10T00:11:42","indexId":"sir20075196","displayToPublicDate":"2008-07-30T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2007-5196","title":"Multiple Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California","docAbstract":"With the exception of Los Angeles, perhaps no urban area in the United States is more at risk from landsliding, triggered by either precipitation or earthquake, than the San Francisco Bay region of northern California. By January each year, seasonal winter storms usually bring moisture levels of San Francisco Bay region hillsides to the point of saturation, after which additional heavy rainfall may induce landslides of various types and levels of severity. In addition, movement at any time along one of several active faults in the area may generate an earthquake large enough to trigger landslides. The danger to life and property rises each year as local populations continue to expand and more hillsides are graded for development of residential housing and its supporting infrastructure. \r\n\r\nThe chapters in the text consist of: \r\n\r\n*Introduction by Russell W. Graymer \r\n\r\n*Chapter 1 Rainfall Thresholds for Landslide Activity, San Francisco Bay Region, Northern California by Raymond C. Wilson \r\n\r\n*Chapter 2 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike and Steven Sobieszczyk \r\n\r\n*Chapter 3 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven Sobieszczyk \r\n\r\n*Chapter 4 Landslide Hazard Modeled for the Cities of Oakland, Piedmont, and Berkeley, Northern California, from a M=7.1 Scenario Earthquake on the Hayward Fault Zone by Scott B. Miles and David K. Keefer \r\n\r\n*Chapter 5 Synthesis of Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike \r\n\r\nThe plates consist of: \r\n*Plate 1 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike, Russell W. Graymer, Sebastian Roberts, Naomi B. Kalman, and Steven Sobieszczyk \r\n\r\n*Plate 2 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven Sobieszczyk \r\n\r\n*Plate 3 Susceptibility to Shallow Landsliding Modeled for the Cities of Oakland and Piedmont Northern California by Kevin M. Schmidt and Steven Sobieszczyk \r\n\r\n*Plate 4 Seismic Landslide Hazard Modeled for the Cities of Oakland, Piedmont, and Berkeley, Northern California by Scott B. Miles and David K. Keefer III \r\n\r\nThe relative hazard for each of several landslide scenarios is presented as a geospatial database. This publication includes ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 8.1.2 grids and associated tables and four text files of FGDC-compliant metadata for each grid.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20075196","usgsCitation":"Pike, R.J., and Graymer, R.W., 2008, Multiple Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2007-5196, Report: iii, 51 p.; 4 Plates: Plates 1 & 2 - 30 x 38 inches, Plates 3 & 4 - 37 x 44 inches; ReadMe; Metadata; Data Files, https://doi.org/10.3133/sir20075196.","productDescription":"Report: iii, 51 p.; 4 Plates: Plates 1 & 2 - 30 x 38 inches, Plates 3 & 4 - 37 x 44 inches; ReadMe; Metadata; Data Files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":647,"text":"Western Earth Surface Processes","active":false,"usgs":true}],"links":[{"id":190887,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11615,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5196/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.36749999999999,37.6175 ], [ -122.36749999999999,38 ], [ -122,38 ], [ -122,37.6175 ], [ -122.36749999999999,37.6175 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b48b0","contributors":{"authors":[{"text":"Pike, Richard J. rpike@usgs.gov","contributorId":5753,"corporation":false,"usgs":true,"family":"Pike","given":"Richard","email":"rpike@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":296703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graymer, Russell W. 0000-0003-4910-5682 rgraymer@usgs.gov","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":1052,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","email":"rgraymer@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":296702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70123994,"text":"70123994 - 2008 - Shear wave velocity investigation of soil liquefaction sites from the Tangshan, China M7.8 earthquake of 1976 using active and passive surface wave methods","interactions":[],"lastModifiedDate":"2017-12-08T12:27:27","indexId":"70123994","displayToPublicDate":"2008-07-24T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Shear wave velocity investigation of soil liquefaction sites from the Tangshan, China M7.8 earthquake of 1976 using active and passive surface wave methods","docAbstract":"An initial investigation of soil liquefaction sites from the July, 28 1976 Tangshan M7.8 earthquake was conducted between 1976 and 1978 by the National Ministry of Railways, China. These data are the basis of the ‘Chinese Method’ for assessment of liquefaction potential of silty-sand deposits, and are an important component of the worldwide data set for modern probabilistic methods for assessment of soil liquefaction using Bayesian updating and system reliability tools.
We revisited 26 sites identified in the maps and published 198 report of the Ministry of Railways in order to investigate these locations with a suite of active- and passive-array surface wave methods. These sites are clustered along the north coast of the Bo Hai Sea in three areas: Lutai, Tianjin; Tangshan City and outlying village, Hebei; and Luannan county, Hebei. First, we gathered and evaluated the Rayleigh wave dispersion characteristics of the ground by comparing dispersion curves from the active source harmonic wave-spectral analysis of surface waves (SASW) method and the passive array Spatial Auto-Correlation method (SPAC). The dispersive properties of the liquefied ground as measured by these two methods were found to be almost identical. These tests were hybridized and the data sets merged in order to invert of shear wave velocities for analysis of liquefaction potential using a probabilistic framework. The data from high-values of seismic intensity near Tangshan city to low-intensities distant of the event in Luannan County segregate out into clusters of liquefied and non liquefied points clearly separated by liquefaction boundary curves developed from a large global data set of 310 sites
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"International Conference on Case Histories in Geotechnical Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Sixth International Conference on Case Histories in Geotechnical Engineering ","language":"English","publisher":"Missouri University of Science and Technology ","usgsCitation":"Kayen, R.E., Tao, X., Shi, L., and Shi, H., 2008, Shear wave velocity investigation of soil liquefaction sites from the Tangshan, China M7.8 earthquake of 1976 using active and passive surface wave methods, in International Conference on Case Histories in Geotechnical Engineering, p. 1-7.","productDescription":"7 p. ","startPage":"1","endPage":"7","ipdsId":"IP-009433","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":342464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342463,"rank":1,"type":{"id":15,"text":"Index 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Robert E rkayen@usgs.gov","contributorId":121447,"corporation":false,"usgs":true,"family":"Kayen","given":"Robert","email":"rkayen@usgs.gov","middleInitial":"E","affiliations":[],"preferred":false,"id":519390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tao, Xiaxin","contributorId":192872,"corporation":false,"usgs":false,"family":"Tao","given":"Xiaxin","email":"","affiliations":[],"preferred":false,"id":697985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Lijing","contributorId":192873,"corporation":false,"usgs":false,"family":"Shi","given":"Lijing","email":"","affiliations":[],"preferred":false,"id":697986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shi, Hailiang","contributorId":192874,"corporation":false,"usgs":false,"family":"Shi","given":"Hailiang","email":"","affiliations":[],"preferred":false,"id":697987,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":85853,"text":"ofr20081127 - 2008 - Influence of the Houma Navigation Canal on Salinity Patterns and Landscape Configuration in Coastal Louisiana","interactions":[],"lastModifiedDate":"2012-02-02T00:14:26","indexId":"ofr20081127","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1127","title":"Influence of the Houma Navigation Canal on Salinity Patterns and Landscape Configuration in Coastal Louisiana","docAbstract":"Coastal Louisiana is a dynamic and ever changing landscape. From 1956 to 2004, over 297,000 ha of Louisiana's coastal wetlands were lost because of the effects of natural and human-induced activities. Studies show that, in 2005, Hurricanes Katrina and Rita transformed over 56,200 ha of wetlands to open water in various parts of coastal Louisiana. Besides the catastrophic hurricanes, factors such as subsidence, sea-level rise, freshwater and sediment deprivation, saltwater intrusion, the dredging of oil and gas canals, navigation canals, shoreline erosion, and herbivory are all contributors to wetland loss in Louisiana. Various scientific literatures have well described the direct impacts associated with an immediate physical conversion of habitat in coastal Louisiana; however, the indirect impacts that are subtle and operate over longer time horizons (such as salinity intrusion) have been difficult to discern. In this report, long-term influences on salinity patterns and landscape configuration are evaluated for pre- and postconstruction periods of the Houma Navigation Canal (HNC), which is located in the coastal region of southeastern Louisiana.\r\n\r\nAnalysis of daily and hourly salinity data from long-term data collection stations within the areas surrounding the HNC indicated that there were no obvious patterns in increasing salinity levels following the completion of the canal, except for the immediate increase in salinity spikes that occurred toward the completion of its construction in 1961. Increases in salinity spikes were also observed during a severe drought in 1999-2000. Data from Bayou Grand Caillou at Dulac, however, show a longer term trend of increasing salinity levels, which is similar to the pattern observed at the Houma Water Treatment Plant. A potential explanation for these patterns is based on the dredging history of the HNC, where dates of maintenance dredging correspond fairly closely to the salinity peaks in Bayou Grand Caillou and the canal. It appears that the dredging events opened up a deeper route from the canal to Crozier and into Grand Bayou Caillou, but it also may be a result of the general breakup of the marsh in the adjacent area, which resulted in greater exchange of bay water and subsequently higher salinity levels. Although the available salinity data were insufficient to conduct statistical correlations, there was close agreement between salinity changes and specific dredging events of the HNC.\r\n\r\nA procedure for analyzing marsh landscapes, which utilizes the FRAGSTATS landscape statistical application and a two-part marsh classification system, was developed as a means of determining the connectivity and configuration of marsh and water patches within the study area. Individual landscape metrics were used to determine the percentage and rate of land change and the shifts in density, shape, and cohesiveness of water within the marsh. Wetland loss rates for coastal Louisiana and Terrebonne basin were compared to the long- and short-term loss rates of the Houma Navigation Canal study area that were quantified by using the FRAGSTATS landscape analysis method. These results suggest that the canal study area was losing land at a significantly faster rate than both the marshes of coastal Louisiana (over all periods) and the other highly degraded neighboring marshes within Terrebonne basin. Overall, 37 percent (17,625 ha) of the project area marsh was lost between 1958 and 1998.\r\nAs a means of quantifying the distance and degree of influence that the HNC had on marsh degradation, a 3-km interval buffer array and comparable years of vegetation data were used to describe the changes in primary metric values across the three project dates (1958, 1968/69, and 1998). The patterns across landscape metrics varied, and it was difficult to discern direct relationships based on proximity to the canal. Even though the canal may have an influence on marsh degradation, these analyses show that the degree and d","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081127","collaboration":"Prepared in cooperation with Minerals Management Service, Gulf of Mexico Outer Continental Shelf Region","usgsCitation":"Steyer, G.D., Sasser, C., Evers, E., Swenson, E., Suir, G., and Sapkota, S., 2008, Influence of the Houma Navigation Canal on Salinity Patterns and Landscape Configuration in Coastal Louisiana (Version 1.0): U.S. Geological Survey Open-File Report 2008-1127, viii, 190 p., https://doi.org/10.3133/ofr20081127.","productDescription":"viii, 190 p.","onlineOnly":"Y","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":195812,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11595,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1127/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab0e4b07f02db66db4e","contributors":{"authors":[{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":296568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sasser, Charles","contributorId":93999,"corporation":false,"usgs":true,"family":"Sasser","given":"Charles","affiliations":[],"preferred":false,"id":296573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evers, Elaine","contributorId":80775,"corporation":false,"usgs":true,"family":"Evers","given":"Elaine","email":"","affiliations":[],"preferred":false,"id":296572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swenson, Erick","contributorId":67617,"corporation":false,"usgs":true,"family":"Swenson","given":"Erick","affiliations":[],"preferred":false,"id":296571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suir, Glenn","contributorId":56331,"corporation":false,"usgs":true,"family":"Suir","given":"Glenn","affiliations":[],"preferred":false,"id":296570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sapkota, Sijan sapkotas@usgs.gov","contributorId":2995,"corporation":false,"usgs":true,"family":"Sapkota","given":"Sijan","email":"sapkotas@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":296569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":85862,"text":"ofr20061260D - 2008 - Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts","interactions":[],"lastModifiedDate":"2012-02-10T00:11:46","indexId":"ofr20061260D","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2006-1260","chapter":"D","title":"Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts","docAbstract":"The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of nine 7.5-minute quadrangles (417 mi2 total) in south-central Massachusetts (fig. 1). Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and in resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, or organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions.\r\nThe mapped distribution of surficial materials that lie between the land surface and the bedrock surface is based on detailed geologic mapping of 7.5-minute topographic quadrangles, produced as part of an earlier (1938-1982) cooperative statewide mapping program between the\r\nU.S. Geological Survey and the Massachusetts Department of Public Works (now Massachusetts Highway Department) (Page, 1967; Stone, 1982). Each published geologic map presents a detailed description of local geologic map units, the genesis of the deposits, and age correlations among units. Previously unpublished field compilation maps exist on paper or mylar sheets and these have been digitally rendered for the present map compilation. Regional summaries based on the Massachusetts surficial geologic mapping studies discuss the ages of multiple glaciations, the nature of glaciofluvial, glaciolacustrine, and glaciomarine deposits, and the processes of ice advance and retreat across Massachusetts (Koteff and Pessl, 1981; papers in Larson and Stone, 1982; Oldale and Barlow, 1986; Stone and Borns, 1986; Warren and Stone, 1986).\r\nThis compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This surficial geologic map layer covering nine quadrangles revises previous digital surficial geologic maps (Stone and others, 1993; MassGIS, 1999) that were compiled on base maps at regional scales of 1:125,000 and 1:250,000. The purpose of this study is to provide fundamental geologic data for the evaluation of natural resources, hazards, and land information within the Commonwealth of Massachusetts.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20061260D","isbn":"9781411320499","collaboration":"Prepared in cooperation with the Commonwealth of Massachusetts, Office of the State Geologist and Executive Office of Energy and Environmental Affairs","usgsCitation":"Stone, B.D., Stone, J.R., and DiGiacomo-Cohen, M.L., 2008, Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts: U.S. Geological Survey Open-File Report 2006-1260, Report: iii, 13 p.; Maps; GIS Files; Metadata; TIFs; ReadMe, https://doi.org/10.3133/ofr20061260D.","productDescription":"Report: iii, 13 p.; Maps; GIS Files; Metadata; TIFs; ReadMe","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195813,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11604,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1260/D/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.5,41.25 ], [ -73.5,42.916666666666664 ], [ -69.91666666666667,42.916666666666664 ], [ -69.91666666666667,41.25 ], [ -73.5,41.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae3e4b07f02db68956f","contributors":{"authors":[{"text":"Stone, Byron D. 0000-0001-6092-0798 bdstone@usgs.gov","orcid":"https://orcid.org/0000-0001-6092-0798","contributorId":1702,"corporation":false,"usgs":true,"family":"Stone","given":"Byron","email":"bdstone@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":296607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Janet Radway jrstone@usgs.gov","contributorId":1695,"corporation":false,"usgs":true,"family":"Stone","given":"Janet","email":"jrstone@usgs.gov","middleInitial":"Radway","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":296606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DiGiacomo-Cohen, Mary L.","contributorId":45253,"corporation":false,"usgs":true,"family":"DiGiacomo-Cohen","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":296608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":85861,"text":"ofr20081163 - 2008 - Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002","interactions":[],"lastModifiedDate":"2018-04-02T16:32:41","indexId":"ofr20081163","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1163","title":"Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002","docAbstract":"This report presents and describes the digital datasets that characterize nutrient source inputs, environmental characteristics, and instream nutrient loads for the purpose of calibrating and applying a nutrient water-quality model for the southeastern United States for 2002. The model area includes all of the river basins draining to the south Atlantic and the eastern Gulf of Mexico, as well as the Tennessee River basin (referred to collectively as the SAGT area). The water-quality model SPARROW (SPAtially-Referenced Regression On Watershed attributes), developed by the U.S. Geological Survey, uses a regression equation to describe the relation between watershed attributes (predictors) and measured instream loads (response). Watershed attributes that are considered to describe nutrient input conditions and are tested in the SPARROW model for the SAGT area as source variables include atmospheric deposition, fertilizer application to farmland, manure from livestock production, permitted wastewater discharge, and land cover. Watershed and channel attributes that are considered to affect rates of nutrient transport from land to water and are tested in the SAGT SPARROW model as nutrient-transport variables include characteristics of soil, landform, climate, reach time of travel, and reservoir hydraulic loading. Datasets with estimates of each of these attributes for each individual reach or catchment in the reach-catchment network are presented in this report, along with descriptions of methods used to produce them. \n\nMeasurements of nutrient water quality at stream monitoring sites from a combination of monitoring programs were used to develop observations of the response variable - mean annual nitrogen or phosphorus load - in the SPARROW regression equation. Instream load of nitrogen and phosphorus was estimated using bias-corrected log-linear regression models using the program Fluxmaster, which provides temporally detrended estimates of long-term mean load well-suited for spatial comparisons. The detrended, or normalized, estimates of load are useful for regional-scale assessments but should be used with caution for local-scale interpretations, for which use of loads estimated for actual time periods and employing more detailed regression analysis is suggested. The mean value of the nitrogen yield estimates, normalized to 2002, for 637 stations in the SAGT area is 4.7 kilograms per hectare; the mean value of nitrogen flow-weighted mean concentration is 1.2 milligrams per liter. The mean value of the phosphorus yield estimates, normalized to 2002, for the 747 stations in the SAGT area is 0.66 kilogram per hectare; the mean value of phosphorus flow-weighted mean concentration is 0.17 milligram per liter.\n\nNutrient conditions measured in streams affected by substantial influx or outflux of water and nutrient mass across surface-water basin divides do not reflect nutrient source and transport conditions in the topographic watershed; therefore, inclusion of such streams in the SPARROW modeling approach is considered inappropriate. River basins identified with this concern include south Florida (where surface-water flow paths have been extensively altered) and the Oklawaha, Crystal, Lower Sante Fe, Lower Suwanee, St. Marks, and Chipola River basins in central and northern Florida (where flow exchange with the underlying regional aquifer may represent substantial nitrogen influx to and outflux from the surface-water basins).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20081163","usgsCitation":"Hoos, A.B., Terziotti, S., McMahon, G., Savvas, K., Tighe, K., and Alkons-Wolinsky, R., 2008, Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002: U.S. Geological Survey Open-File Report 2008-1163, Report: viii, 51 p.; Data (ZIP), https://doi.org/10.3133/ofr20081163.","productDescription":"Report: viii, 51 p.; Data (ZIP)","additionalOnlineFiles":"Y","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":195273,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11603,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1163/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92,25 ], [ -92,40 ], [ -75,40 ], [ -75,25 ], [ -92,25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac5e4b07f02db679c48","contributors":{"authors":[{"text":"Hoos, Anne B. abhoos@usgs.gov","contributorId":2236,"corporation":false,"usgs":true,"family":"Hoos","given":"Anne","email":"abhoos@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":296602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":296601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":296600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savvas, Katerina","contributorId":107390,"corporation":false,"usgs":true,"family":"Savvas","given":"Katerina","email":"","affiliations":[],"preferred":false,"id":296605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tighe, Kirsten C.","contributorId":99930,"corporation":false,"usgs":true,"family":"Tighe","given":"Kirsten C.","affiliations":[],"preferred":false,"id":296604,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alkons-Wolinsky, Ruth","contributorId":55921,"corporation":false,"usgs":true,"family":"Alkons-Wolinsky","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":296603,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":85859,"text":"sir20085104 - 2008 - Peak-flow frequency estimates based on data through water year 2001 for selected streamflow-gaging stations in South Dakota","interactions":[],"lastModifiedDate":"2017-10-14T12:29:08","indexId":"sir20085104","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-5104","title":"Peak-flow frequency estimates based on data through water year 2001 for selected streamflow-gaging stations in South Dakota","docAbstract":"Numerous users, including the South Dakota Department of Transportation, have continuing needs for peak-flow information for the design of highway infrastructure and many other purposes. This report documents results from a cooperative study between the South Dakota Department of Transportation and the U.S. Geological Survey to provide an update of peak-flow frequency estimates for South Dakota.\r\n\r\nEstimates of peak-flow magnitudes for 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals are reported for 272 streamflow-gaging stations, which include most gaging stations in South Dakota with 10 or more years of systematic peak-flow records through water year 2001. Recommended procedures described in Bulletin 17B were used as primary guidelines for developing peak-flow frequency estimates. The computer program PEAKFQ developed by the U.S. Geological Survey was used to run the frequency analyses. Flood frequencies for all stations were initially analyzed by using standard Bulletin 17B default procedures for fitting the log-Pearson III distribution. The resulting preliminary frequency curves were then plotted on a log-probability scale, and fits of the curves with systematic data were evaluated. In many cases, results of the default Bulletin 17B analyses were determined to be satisfactory. In other cases, however, the results could be improved by using various alternative procedures for frequency analysis.\r\n\r\nAlternative procedures for some stations included adjustments to skew coefficients or use of user-defined low-outlier criteria. Peak-flow records for many gaging stations are strongly influenced by low- or zero-flow values. This situation often results in a frequency curve that plots substantially above the systematic record data points at the upper end of the frequency curve. Adjustments to low-outlier criteria reduced the influence of very small peak flows and generally focused the analyses on the upper parts of the frequency curves (10- to 500-year recurrence intervals).\r\n\r\nThe most common alternative procedures involved several different methods to extend systematic records, which was done primarily to address biases resulting from nonrepresentative climatic conditions during several specific periods of record and to reduce inconsistencies among multiple gaging stations along common stream channels with different periods of record. In some cases, records for proximal stations could be combined directly. In other cases, the two-station comparison procedure recommended in Bulletin 17B was used to adjust the mean and standard deviation of the logs of the systematic data for a target station on the basis of correlation with concurrent records from a nearby long-term index station. In some other cases, a 'mixed-station procedure' was used to adjust the log-distributional parameters for a target station, on the basis of correlation with one or more index stations, for the purpose of fitting the log-Pearson III distribution.\r\n\r\nHistorical adjustment procedures were applied to peak-flow frequency analyses for 17 South Dakota gaging stations. A historical adjustment period extending back to 1881 (121 years) was used for 12 gaging stations in the James and Big Sioux River Basins, and various other adjustment periods were used for additional stations. Large peak flows that occurred in 1969 and 1997 accounted for 13 of the 17 historical adjustments. Other years for which historical peak flows were used include 1957, 1962, 1992, and 2001.\r\n\r\nA regional mixed-population analysis was developed to address complications associated with many high outliers for the Black Hills region. This analysis included definition of two populations of flood events. The population of flood events that composes the main body of peak flows for a given station is considered the 'ordinary-peaks population,' and the population of unusually large peak flows that plot substantially above the main body of peak flows on log-probability scale is co","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20085104","collaboration":"Prepared in cooperation with the South Dakota Department of Transportation","usgsCitation":"Sando, S.K., Driscoll, D.G., and Parrett, C., 2008, Peak-flow frequency estimates based on data through water year 2001 for selected streamflow-gaging stations in South Dakota: U.S. Geological Survey Scientific Investigations Report 2008-5104, Report: xii, 42 p.; Appendixes; Table 8 Spreadsheet, https://doi.org/10.3133/sir20085104.","productDescription":"Report: xii, 42 p.; Appendixes; Table 8 Spreadsheet","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":194489,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11601,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5104/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"South Dakota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.25,42 ], [ -104.25,46 ], [ -96,46 ], [ -96,42 ], [ -104.25,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae1e4b07f02db688991","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":296596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Daniel G. dgdrisco@usgs.gov","contributorId":1558,"corporation":false,"usgs":true,"family":"Driscoll","given":"Daniel","email":"dgdrisco@usgs.gov","middleInitial":"G.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":296597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parrett, Charles","contributorId":9635,"corporation":false,"usgs":true,"family":"Parrett","given":"Charles","email":"","affiliations":[],"preferred":false,"id":296598,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":85858,"text":"sir20085111 - 2008 - Temporal and spatial variations in precipitation, streamflow, suspended-sediment loads and yields, and land-condition trend analysis at the U.S. Army Piñon Canyon Maneuver Site, Las Animas County, Colorado, 1983 through 2007","interactions":[],"lastModifiedDate":"2021-11-24T21:43:36.072525","indexId":"sir20085111","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-5111","title":"Temporal and spatial variations in precipitation, streamflow, suspended-sediment loads and yields, and land-condition trend analysis at the U.S. Army Piñon Canyon Maneuver Site, Las Animas County, Colorado, 1983 through 2007","docAbstract":"In 2007, the U.S. Geological Survey, in cooperation with the U.S. Department of the Army, began an assessment of the spatial and temporal variations in precipitation, streamflow, suspended-sediment loads and yields, changes in land condition, effects of the tributaries on the Purgatoire River and the possible relation of effects from military training to hydrology and land conditions that have occurred at Pinon Canyon Maneuver Site (PCMS) from 1983 through 2007. Data were collected for precipitation (19 stations) and streamflow and sediment load (5 tributary and 2 main-stem Purgatoire River stations) during 1983 through 2007 for various time periods. The five tributary stations were Van Bremer Arroyo near Model, Taylor Arroyo below Rock Crossing, Lockwood Canyon Creek near Thatcher, Red Rock Canyon Creek at the mouth, and Bent Canyon Creek at the mouth. In addition, data were collected at two Purgatoire River stations: Purgatoire River near Thatcher and Purgatoire River at Rock Crossing.","language":"English","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20085111","usgsCitation":"Stevens, M.R., Dupree, J., and Kuzmiak, J., 2008, Temporal and spatial variations in precipitation, streamflow, suspended-sediment loads and yields, and land-condition trend analysis at the U.S. Army Piñon Canyon Maneuver Site, Las Animas County, Colorado, 1983 through 2007: U.S. Geological Survey Scientific Investigations Report 2008-5111, vii, 46 p., https://doi.org/10.3133/sir20085111.","productDescription":"vii, 46 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1983-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":121212,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2008_5111.gif"},{"id":392115,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_84089.htm"},{"id":11600,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2008/5111/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","county":"Las Animas County","otherGeospatial":"U.S. Army Pinion Canyon Maneuver Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.1667,\n 37.3333\n ],\n [\n -103.5792,\n 37.3333\n ],\n [\n -103.5792,\n 37.6667\n ],\n [\n -104.1667,\n 37.6667\n ],\n [\n -104.1667,\n 37.3333\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adae4b07f02db685689","contributors":{"authors":[{"text":"Stevens, M. R.","contributorId":25178,"corporation":false,"usgs":true,"family":"Stevens","given":"M.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":296594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupree, J.","contributorId":17329,"corporation":false,"usgs":true,"family":"Dupree","given":"J.","email":"","affiliations":[],"preferred":false,"id":296593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuzmiak, J. M.","contributorId":46548,"corporation":false,"usgs":true,"family":"Kuzmiak","given":"J. M.","affiliations":[],"preferred":false,"id":296595,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":85857,"text":"ofr20081240 - 2008 - Landscape Features Shape Genetic Structure in Threatened Northern Spotted Owls","interactions":[],"lastModifiedDate":"2012-02-02T00:14:32","indexId":"ofr20081240","displayToPublicDate":"2008-07-23T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2008-1240","title":"Landscape Features Shape Genetic Structure in Threatened Northern Spotted Owls","docAbstract":"Several recent studies have shown that landscape features can strongly affect spatial patterns of gene flow and genetic variation. Understanding landscape effects on genetic variation is important in conservation for defining management units and understanding movement patterns. The landscape may have little effect on gene flow, however, in highly mobile species such as birds. We tested for genetic breaks associated with landscape features in the northern spotted owl (Strix occidentalis caurina), a threatened subspecies associated with old forests in the U.S. Pacific Northwest and extreme southwestern Canada. We found little evidence for distinct genetic breaks in northern spotted owls using a large microsatellite dataset (352 individuals from across the subspecies' range genotyped at 10 loci). Nonetheless, dry low-elevation valleys and the Cascade and Olympic Mountains restrict gene flow, while the Oregon Coast Range facilitates it. The wide Columbia River is not a barrier to gene flow. In addition, inter-individual genetic distance and latitude were negatively related, likely reflecting northward colonization following Pleistocene glacial recession. Our study shows that landscape features may play an important role in shaping patterns of genetic variation in highly vagile taxa such as birds.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/ofr20081240","usgsCitation":"Funk, W.C., Forsman, E.D., Mullins, T., and Haig, S.M., 2008, Landscape Features Shape Genetic Structure in Threatened Northern Spotted Owls: U.S. Geological Survey Open-File Report 2008-1240, iv, 13 p., https://doi.org/10.3133/ofr20081240.","productDescription":"iv, 13 p.","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":195038,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":11599,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1240/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b20e4b07f02db6abb06","contributors":{"authors":[{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":296592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":296591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":296590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":296589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}