Arc-continent collisions occur commonly in the plate-tectonic cycle and result in rapidly formed and rapidly collapsing orogens, often spanning just 5-15 My. Growth of continental masses through arc-continent collision is widely thought to be a major process governing the structural and geochemical evolution of the continental crust over geologic time. Collisions of intra-oceanic arcs with passive continental margins (a situation in which the arc, on the upper plate, faces the continent) involve a substantially different geometry than collisions of intra-oceanic arcs with active continental margins (a situation requiring more than one convergence zone and in which the arc, on the lower plate, backs into the continent), with variable preservation potential for basins in each case. Substantial differences also occur between trench and forearc evolution in tectonically erosive versus tectonically accreting margins, both before and after collision.
\nWe examine the evolution of trenches, trench-slope basins, forearc basins, intra-arc basins, and backarc basins during arc-continent collision. The preservation potential of trench-slope basins is low; in collision they are rapidly uplifted and eroded, and at erosive margins they are progressively destroyed by subduction erosion. Post-collisional preservation of trench sediment and trench-slope basins is biased toward margins that were tectonically accreting for a substantial length of time before collision. Forearc basins in erosive margins are usually floored by strong lithosphere and may survive collision with a passive margin, sometimes continuing sedimentation throughout collision and orogeny. The low flexural rigidity of intra-arc basins makes them deep and, if preserved, potentially long records of arc and collisional tectonism. Backarc basins, in contrast, are typically subducted and their sediment either lost or preserved only as fragments in melange sequences. A substantial proportion of the sediment derived from collisional orogenesis ends up in the foreland basin that forms as a result of collision, and may be preserved largely undeformed. Compared to continent-continent collisional foreland basins, arc-continent collisional foreland basins are short-lived and may undergo partial inversion after collision as a new, active continental margin forms outboard of the collision zone and the orogen whose load forms the basin collapses in extension.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonics of Sedimentary Basins: Recent Advances","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Wiley-Blackwell","publisherLocation":"Hoboken, NJ","doi":"10.1002/9781444347166.ch17","usgsCitation":"Draut, A.E., and Clift, P.D., 2012, Basins in ARC-continental collisions, chap. of Tectonics of Sedimentary Basins: Recent Advances, p. 347-368, https://doi.org/10.1002/9781444347166.ch17.","productDescription":"22 p.","startPage":"347","endPage":"368","numberOfPages":"22","ipdsId":"IP-015773","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":280748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280743,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/9781444347166.ch17"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2012-01-30","publicationStatus":"PW","scienceBaseUri":"53cd4ee6e4b0b290850f25e8","contributors":{"editors":[{"text":"Busby, Cathy","contributorId":113649,"corporation":false,"usgs":true,"family":"Busby","given":"Cathy","email":"","affiliations":[],"preferred":false,"id":509658,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Azor, Antonio","contributorId":113881,"corporation":false,"usgs":true,"family":"Azor","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":509659,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":487373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clift, Peter D.","contributorId":17711,"corporation":false,"usgs":true,"family":"Clift","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":487372,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042357,"text":"sir20125269 - 2012 - Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011","interactions":[],"lastModifiedDate":"2013-01-17T11:22:10","indexId":"sir20125269","displayToPublicDate":"2013-01-08T00:00:00","publicationYear":"2012","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":"2012-5269","title":"Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the Kansas Water Office, investigated sediment transport to and from three small impoundments (average surface area of 0.1 to 0.8 square miles) in northeast Kansas during March 2009 through September 2011. Streamgages and continuous turbidity sensors were operated upstream and downstream from Atchison County, Banner Creek, and Centralia Lakes to study the effect of varied watershed characteristics and agricultural practices on sediment transport in small watersheds in northeast Kansas. Atchison County Lake is located in a predominantly agricultural basin of row crops, with wide riparian buffers along streams, a substantial amount of tile drainage, and numerous small impoundments (less than 0.05 square miles; hereafter referred to as “ponds”). Banner Creek Lake is a predominantly grassland basin with numerous small ponds located in the watershed, and wide riparian buffers along streams. Centralia Lake is a predominantly agricultural basin of row crops with few ponds, few riparian buffers along streams, and minimal tile drainage. Upstream from Atchison County, Banner Creek, and Centralia Lakes 24, 38, and 32 percent, respectively, of the total load was transported during less than 0.1 percent (approximately 0.9 days) of the time. Despite less streamflow in 2011, larger sediment loads during that year indicate that not all storm events transport the same amount of sediment; larger, extreme storms during the spring may transport much larger sediment loads in small Kansas watersheds. Annual sediment yields were 360, 400, and 970 tons per square mile per year at Atchison County, Banner, and Centralia Lake watersheds, respectively, which were less than estimated yields for this area of Kansas (between 2,000 and 5,000 tons per square mile per year). Although Centralia and Atchison County Lakes had similar percentages of agricultural land use, mean annual sediment yields upstream from Centralia Lake were about 2.7 times those at Atchison County or Banner Creek Lakes. These data indicate larger yields of sediment from watersheds with row crops and those with fewer small ponds, and smaller yields in watersheds which are primarily grassland, or agricultural with substantial tile drainage and riparian buffers along streams. These results also indicated that a cultivated watershed can produce yields similar to those observed under the assumed reference (or natural) condition. Selected small ponds were studied in the Atchison County Lake watershed to characterize the role of small ponds in sediment trapping. Studied ponds trapped about 8 percent of the sediment upstream from the sediment-sampling site. When these results were extrapolated to the other ponds in the watershed, differences in the extent of these ponds was not the primary factor affecting differences in yields among the three watersheds. However, the selected small ponds were both 45 years old at the time of this study, and have reduced capacity because of being filled in with sediments. Additionally, trapping efficiency of these small ponds decreased over five observed storms, indicating that processes that suspended or resuspended sediments in these shallow ponds, such as wind and waves, affected their trapping efficiencies. While small ponds trapped sediments in small storms, they could be a source of sediment in larger or more closely spaced storm events. Channel slope was similar at all three watersheds, 0.40, 0.46, and 0.31 percent at Atchison County, Banner Creek, and Centralia Lake watersheds, respectively. Other factors, such as increased bank and stream erosion, differences in tile drainage, extent of grassland, or riparian buffers, could be the predominant factors affecting sediment yields from these basins. These results show that reference-like sediment yields may be observed in heavily agricultural watersheds through a combination of field-scale management activities and stream channel protection. When computing loads using published erosion rates obtained by single-point survey methodology, streambank contributions from the main stem of Banner Creek are three times more than the sediment load observed by this study at the sediment sampling site at Banner Creek, 2.6 times more than the sediment load observed by this study at the sediment sampling site at Clear Creek (upstream from Atchison County Lake), and are 22 percent of the load observed by this study at the sediment sampling site at Black Vermillion River above Centralia Lake. Comparisons of study sites to similarly sized urban and urbanizing watersheds in Johnson County, Kansas indicated that sediment yields from the Centralia Lake watershed were similar to those in construction-affected watersheds, while much smaller sediment yields in the Atchison County and Banner Creek watersheds were comparable to stable, heavily urbanized watersheds. Comparisons of study sites to larger watersheds upstream from Tuttle Creek Lake indicate the Black Vermillion River watershed continues to have high sediment yields despite 98 percent of sediment from the Centralia watershed (a headwater of the Black Vermillion River) being trapped in Centralia Lake. Estimated trapping efficiencies for the larger watershed lakes indicated that Banner Creek and Centralia Lakes trapped 98 percent of incoming sediment, whereas Atchison County Lake trapped 72 percent of incoming sediment during the 3-year study period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125269","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Foster, G., Lee, C., and Ziegler, A., 2012, Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011: U.S. Geological Survey Scientific Investigations Report 2012-5269, vi, 38 p., https://doi.org/10.3133/sir20125269.","productDescription":"vi, 38 p.","numberOfPages":"48","onlineOnly":"Y","temporalStart":"2009-03-01","temporalEnd":"2011-09-30","ipdsId":"IP-035289","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":265371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5269.gif"},{"id":265370,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5269/"},{"id":265369,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5269/sir12-5269.pdf"}],"country":"United States","state":"Kansas","county":"Atchison;Brown;Doniphan;Jackson;Jefferson;Marshall;Nemaha;Pottawatomie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.333333,39.366667 ], [ -96.333333,39.8 ], [ -95.25,39.8 ], [ -95.25,39.366667 ], [ -96.333333,39.366667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ed3fe1e4b0438b00db0746","contributors":{"authors":[{"text":"Foster, Guy M. gfoster@usgs.gov","contributorId":3437,"corporation":false,"usgs":true,"family":"Foster","given":"Guy M.","email":"gfoster@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":471375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Casey J. 0000-0002-5753-2038","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":31062,"corporation":false,"usgs":true,"family":"Lee","given":"Casey J.","affiliations":[],"preferred":false,"id":471376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":471374,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042411,"text":"ds734 - 2012 - Quality of surface water in Missouri, water year 2011","interactions":[],"lastModifiedDate":"2016-08-10T11:14:59","indexId":"ds734","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"734","title":"Quality of surface water in Missouri, water year 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2011 water year (October 1, 2010, through September 30, 2011), data were collected at 75 stations—72 Ambient Water-Quality Monitoring Network stations, 2 U.S. Geological Survey National Stream Quality Accounting Network stations, and 1 spring sampled in cooperation with the U.S. Forest Service. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, fecal coliform bacteria, Escherichia coli bacteria, dissolved nitrate plus nitrite, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 72 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds734","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., 2012, Quality of surface water in Missouri, water year 2011: U.S. Geological Survey Data Series 734, vi, 22 p., https://doi.org/10.3133/ds734.","productDescription":"vi, 22 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-10-01","temporalEnd":"2011-09-30","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":265365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_734.gif"},{"id":265363,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/734/"},{"id":265364,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/734/ds734.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Missouri","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.8,36.0 ], [ -95.8,40.6 ], [ -89.1,40.6 ], [ -89.1,36.0 ], [ -95.8,36.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee6ee4b07f1501afcfc0","contributors":{"authors":[{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471488,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70042404,"text":"ds709I - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:13:56","indexId":"ds709I","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"I","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’ picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’ local zone (41 for Dusar-Shaida) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Dusar-Shaida area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Dusar-Shaida study area, three subareas were designated for detailed field investigations (that is, the Dahana-Misgaran, Kaftar VMS, and Shaida subareas); these subareas were extracted from the area’ image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709I","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 63.42 x 42.75 inches; 28 Image Files; 28 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709I.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 63.42 x 42.75 inches; 28 Image Files; 28 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_i.jpg"},{"id":265333,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/i/index_maps/Dusar-Shaida_Area-of-Interest_Index_Map.pdf"},{"id":265334,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/i/index_maps/Dusar-Shaida_Image_Index_Map.pdf"},{"id":265335,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/i/index_maps/Dusar-Shaida_Subarea_Image_Index_Map.pdf"},{"id":265338,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/i/metadata/metadata.html"},{"id":265339,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/i/shapefiles/shapefiles.html"},{"id":265336,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/i/index_maps/index_maps.html"},{"id":265337,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/i/image_files/image_files.html"},{"id":265340,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":265331,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/i/"},{"id":265332,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/i/1_readme.txt"}],"country":"Afghanistan","state":"Farah;Herat","otherGeospatial":"Dusar-shaida Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 61.0,33.2 ], [ 61.0,34.0 ], [ 62.5,34.0 ], [ 62.5,33.2 ], [ 61.0,33.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee6be4b07f1501afcfb0","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":471471,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042329,"text":"70042329 - 2012 - Understanding the role of ecohydrological feedbacks in ecosystem state change in drylands","interactions":[],"lastModifiedDate":"2013-01-10T15:47:55","indexId":"70042329","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the role of ecohydrological feedbacks in ecosystem state change in drylands","docAbstract":"Ecohydrological feedbacks are likely to be critical for understanding the mechanisms by which changes in exogenous forces result in ecosystem state change. We propose that in drylands, the dynamics of ecosystem state change are determined by changes in the type (stabilizing vs amplifying) and strength of ecohydrological feedbacks following a change in exogenous forces. Using a selection of five case studies from drylands, we explore the characteristics of ecohydrological feedbacks and resulting dynamics of ecosystem state change. We surmise that stabilizing feedbacks are critical for the provision of plant-essential resources in drylands. Exogenous forces that break these stabilizing feedbacks can alter the state of the system, although such changes are potentially reversible if strong amplifying ecohydrological feedbacks do not develop. The case studies indicate that if amplifying ecohydrological feedbacks do develop, they are typically associated with abiotic processes such as runoff, erosion (by wind and water), and fire. These amplifying ecohydrological feedbacks progressively modify the system in ways that are long-lasting and possibly irreversible on human timescales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecohydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/eco.265","usgsCitation":"Turnbull, L., Wilcox, B., Belnap, J., Ravi, S., D’Odorico, P., Childers, D., Gwenzi, W., Okin, G., Wainwright, J., Caylor, K., and Sankey, T., 2012, Understanding the role of ecohydrological feedbacks in ecosystem state change in drylands: Ecohydrology, v. 5, no. 2, p. 174-183, https://doi.org/10.1002/eco.265.","productDescription":"10 p.","startPage":"174","endPage":"183","numberOfPages":"10","ipdsId":"IP-029337","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":474106,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.265","text":"Publisher Index Page"},{"id":265524,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/eco.265"},{"id":265526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-11-25","publicationStatus":"PW","scienceBaseUri":"53cd7a32e4b0b2908510d537","contributors":{"authors":[{"text":"Turnbull, L.","contributorId":74649,"corporation":false,"usgs":true,"family":"Turnbull","given":"L.","email":"","affiliations":[],"preferred":false,"id":471293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilcox, B.P.","contributorId":83490,"corporation":false,"usgs":true,"family":"Wilcox","given":"B.P.","email":"","affiliations":[],"preferred":false,"id":471294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, J. 0000-0001-7471-2279","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":23872,"corporation":false,"usgs":true,"family":"Belnap","given":"J.","affiliations":[],"preferred":false,"id":471288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravi, S.","contributorId":45977,"corporation":false,"usgs":true,"family":"Ravi","given":"S.","affiliations":[],"preferred":false,"id":471290,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"D’Odorico, P.","contributorId":56528,"corporation":false,"usgs":true,"family":"D’Odorico","given":"P.","email":"","affiliations":[],"preferred":false,"id":471291,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Childers, D.","contributorId":86654,"corporation":false,"usgs":true,"family":"Childers","given":"D.","email":"","affiliations":[],"preferred":false,"id":471295,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gwenzi, W.","contributorId":43242,"corporation":false,"usgs":true,"family":"Gwenzi","given":"W.","email":"","affiliations":[],"preferred":false,"id":471289,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Okin, G.","contributorId":64963,"corporation":false,"usgs":true,"family":"Okin","given":"G.","affiliations":[],"preferred":false,"id":471292,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wainwright, J.","contributorId":19046,"corporation":false,"usgs":true,"family":"Wainwright","given":"J.","email":"","affiliations":[],"preferred":false,"id":471287,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Caylor, K.K.","contributorId":15820,"corporation":false,"usgs":true,"family":"Caylor","given":"K.K.","email":"","affiliations":[],"preferred":false,"id":471285,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sankey, T.","contributorId":16287,"corporation":false,"usgs":true,"family":"Sankey","given":"T.","email":"","affiliations":[],"preferred":false,"id":471286,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70042409,"text":"ds709J - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:10:57","indexId":"ds709J","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"J","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Tourmaline) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Tourmaline area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709J","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Cagney, L.E., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 26.58 x 24.67 inches; 8 Image Files; 8 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709J.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 26.58 x 24.67 inches; 8 Image Files; 8 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_j.jpg"},{"id":265344,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/j/index_maps/Tourmaline_Area-of-Interest_Index_Map.pdf"},{"id":265345,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/j/index_maps/Tourmaline_Image_Index_Map.pdf"},{"id":265346,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/j/index_maps/index_maps.html"},{"id":265347,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/j/image_files/image_files.html"},{"id":265348,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/j/metadata/metadata.html"},{"id":265349,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/j/shapefiles/shapefiles.html"},{"id":265350,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":265342,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/j/"},{"id":265343,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/j/1_readme.txt"}],"country":"Afghanistan","state":"Farah;Herat","otherGeospatial":"Tourmaline Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 61.5,32.8 ], [ 61.5,33.25 ], [ 62.0,33.25 ], [ 62.0,32.8 ], [ 61.5,32.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee6de4b07f1501afcfbc","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":471482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":471483,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042403,"text":"ds709H - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:12:57","indexId":"ds709H","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"H","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Kundalyan) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Kundalyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kundalyan study area, three subareas were designated for detailed field investigations (that is, the Baghawan-Garangh, Charsu-Ghumbad, and Kunag Skarn subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709H","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Cagney, L.E., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 41.22 x 49.43 inches; 16 Image Files; 16 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709H.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 41.22 x 49.43 inches; 16 Image Files; 16 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_h.jpg"},{"id":265320,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/h/"},{"id":265321,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/h/1_readme.txt"},{"id":265322,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/h/index_maps/Kundalyan_Area-of-Interest_Index_Map.pdf"},{"id":265323,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/h/index_maps/Kundalyan_Image_Index_Map.pdf"},{"id":265324,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/h/index_maps/Kundalyan_Subarea_Image_Index_Map.pdf"},{"id":265325,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/h/index_maps/index_maps.html"},{"id":265326,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/h/image_files/image_files.html"},{"id":265327,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/h/metadata/metadata.html"},{"id":265328,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/h/shapefiles/shapefiles.html"},{"id":265329,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","otherGeospatial":"Kundalyan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66.0,31.75 ], [ 66.0,33.0 ], [ 67.0,33.0 ], [ 67.0,31.75 ], [ 66.0,31.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee6de4b07f1501afcfb8","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":471467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":471468,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042410,"text":"ds709K - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:13:12","indexId":"ds709K","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"K","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 1,000-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Kharnak-Kanjar) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Kharnak-Kanjar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kharnak-Kanjar study area, three subareas were designated for detailed field investigations (that is, the Koh-e-Katif Passaband, Panjshah-Mullayan, and Sahebdad-Khanjar subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709K","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 78.68 x 64.04 inches; 26 Image Files; 26 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709K.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 78.68 x 64.04 inches; 26 Image Files; 26 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_k.jpg"},{"id":265354,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/k/index_maps/Kharnak-Kanjar_Area-of-Interest_Index_Map.pdf"},{"id":265355,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/k/index_maps/Kharnak-Kanjar_Image_Index_Map.pdf"},{"id":265356,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/k/index_maps/Kharnak-Kanjar_Subarea_Image_Index_Map.pdf"},{"id":265357,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/k/index_maps/index_maps.html"},{"id":265358,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/k/image_files/image_files.html"},{"id":265359,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/k/metadata/metadata.html"},{"id":265360,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/k/shapefiles/shapefiles.html"},{"id":265361,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":265352,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/k/"},{"id":265353,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/k/1_readme.txt"}],"country":"Afghanistan","state":"Farah;Ghor;Daykundi","otherGeospatial":"Kharnak-kanjar Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 64.0,33.0 ], [ 64.0,34.25 ], [ 65.75,34.25 ], [ 65.75,33.0 ], [ 64.0,33.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee6ce4b07f1501afcfb4","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":471486,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042374,"text":"sir20125268 - 2012 - Hydrologic and sediment data collected from selected basins at the Fort Leonard Wood Military Reservation, Missouri--2010-11","interactions":[],"lastModifiedDate":"2013-01-06T13:53:14","indexId":"sir20125268","displayToPublicDate":"2013-01-06T00:00:00","publicationYear":"2012","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":"2012-5268","title":"Hydrologic and sediment data collected from selected basins at the Fort Leonard Wood Military Reservation, Missouri--2010-11","docAbstract":"Commercial and residential development within a basin often increases the amount of impervious area, which changes the natural hydrologic response to storm events by increasing runoff. Land development and disturbance combined with increased runoff from impervious areas potentially can increase sediment transport. At the Fort Leonard Wood Military Reservation in Missouri, there has been an increase in population and construction activities in the recent past, which has initiated an assessment of the hydrology in selected basins. From April 2010 to December 2011, the U.S. Geological Survey, in cooperation with the U.S. Army Maneuver Support Center at the Fort Leonard Wood Military Reservation, collected hydrologic and suspended-sediment concentration data in six basins at Fort Leonard Wood. Storm-sediment concentration, load, and yield varied from basin to basin and from storm to storm. In general, storm-sediment yield, in pounds per square mile per minute, was greatest from Ballard Hollow tributary (06928410) and Dry Creek (06930250), and monthly storm-sediment yield, in tons per square mile, estimates were largest in Ballard Hollow tributary (06928410), East Gate Hollow tributary (06930058), and Dry Creek (06930250). Sediment samples, collected at nine sites, primarily were collected using automatic samplers and augmented with equal-width-increment cross-sectional samples and manually collected samples when necessary. Storm-sediment load and yield were computed from discharge and suspended-sediment concentration data. Monthly storm-sediment yields also were estimated from the total storm discharge and the mean suspended-sediment concentration at each given site.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125268","isbn":"978-1-4113-3531-8","collaboration":"Prepared in cooperation with U.S. Army Maneuver Support Center at the Fort Leonard Wood Military Reservation","usgsCitation":"Richards, J.M., Rydlund, P.H., and Barr, M.N., 2012, Hydrologic and sediment data collected from selected basins at the Fort Leonard Wood Military Reservation, Missouri--2010-11: U.S. Geological Survey Scientific Investigations Report 2012-5268, vi, 23 p., https://doi.org/10.3133/sir20125268.","productDescription":"vi, 23 p.","numberOfPages":"36","additionalOnlineFiles":"N","temporalStart":"2010-04-01","temporalEnd":"2011-12-31","ipdsId":"IP-039458","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":265315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5268.gif"},{"id":265313,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5268/"},{"id":265314,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5268/sir12-5268.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Missouri","county":"Pulaski","otherGeospatial":"Fort Leonard Wood","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.25,37.583333 ], [ -92.25,37.833333 ], [ -92.0,37.833333 ], [ -92.0,37.583333 ], [ -92.25,37.583333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ea9ceee4b02dd6076fad8b","contributors":{"authors":[{"text":"Richards, Joseph M. 0000-0002-9822-2706 richards@usgs.gov","orcid":"https://orcid.org/0000-0002-9822-2706","contributorId":2370,"corporation":false,"usgs":true,"family":"Richards","given":"Joseph","email":"richards@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471404,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042379,"text":"fs20123138 - 2012 - Assessing the vulnerability of public-supply wells to contamination: Rio Grande aquifer system in Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2013-01-06T12:14:53","indexId":"fs20123138","displayToPublicDate":"2013-01-06T00:00:00","publicationYear":"2012","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":"2012-3138","title":"Assessing the vulnerability of public-supply wells to contamination: Rio Grande aquifer system in Albuquerque, New Mexico","docAbstract":"This fact sheet highlights findings from the vulnerability study of a public-supply well in Albuquerque, New Mexico (hereafter referred to as “the study well”). The study well produces about 3,000 gallons of water per minute from the Rio Grande aquifer system. Water samples were collected at the study well, at two other nearby public-supply wells, and at monitoring wells installed in or near the simulated zone of contribution to the study well. Untreated water samples from the study well contained arsenic at concentrations exceeding the Maximum Contaminant Level (MCL) of 10 micrograms per liter (µg/L) established by the U.S. Environmental Protection Agency for drinking water. Volatile organic compounds (VOCs) and nitrate also were detected, although at concentrations at least an order of magnitude less than established drinking-water standards, where such standards exist. Overall, study findings point to four primary influences on the movement and (or) fate of contaminants and the vulnerability of the public-supply well in Albuquerque: (1) groundwater age (how long ago water entered, or recharged, the aquifer), (2) groundwater development (introduction of manmade recharge and discharge sources), (3) natural geochemical conditions of the aquifer, and (4) seasonal pumping stresses. Concentrations of the isotope carbon-14 indicate that groundwater from most sampled wells in the local study area is predominantly water that entered, or recharged, the aquifer more than 6,000 years ago. However, the additional presence of the age tracer tritium in several groundwater samples at concentrations above 0.3 tritium units indicates that young (post-1950) recharge is reaching the aquifer across broad areas beneath Albuquerque. This young recharge is mixing with the thousands-of-years-old water, is migrating to depths as great as 245 feet below the water table, and is traveling to some (but not all) of the public-supply wells sampled. Most groundwater samples containing a fraction of young water also contain manmade VOCs, including chloroform (a byproduct of drinking-water chlorination), which indicates that the source of young recharge is, at least in part, infiltration of chlorinated municipal-supply water from leaking waterlines and sewerlines or from turf watering. Other likely manmade, urban recharge sources are seepage from constructed ponds and unlined portions of a stormwater diversion channel. A regional-scale computer-model simulation of groundwater flow and transport to the public-supply well shows that manmade sources of recharge and discharge that were added after about 1930 have greatly altered directions of groundwater flow near Albuquerque and have caused water levels to decline by as much as 120 feet. Local-scale simulations show that seasonal changes in the pumping schedule of the study well affect the age and quality of water produced by the well. Increased pumping during the summer causes significant volumes of water to flow downward from the shallow to the intermediate zones of the aquifer, causing a higher fraction of young water to be produced by the well in the summer than in the winter months and a corresponding increase in VOC detections in the summer relative to the winter. During the winter when the study-well pump is idle for several hours each day, old, high-arsenic water from the deep zone of the aquifer travels up the wellbore and exits into the intermediate zone of the aquifer. When the pump is activated in the winter (for a relatively short time each day), some of the leaked, high-arsenic water is recaptured by the well. This results in a higher arsenic concentration (commonly more than 12 µg/L) in water produced in the winter than in the summer, and a smaller fraction of young water being produced by the well in the winter than in the summer (6 percent in the winter, compared to 11 percent in the summer). Knowledge of the vertical flow direction (both natural and pumping-enhanced) in the vicinity of a long-screened well, coupled with understanding of variations in contaminant concentrations with depth in the aquifer, can help water managers predict the positive or negative effect that wellbore flow will have on water quality and can lead to development of strategies to mitigate contamination (such as changes in pumping schedules or development of devices to inhibit wellbore flow when the pump is off).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123138","collaboration":"National Water-Quality Assessment, Transport of Anthropogenic and Natural Contaminants (TANC) to Public-Supply Wells","usgsCitation":"Jagucki, M.L., Bexfield, L.M., Heywood, C.E., and Eberts, S., 2012, Assessing the vulnerability of public-supply wells to contamination: Rio Grande aquifer system in Albuquerque, New Mexico: U.S. Geological Survey Fact Sheet 2012-3138, 6 p., https://doi.org/10.3133/fs20123138.","productDescription":"6 p.","additionalOnlineFiles":"N","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":265301,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3138/"},{"id":265302,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3138/pdf/fs2012-3138.pdf"},{"id":265303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3138.gif"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Rio Grande","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.666667,35.041667 ], [ -106.666667,35.1 ], [ -106.608333,35.1 ], [ -106.608333,35.041667 ], [ -106.666667,35.041667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ea9cebe4b02dd6076fad87","contributors":{"authors":[{"text":"Jagucki, Martha L. 0000-0003-3798-8393 mjagucki@usgs.gov","orcid":"https://orcid.org/0000-0003-3798-8393","contributorId":1794,"corporation":false,"usgs":true,"family":"Jagucki","given":"Martha","email":"mjagucki@usgs.gov","middleInitial":"L.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heywood, Charles E. cheywood@usgs.gov","contributorId":2043,"corporation":false,"usgs":true,"family":"Heywood","given":"Charles","email":"cheywood@usgs.gov","middleInitial":"E.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eberts, Sandra M. smeberts@usgs.gov","contributorId":2264,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra M.","email":"smeberts@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471423,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042074,"text":"70042074 - 2012 - Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition","interactions":[],"lastModifiedDate":"2014-05-14T12:41:22","indexId":"70042074","displayToPublicDate":"2013-01-05T11:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition","docAbstract":"Stream indicators used to make assessments of biological condition are influenced by many possible sources of variability. To examine this issue, we used multiple-year and multiple-reach diatom, fish, and invertebrate data collected from 20 least-disturbed and 46 developed stream segments between 1993 and 2004 as part of the US Geological Survey National Water Quality Assessment Program. We used a variance-component model to summarize the relative and absolute magnitude of 4 variance components (among-site, among-year, site × year interaction, and residual) in indicator values (observed/expected ratio [O/E] and regional multimetric indices [MMI]) among assemblages and between basin types (least-disturbed and developed). We used multiple-reach samples to evaluate discordance in site assessments of biological condition caused by sampling variability. Overall, patterns in variance partitioning were similar among assemblages and basin types with one exception. Among-site variance dominated the relative contribution to the total variance (64–80% of total variance), residual variance (sampling variance) accounted for more variability (8–26%) than interaction variance (5–12%), and among-year variance was always negligible (0–0.2%). The exception to this general pattern was for invertebrates at least-disturbed sites where variability in O/E indicators was partitioned between among-site and residual (sampling) variance (among-site = 36%, residual = 64%). This pattern was not observed for fish and diatom indicators (O/E and regional MMI). We suspect that unexplained sampling variability is what largely remained after the invertebrate indicators (O/E predictive models) had accounted for environmental differences among least-disturbed sites. The influence of sampling variability on discordance of within-site assessments was assemblage or basin-type specific. Discordance among assessments was nearly 2× greater in developed basins (29–31%) than in least-disturbed sites (15–16%) for invertebrates and diatoms, whereas discordance among assessments based on fish did not differ between basin types (least-disturbed = 16%, developed = 17%). Assessments made using invertebrate and diatom indicators from a single reach disagreed with other samples collected within the same stream segment nearly ⅓ of the time in developed basins, compared to ⅙ for all other cases.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Freshwater Science","doi":"10.1899/11-040.1","usgsCitation":"Zuellig, R.E., Carlisle, D.M., Meador, M., and Potapova, M., 2012, Variance partitioning of stream diatom, fish, and invertebrate indicators of biological condition: Freshwater Science, v. 31, no. 1, p. 182-190, https://doi.org/10.1899/11-040.1.","productDescription":"9 p.","startPage":"182","endPage":"190","ipdsId":"IP-011898","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":474107,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1899/11-040.1","text":"External Repository"},{"id":287130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287129,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1899/11-040.1"}],"country":"United States","volume":"31","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5374907ae4b0870f4d23d007","contributors":{"authors":[{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":470743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":470741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meador, Michael R. mrmeador@usgs.gov","contributorId":615,"corporation":false,"usgs":true,"family":"Meador","given":"Michael R.","email":"mrmeador@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":470742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Potapova, Marina","contributorId":89274,"corporation":false,"usgs":true,"family":"Potapova","given":"Marina","email":"","affiliations":[],"preferred":false,"id":470744,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042369,"text":"ofr20121248 - 2012 - Comparison of concentrations and profiles of polycyclic aromatic hydrocarbon metabolites in bile of fishes from offshore oil platforms and natural reefs along the California coast","interactions":[],"lastModifiedDate":"2013-01-06T12:06:29","indexId":"ofr20121248","displayToPublicDate":"2013-01-05T00:00:00","publicationYear":"2012","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":"2012-1248","title":"Comparison of concentrations and profiles of polycyclic aromatic hydrocarbon metabolites in bile of fishes from offshore oil platforms and natural reefs along the California coast","docAbstract":"To determine the environmental consequences of decommissioning offshore oil platforms on local and regional fish populations, contaminant loads in reproducing adults were investigated at seven platform sites and adjacent, natural sites. Specimens of three species (Pacific sanddab, Citharichthys sordidus; kelp rockfish, Sebastes atrovirens; and kelp bass, Paralabrax clathratus) residing at platforms and representing the regional background within the Santa Barbara Channel and within the San Pedro Basin were collected. Some of the most important contaminant classes related to oil operations are polycyclic aromatic hydrocarbons (PAHs) because of their potential toxicity and carcinogenicity. However, acute exposure cannot be related directly to PAH tissue concentrations because of rapid metabolism of the parent chemicals in fish; therefore, PAH metabolites in bile were measured, targeting free hydroxylated PAHs (OH-PAHs) liberated by enzymatic hydrolysis of the bound PAH glucuronides and sulfates. An ion-pairing method was developed for confirmatory analysis that targeted PAH glucuronides and sulfates. Concentrations of hydroxylated PAHs in all samples (76 fish from platforms and 64 fish from natural sites) were low, ranging from less than the limits of detection (5 to 120 nanograms per milliliter bile; 0.03 to 42 nanograms per milligram protein) to a maximum of 320 nanograms per milliliter bile (32 nanograms per milligram protein). A previously proposed dosimeter of PAH exposure in fish, 1-hydroxypyrene, was not detected at any platform site. Low concentrations of 1-hydroxypyrene were detected in 3 of 12 kelp rockfish collected from a natural reef site off Santa Barbara. The most prevalent OH-PAH, 2-hydroxyfluorene, was detected at low concentrations in seven fish of various species; of these, four were from two of the seven platform sites. The greatest concentrations of 2-hydroxyfluorene were found in three fish of various species from Platform Holly and were only about threefold above low, yet quantifiable, concentrations found in three fish from Horseshoe Reef, East Anacapa Island, and Coche Point natural sites; the mean concentrations among all sampling sites were not measurably different.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121248","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management","usgsCitation":"Gale, R.W., Tanner, M.J., Love, M., Nishimoto, M.M., and Schroeder, D.M., 2012, Comparison of concentrations and profiles of polycyclic aromatic hydrocarbon metabolites in bile of fishes from offshore oil platforms and natural reefs along the California coast: U.S. Geological Survey Open-File Report 2012-1248, Report: v, 27 p.; Supplemental Tables, https://doi.org/10.3133/ofr20121248.","productDescription":"Report: v, 27 p.; Supplemental Tables","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-029789","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":265300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1248.gif"},{"id":265297,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1248/"},{"id":265298,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1248/of2012-1248.pdf"},{"id":265299,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1248/downloads/supplemental_tables.xlsx"}],"country":"United States","state":"California","city":"Goleta;Long Beach;Santa Barbara","otherGeospatial":"Anacapa Island;Catalina Island;Santa Cruz Island;Southern California Bight","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0,33.58 ], [ -120.0,34.6 ], [ -117.9,34.6 ], [ -117.9,33.58 ], [ -120.0,33.58 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50eaab76e4b02dd6076fad9f","contributors":{"authors":[{"text":"Gale, Robert W. 0000-0002-8533-141X rgale@usgs.gov","orcid":"https://orcid.org/0000-0002-8533-141X","contributorId":2808,"corporation":false,"usgs":true,"family":"Gale","given":"Robert","email":"rgale@usgs.gov","middleInitial":"W.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":471391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanner, Michael J.","contributorId":55115,"corporation":false,"usgs":true,"family":"Tanner","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":471393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Love, Milton S.","contributorId":74652,"corporation":false,"usgs":true,"family":"Love","given":"Milton S.","affiliations":[],"preferred":false,"id":471395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nishimoto, Mary M.","contributorId":54083,"corporation":false,"usgs":true,"family":"Nishimoto","given":"Mary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schroeder, Donna M.","contributorId":67604,"corporation":false,"usgs":true,"family":"Schroeder","given":"Donna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471394,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042382,"text":"sir20105070F - 2012 - Occurrence model for volcanogenic beryllium deposits","interactions":[],"lastModifiedDate":"2022-04-22T20:13:40.290191","indexId":"sir20105070F","displayToPublicDate":"2013-01-05T00:00:00","publicationYear":"2012","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":"2010-5070","chapter":"F","title":"Occurrence model for volcanogenic beryllium deposits","docAbstract":"Current global and domestic mineral resources of beryllium (Be) for industrial uses are dominated by ores produced from deposits of the volcanogenic Be type. Beryllium deposits of this type can form where hydrothermal fluids interact with fluorine and lithophile-element (uranium, thorium, rubidium, lithium, beryllium, cesium, tantalum, rare earth elements, and tin) enriched volcanic rocks that contain a highly reactive lithic component, such as carbonate clasts. Volcanic and hypabyssal high-silica biotite-bearing topaz rhyolite constitutes the most well-recognized igneous suite associated with such Be deposits. The exemplar setting is an extensional tectonic environment, such as that characterized by the Basin and Range Province, where younger topaz-bearing igneous rock sequences overlie older dolomite, quartzite, shale, and limestone sequences. Mined deposits and related mineralized rocks at Spor Mountain, Utah, make up a unique economic deposit of volcanogenic Be having extensive production and proven and probable reserves. Proven reserves in Utah, as reported by the U.S. Geological Survey National Mineral Information Center, total about 15,900 tons of Be that are present in the mineral bertrandite (Be4Si2O7(OH)2). At the type locality for volcanogenic Be, Spor Mountain, the tuffaceous breccias and stratified tuffs that host the Be ore formed as a result of explosive volcanism that brought carbonate and other lithic fragments to the surface through vent structures that cut the underlying dolomitic Paleozoic sedimentary rock sequences. The tuffaceous sediments and lithic clasts are thought to make up phreatomagmatic base surge deposits. Hydrothermal fluids leached Be from volcanic glass in the tuff and redeposited the Be as bertrandite upon reaction of the hydrothermal fluid with carbonate clasts in lithic-rich sections of tuff. The localization of the deposits in tuff above fluorite-mineralized faults in carbonate rocks, together with isotopic evidence for the involvement of magmatic water in an otherwise meteoric water-dominated hydrothermal system, indicate that magmatic volatiles contributed to mineralization. At the type locality, hydrothermal alteration of dolomite clasts formed layered nodules of calcite, opal, fluorite, and bertrandite, the latter occurring finely intergrown with fluorite. Alteration assemblages and elemental enrichments in the tuff and surrounding volcanic rocks include regional diagenetic clays and potassium feldspar and distinctive hydrothermal halos of anomalous fluorine, lithium, molybdenum, niobium, tin, and tantalum, and intense potassium feldspathization with sericite and lithium-smectite in the immediate vicinity of Be ore. Formation of volcanogenic Be deposits is due to the coincidence of multiple factors that include an appropriate Be-bearing source rock, a subjacent pluton that supplied volatiles and heat to drive convection of meteoric groundwater, a depositional site characterized by the intersection of normal faults with permeable tuff below a less permeable cap rock, a fluorine-rich ore fluid that facilitated Be transport (for example, BeF42- complex), and the existence of a chemical trap that caused fluorite and bertrandite to precipitate at the former site of carbonate lithic clasts in the tuff.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070F","usgsCitation":"Foley, N.K., Hofstra, A.H., Lindsey, D.A., Seal, R., Jaskula, B.W., and Piatak, N., 2012, Occurrence model for volcanogenic beryllium deposits: U.S. Geological Survey Scientific Investigations Report 2010-5070, vi, 43 p., https://doi.org/10.3133/sir20105070F.","productDescription":"vi, 43 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":265312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5070_F.gif"},{"id":399523,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98030.htm"},{"id":265310,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/f/"},{"id":265311,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/f/SIR10-5070F.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50eaabf2e4b02dd6076fadb0","contributors":{"authors":[{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":471436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":471434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindsey, David A. 0000-0002-9466-0899 dlindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-9466-0899","contributorId":773,"corporation":false,"usgs":true,"family":"Lindsey","given":"David","email":"dlindsey@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":471433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":471432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaskula, Brian W. bjaskula@usgs.gov","contributorId":1935,"corporation":false,"usgs":true,"family":"Jaskula","given":"Brian","email":"bjaskula@usgs.gov","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":471435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piatak, Nadine M.","contributorId":23621,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine M.","affiliations":[],"preferred":false,"id":471437,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70042366,"text":"ofr20121261 - 2012 - Should ground-motion records be rotated to fault-normal/parallel or maximum direction for response history analysis of buildings?","interactions":[],"lastModifiedDate":"2013-01-06T12:07:11","indexId":"ofr20121261","displayToPublicDate":"2013-01-05T00:00:00","publicationYear":"2012","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":"2012-1261","title":"Should ground-motion records be rotated to fault-normal/parallel or maximum direction for response history analysis of buildings?","docAbstract":"In the United States, regulatory seismic codes (for example, California Building Code) require at least two sets of horizontal ground-motion components for three-dimensional (3D) response history analysis (RHA) of building structures. For sites within 5 kilometers (3.1 miles) of an active fault, these records should be rotated to fault-normal and fault-parallel (FN/FP) directions, and two RHAs should be performed separately—when FN and then FP direction are aligned with transverse direction of the building axes. This approach is assumed to lead to two sets of responses that envelope the range of possible responses over all nonredundant rotation angles. The validity of this assumption is examined here using 3D computer models of single-story structures having symmetric (torsionally stiff) and asymmetric (torsionally flexible) layouts subjected to an ensemble of near-fault ground motions with and without apparent velocity pulses. In this parametric study, the elastic vibration period is varied from 0.2 to 5 seconds, and yield-strength reduction factors, R, are varied from a value that leads to linear-elastic design to 3 and 5. Further validations are performed using 3D computer models of 9-story structures having symmetric and asymmetric layouts subjected to the same ground-motion set. The influence of the ground-motion rotation angle on several engineering demand parameters (EDPs) is examined in both linear-elastic and nonlinear-inelastic domains to form benchmarks for evaluating the use of the FN/FP directions and also the maximum direction (MD). The MD ground motion is a new definition for horizontal ground motions for use in site-specific ground-motion procedures for seismic design according to provisions of the American Society of Civil Engineers/Seismic Engineering Institute (ASCE/SEI) 7-10. The results of this study have important implications for current practice, suggesting that ground motions rotated to MD or FN/FP directions do not necessarily provide the most critical EDPs in nonlinear-inelastic domain; however, they tend to produce larger EDPs than as-recorded (arbitrarily oriented) motions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121261","usgsCitation":"Reyes, J.C., and Kalkan, E., 2012, Should ground-motion records be rotated to fault-normal/parallel or maximum direction for response history analysis of buildings?: U.S. Geological Survey Open-File Report 2012-1261, xii, 81 p., https://doi.org/10.3133/ofr20121261.","productDescription":"xii, 81 p.","numberOfPages":"93","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040285","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":265293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1261.gif"},{"id":265291,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1261/"},{"id":265292,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1261/of2012-1261.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50eaac31e4b02dd6076fadba","contributors":{"authors":[{"text":"Reyes, Juan C.","contributorId":30731,"corporation":false,"usgs":true,"family":"Reyes","given":"Juan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":471382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471381,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042372,"text":"ds709G - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:10:42","indexId":"ds709G","displayToPublicDate":"2013-01-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"G","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Zarkashan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Zarkashan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Zarkashan study area, three subareas were designated for detailed field investigations (that is, the Mine Area, Bolo Gold Prospect, and Luman-Tamaki Gold Prospect subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709G","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 37.63 x 40.38 inches; 10 Images; 10 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709G.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 37.63 x 40.38 inches; 10 Images; 10 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":265281,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/g/"},{"id":265283,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/Zarkashan_Area-of-Interest_Index_Map.pdf"},{"id":265282,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/g/1_readme.txt"},{"id":265284,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/Zarkashan_Image_Index_Map.pdf"},{"id":265285,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/index_maps.html"},{"id":265286,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/g/image_files/image_files.html"},{"id":265287,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/g/metadata/metadata.html"},{"id":265288,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/g/shapefiles/shapefiles.html"},{"id":265289,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","otherGeospatial":"Zarkashan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 67.0,32.5 ], [ 67.0,33.5 ], [ 68.0,33.5 ], [ 68.0,32.5 ], [ 67.0,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e7f9ede4b033ce2d2433ed","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":471402,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042381,"text":"sir20125272 - 2012 - The occurrence of trace elements in bed sediment collected from areas of varying land use and potential effects on stream macroinvertebrates in the conterminous western United States, Alaska, and Hawaii, 1992-2000","interactions":[],"lastModifiedDate":"2017-01-25T10:41:04","indexId":"sir20125272","displayToPublicDate":"2013-01-04T00:00:00","publicationYear":"2012","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":"2012-5272","title":"The occurrence of trace elements in bed sediment collected from areas of varying land use and potential effects on stream macroinvertebrates in the conterminous western United States, Alaska, and Hawaii, 1992-2000","docAbstract":"As part of the National Water-Quality Assessment Program of the U.S. Geological Survey, this study examines the occurrence of nine trace elements in bed sediment of varying mineralogy and land use and assesses the possible effects of these trace elements on aquatic-macroinvertebrate community structure. Samples of bed sediment and macroinvertebrates were collected from 154 streams at sites representative of undeveloped, agricultural, urban, mined, or mixed land-use areas and 12 intermediate-scale ecoregions within the conterminous western United States, Alaska, and Hawaii from 1992 to 2000. The nine trace elements evaluated during this study—arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn)—were selected on the basis of potential ecologic significance and availability of sediment-quality guidelines. At most sites, the occurrence of these trace elements in bed sediment was at concentrations consistent with natural geochemical abundance, and the lowest concentrations were in bed-sediment samples collected from streams in undeveloped and agricultural areas. With the exception of Zn at sampling sites influenced by historic mining-related activities, median concentrations of all nine trace elements in bed sediment collected from sites representative of the five general land-use areas were below concentrations predicted to be harmful to aquatic macroinvertebrates. The highest concentrations of As, Cd, Pb, and Zn were in bed sediment collected from mined areas. Median concentrations of Cu and Ni in bed sediment were similarly enriched in areas of mining, urban, and mixed land use. Concentrations of Cr and Ni appear to originate largely from geologic sources, especially in the western coastal states (California, Oregon, and Washington), Alaska, and Hawaii. In these areas, naturally high concentrations of Cr and Ni can exceed concentrations that may adversely affect aquatic macroinvertebrates. Generally, Hg concentrations were below the sediment-quality guideline for this trace element but appeared elevated in urbanized areas and at sites contaminated by historic mining practices. Lastly, although there was no distinctive pattern in Se concentrations with land use, median bed-sediment concentrations were slightly elevated in urbanized areas.
Macroinvertebrate community structure was influenced by topographic, geologic, climatic, and in-stream characteristics. To account for inherent distribution patterns resulting from these influences, samples of macroinvertebrates were stratified by ecoregion to assess the influence of trace elements on community structure. Cumulative toxic units (CTUs) were used to evaluate gradients in trace-element concentrations in mixture. Correlation analyses among the trace elements under different land-use conditions indicate that trace-element mixtures vary among bed sediment and can have a marked influence on CTU composition. Macroinvertebrate response to bed-sediment trace-element exposure was evident only at the most highly contaminated sites, notably at sites classified as contaminated by the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) as a result of historic mining activities. Results of this study agree with the findings of other studies evaluating trace-element exposure to in-stream macroinvertebrate community structure in that generally lower richness metrics and taxa dominance occur in streams where high trace-element enrichment occurs; however, not all streams in all areas have the same characterizing taxa. In the mountain and xeric ecosystems, the mayfly, Baetis sp.; the Diptera, Simulium sp.; caddisflies in the family Hydropsychiidae; midges in the family Orthocladiinae; and the worms belonging to Turbellaria and Naididae all demonstrated resilience to trace-element exposure and, in some cases, possible changes in physical habitat within stream ecosystems. The taxa characteristics within the Ozark Highland ecoregion were different than other ecoregions as evidenced by generally more diverse mayfly populations. In addition, Baetis sp. was common and dominated many of the mayfly populations found in the Rocky Mountain streams within the Mountain Southern Rockies and Mountain Northern Rockies ecoregions; however, within the Ozark Highland ecoregion, Tricorythodes sp. appeared to be more common than Baetis sp.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125272","usgsCitation":"Paul, A.P., Paretti, N., MacCoy, D.E., and Brasher, A., 2012, The occurrence of trace elements in bed sediment collected from areas of varying land use and potential effects on stream macroinvertebrates in the conterminous western United States, Alaska, and Hawaii, 1992-2000: U.S. Geological Survey Scientific Investigations Report 2012-5272, Report: viii, 64 p.; Appendixes, https://doi.org/10.3133/sir20125272.","productDescription":"Report: viii, 64 p.; Appendixes","numberOfPages":"76","additionalOnlineFiles":"N","temporalStart":"1992-01-01","temporalEnd":"2000-12-31","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science 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demaccoy@usgs.gov","orcid":"https://orcid.org/0000-0001-6810-4728","contributorId":948,"corporation":false,"usgs":true,"family":"MacCoy","given":"Dorene","email":"demaccoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brasher, Anne M.D.","contributorId":33686,"corporation":false,"usgs":true,"family":"Brasher","given":"Anne M.D.","affiliations":[],"preferred":false,"id":471431,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042337,"text":"ds736 - 2012 - Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley","interactions":[],"lastModifiedDate":"2017-05-24T12:54:21","indexId":"ds736","displayToPublicDate":"2013-01-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"736","title":"Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley","docAbstract":"The Land Capacity Potential Index (LCPI) is a coarse-scale index intended to delineate broad land-capability classes in the Lower Missouri River valley bottom from the Gavins Point Dam near Yankton, South Dakota to the mouth of the Missouri River near St. Louis, Missouri (river miles 811–0). The LCPI provides a systematic index of wetness potential and soil moisture-retention potential of the valley-bottom lands by combining the interactions among water-surface elevations, land-surface elevations, and the inherent moisture-retention capability of soils. A nine-class wetness index was generated by intersecting a digital elevation model for the valley bottom with sloping water-surface elevation planes derived from eight modeled discharges. The flow-recurrence index was then intersected with eight soil-drainage classes assigned to soils units in the digital Soil Survey Geographic (SSURGO) Database (Soil Survey Staff, 2010) to create a 72-class index of potential flow-recurrence and moisture-retention capability of Missouri River valley-bottom lands. The LCPI integrates the fundamental abiotic factors that determine long-term suitability of land for various uses, particularly those relating to vegetative communities and their associated values. Therefore, the LCPI provides a mechanism allowing planners, land managers, landowners, and other stakeholders to assess land-use capability based on the physical properties of the land, in order to guide future land-management decisions. This report documents data compilation for the LCPI in a revised and expanded, 72-class version for the Lower Missouri River valley bottom, and inclusion of additional soil attributes to allow users flexibility in exploring land capabilities.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds736","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, Nebraska Game and Parks Commission, and the Nature Conservancy","usgsCitation":"Chojnacki, K.A., Struckhoff, M.A., and Jacobson, R.B., 2012, Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley: U.S. Geological Survey Data Series 736, Report: iv, 18 p.; Downloads Directory, https://doi.org/10.3133/ds736.","productDescription":"Report: iv, 18 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-037780","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":265277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_736.gif"},{"id":265276,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/736/downloads/"},{"id":265274,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/736/"},{"id":265275,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/736/ds736.pdf"}],"scale":"2000000","datum":"North American Datum 1983","country":"United States","state":"Iowa, Kansas, Missouri, Nebraska, South Dakota","otherGeospatial":"Missouri River Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.0,38.0 ], [ -98.0,43.5 ], [ -90.0,43.5 ], [ -90.0,38.0 ], [ -98.0,38.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e7f9ebe4b033ce2d2433e9","contributors":{"authors":[{"text":"Chojnacki, Kimberly A. kchojnacki@usgs.gov","contributorId":1978,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Kimberly","email":"kchojnacki@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":471329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struckhoff, Matthew A. 0000-0002-4911-9956 mstruckhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":2095,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","email":"mstruckhoff@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":471330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":471328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042285,"text":"70042285 - 2012 - Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models","interactions":[],"lastModifiedDate":"2013-01-03T10:10:08","indexId":"70042285","displayToPublicDate":"2013-01-03T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models","docAbstract":"1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.2041-210X.2012.00241.x","usgsCitation":"Gopalaswamy, A., Royle, J., Hines, J., Singh, P., Jathanna, D., Kumar, N.S., and Karanth, K.U., 2012, Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models: Methods in Ecology and Evolution, v. 3, no. 6, p. 1067-1072, https://doi.org/10.1111/j.2041-210X.2012.00241.x.","productDescription":"6 p.","startPage":"1067","endPage":"1072","ipdsId":"IP-039292","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2012.00241.x","text":"Publisher Index Page"},{"id":265030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":265029,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.2041-210X.2012.00241.x"}],"volume":"3","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-09-17","publicationStatus":"PW","scienceBaseUri":"50e5d023e4b0a4aa5bb0af86","contributors":{"authors":[{"text":"Gopalaswamy, Arjun M.","contributorId":12167,"corporation":false,"usgs":true,"family":"Gopalaswamy","given":"Arjun M.","affiliations":[],"preferred":false,"id":471203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. 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Ullas","contributorId":6984,"corporation":false,"usgs":true,"family":"Karanth","given":"K.","email":"","middleInitial":"Ullas","affiliations":[],"preferred":false,"id":471202,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70042281,"text":"70042281 - 2012 - Density estimation in tiger populations: combining information for strong inference","interactions":[],"lastModifiedDate":"2013-01-02T12:03:14","indexId":"70042281","displayToPublicDate":"2013-01-02T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Density estimation in tiger populations: combining information for strong inference","docAbstract":"A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture–recapture data. The model, which combined information, provided the most precise estimate of density (8.5 ± 1.95 tigers/100 km2 [posterior mean ± SD]) relative to a model that utilized only one data source (photographic, 12.02 ± 3.02 tigers/100 km2 and fecal DNA, 6.65 ± 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ESA","publisherLocation":"Ithaca, NY","doi":"10.1890/11-2110.1","usgsCitation":"Gopalaswamy, A., Royle, J., Delampady, M., Nichols, J., Karanth, K.U., and Macdonald, D.W., 2012, Density estimation in tiger populations: combining information for strong inference: Ecology, v. 93, no. 7, p. 1741-1751, https://doi.org/10.1890/11-2110.1.","productDescription":"11 p.","startPage":"1741","endPage":"1751","ipdsId":"IP-039030","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":265020,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-2110.1"},{"id":265021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfefe4b0a4aa5bb0aebb","contributors":{"authors":[{"text":"Gopalaswamy, Arjun M.","contributorId":12167,"corporation":false,"usgs":true,"family":"Gopalaswamy","given":"Arjun M.","affiliations":[],"preferred":false,"id":471186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. 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