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,{"id":70007324,"text":"ds632 - 2012 - Water chemistry and electrical conductivity database for rivers in Yellowstone National Park, Wyoming","interactions":[],"lastModifiedDate":"2019-05-30T16:18:46","indexId":"ds632","displayToPublicDate":"2012-02-08T10:34:00","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":"632","title":"Water chemistry and electrical conductivity database for rivers in Yellowstone National Park, Wyoming","docAbstract":"<p>Chloride flux has been used to estimate heat flow in volcanic environments since the method was developed in New Zealand by Ellis and Wilson (1955). The method can be applied effectively at Yellowstone, because nearly all of the water discharged from its thermal features enters one of four major rivers (the Madison, Yellowstone, Snake, and Falls Rivers) that drain the park, and thus integration of chloride fluxes from all these rivers provides a means to monitor the total heat flow from the entire Yellowstone volcanic system (Fournier and others, 1976; Fournier, 1979). Fournier (1989) summarized the results and longterm heat-flow trends from Yellowstone, and later efforts that applied the chloride inventory method to estimate heat flow were described by Ingebritsen and others (2001) and Friedman and Norton (2007). Most recently, the U.S. Geological Survey (USGS), in conjunction with the National Park Service, has provided publicly accessible reports on solute flux, based on periodic sampling at selected locations (Hurwitz and others, 2007a,b). While these studies have provided a wealth of valuable data, winter travel restrictions and the great distances between sites present significant logistical challenges and have limited collection to a maximum of 28 samples per site annually.</p>\n<p>This study aims to quantify relations between solute concentrations (especially chloride) and electrical conductivity for several rivers in Yellowstone National Park (YNP), by using automated samplers and conductivity meters. Norton and Friedman (1985) found that chloride concentrations and electrical conductivity have a good correlation in the Falls, Snake, Madison, and Yellowstone Rivers. However, their results are based on limited sampling and hydrologic conditions and their relation with other solutes was not determined. Once the correlations are established, conductivity measurements can then be used as a proxy for chloride concentrations, thereby enabling continuous heat-flow estimation on a much finer timescale and at lower cost than is currently possible with direct sampling. This publication serves as a repository for all data collected during the course of the study from May 2010 through July 2011, but it does not include correlations between solutes and conductivity or recommendations for quantification of chloride through continuous electrical conductivity measurements. This will be the object of a future document.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reson, VA","doi":"10.3133/ds632","collaboration":"In cooperation with the National Park Service","usgsCitation":"Clor, L.E., McCleskey, R.B., Huebner, M., Lowenstern, J.B., Heasler, H.P., Mahony, D.L., Maloney, T., and Evans, W.C., 2012, Water chemistry and electrical conductivity database for rivers in Yellowstone National Park, Wyoming: U.S. Geological Survey Data Series 632, Report: iv, 6 p., https://doi.org/10.3133/ds632.","productDescription":"Report: iv, 6 p.","onlineOnly":"Y","temporalStart":"2010-05-01","temporalEnd":"2011-07-31","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":686,"text":"Yellowstone Volcano Observatory","active":false,"usgs":true}],"links":[{"id":116459,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_632.gif"},{"id":115782,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/632/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.16666666666667,44.083333333333336 ], [ -111.16666666666667,45.166666666666664 ], [ -109.75,45.166666666666664 ], [ -109.75,44.083333333333336 ], [ -111.16666666666667,44.083333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc7cee4b08c986b32c630","contributors":{"authors":[{"text":"Clor, Laura E.","contributorId":94749,"corporation":false,"usgs":true,"family":"Clor","given":"Laura","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":356257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huebner, Mark A.","contributorId":27902,"corporation":false,"usgs":true,"family":"Huebner","given":"Mark A.","affiliations":[],"preferred":false,"id":356260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":356259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heasler, Henry P.","contributorId":65935,"corporation":false,"usgs":true,"family":"Heasler","given":"Henry","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":356262,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahony, Dan L.","contributorId":43911,"corporation":false,"usgs":true,"family":"Mahony","given":"Dan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":356261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maloney, Tim","contributorId":70537,"corporation":false,"usgs":true,"family":"Maloney","given":"Tim","email":"","affiliations":[],"preferred":false,"id":356263,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":356258,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70168416,"text":"70168416 - 2012 - Spatial and temporal diet patterns of subadult and small adult striped bass in Massachusetts estuaries: Data, a synthesis, and trends across scales","interactions":[],"lastModifiedDate":"2016-02-12T12:01:27","indexId":"70168416","displayToPublicDate":"2012-02-07T13:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal diet patterns of subadult and small adult striped bass in Massachusetts estuaries: Data, a synthesis, and trends across scales","docAbstract":"<p>Subadult and small adult (375&ndash;475 mm total length) striped bass <i>Morone saxatilis</i> are abundant and represent an important component of the recovered U.S. Atlantic coast stocks. However, little is known about these large aggregations of striped bass during their annual foraging migrations to New England. A quantitative understanding of trends in the diets of subadult and small adult migrants is critical to research and management. Because of the complexity of the Massachusetts coast, we were able to compare diets at multiple spatial, temporal, and taxonomic scales and evaluate which of these provided the greatest insights into the foraging patterns of this size of fish. Specifically, during spring through autumn, we quantified the diets of 797 migratory striped bass collected from 13 Massachusetts estuaries distributed among three geographic regions in two biogeographic provinces. Our data provided three useful results. First, subadult and young adult striped bass ate a season-specific mixture of fish and invertebrates. For example, more juvenile Atlantic herring <i>Clupea harengus</i> were eaten in spring than in summer or autumn, more juvenile Atlantic menhaden <i>Brevoortia tyrannus</i> were eaten in autumn than in spring or summer, amphipods were eaten primarily in the southern biogeographic province, and shrimp <i>Crangon</i> sp. were eaten in all locations and seasons. Second, examining diets by season was essential because of the temporal variability in striped bass prey. Grouping prey by fish and invertebrates revealed the potential for predictable differences in growth across geographic locations and seasons, based on the output from simple bioenergetics simulations. Third, of the three spatial scales examined, region provided the most quantitative and interpretable ecological trends. Our results demonstrate the utility of comparing multiple scales to evaluate the best way to depict diet trends in a migrating predator that seasonally uses different geographic locations.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/19425120.2011.642747","usgsCitation":"Ferry, K., and Mather, M.E., 2012, Spatial and temporal diet patterns of subadult and small adult striped bass in Massachusetts estuaries: Data, a synthesis, and trends across scales: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 4, no. 1, p. 30-45, https://doi.org/10.1080/19425120.2011.642747.","productDescription":"16 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,{"id":70007323,"text":"sir20115153 - 2012 - Quality of major ion and total dissolved solids data from groundwater sampled by the National Water-Quality Assessment Program, 1992&ndash;2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115153","displayToPublicDate":"2012-02-03T10:16:00","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":"2011-5153","title":"Quality of major ion and total dissolved solids data from groundwater sampled by the National Water-Quality Assessment Program, 1992&ndash;2010","docAbstract":"<p>Proper interpretation of water quality requires consideration of the effects that contamination bias and sampling variability might have on measured analyte concentrations. The effect of contamination bias and sampling variability on major ion and total dissolved solids data in water samples collected in 48 of the 52 National Water-Quality Assessment Program study units from 1992&ndash;2010 is discussed in this report. Contamination bias and sampling variability can occur as a result of sample collection, processing, shipping, and analysis. Contamination bias can adversely affect interpretation of measured concentrations in comparison to standards or criteria. Sampling variability can help determine the reproducibility of an individual measurement or whether two measurements are different.</p>\n<p>Field blank samples help determine the frequency and magnitude of contamination bias, and replicate samples help determine the sampling variability (error) of measured analyte concentrations. Quality control data were evaluated for calcium, magnesium, sodium, potassium, chloride, sulfate, fluoride, silica, and total dissolved solids. A 99-percent upper confidence limit is calculated from field blanks to assess the potential for contamination bias. For magnesium, potassium, chloride, sulfate, and fluoride, potential contamination in more than 95 percent of environmental samples is less than or equal to the common maximum reporting level. Contamination bias has little effect on measured concentrations greater than 4.74 mg/L (milligrams per liter) for calcium, 14.98 mg/L for silica, 4.9 mg/L for sodium, and 120 mg/L for total dissolved solids. Estimates of sampling variability are calculated for high and low ranges of concentration for major ions and total dissolved solids. Examples showing the calculation of confidence intervals and how to determine whether measured differences between two water samples are significant are presented.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115153","collaboration":"Prepared in cooperation with the National Water-Quality Assessment Program","usgsCitation":"Gross, E.L., Lindsey, B., and Rupert, M.G., 2012, Quality of major ion and total dissolved solids data from groundwater sampled by the National Water-Quality Assessment Program, 1992&ndash;2010: U.S. Geological Survey Scientific Investigations Report 2011-5153, vi, 26 p., https://doi.org/10.3133/sir20115153.","productDescription":"vi, 26 p.","onlineOnly":"Y","temporalStart":"1992-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":116458,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5153.png"},{"id":115781,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5153/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a90bce4b0c8380cd7fee1","contributors":{"authors":[{"text":"Gross, Eliza L. 0000-0002-8835-3382 egross@usgs.gov","orcid":"https://orcid.org/0000-0002-8835-3382","contributorId":430,"corporation":false,"usgs":true,"family":"Gross","given":"Eliza","email":"egross@usgs.gov","middleInitial":"L.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":434,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce D.","email":"blindsey@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":356255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rupert, Michael G. mgrupert@usgs.gov","contributorId":1194,"corporation":false,"usgs":true,"family":"Rupert","given":"Michael","email":"mgrupert@usgs.gov","middleInitial":"G.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356256,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70007288,"text":"ofr20111280 - 2012 - Preliminary assessment of channel stability and bed-material transport in the Rogue River basin, southwestern Oregon","interactions":[],"lastModifiedDate":"2019-04-25T10:21:52","indexId":"ofr20111280","displayToPublicDate":"2012-02-02T00:00:00","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":"2011-1280","title":"Preliminary assessment of channel stability and bed-material transport in the Rogue River basin, southwestern Oregon","docAbstract":"<p>This report summarizes a preliminary assessment of bed-material transport, vertical and lateral channel changes, and existing datasets for the Rogue River basin, which encompasses 13,390 square kilometers (km<sup>2</sup>) along the southwestern Oregon coast. This study, conducted to inform permitting decisions regarding instream gravel mining, revealed that:</p><ul><li>The Rogue River in its lowermost 178.5 kilometers (km) alternates between confined and unconfined segments, and is predominately alluvial along its lowermost 44 km. The study area on the mainstem Rogue River can be divided into five reaches based on topography, hydrology, and tidal influence. The largely confined, active channel flows over bedrock and coarse bed material composed chiefly of boulders and cobbles in the Grants Pass (river kilometers [RKM] 178.5–152.8), Merlin (RKM 152.8–132.7), and Galice Reaches (RKM 132.7–43.9). Within these confined reaches, the channel contains few bars and has stable planforms except for locally wider segments such as the Brushy Chutes area in the Merlin Reach. Conversely, the active channel flows over predominately alluvial material and contains nearly continuous gravel bars in the Lobster Creek Reach (RKM 43.9–6.7). The channel in the Tidal Reach (RKM 6.7–0) is also alluvial, but tidally affected and unconfined until RKM 2. The Lobster Creek and Tidal Reaches contain some of the most extensive bar deposits within the Rogue River study area.</li><li>For the 56.6-km-long segment of the Applegate River included in this study, the river was divided into two reaches based on topography. In the Upper Applegate River Reach (RKM 56.6–41.6), the confined, active channel flows over alluvium and bedrock and has few bars. In the Lower Applegate River Reach (RKM 41.6–0), the active channel alternates between confined and unconfined segments, flows predominantly over alluvium, shifts laterally in unconfined sections, and contains more numerous and larger bars.</li><li>The 6.5-km segment of the lower Illinois River included in this study was treated as one reach. This stretch of the Illinois River is fully alluvial, with nearly continuous gravel bars flanking the channel. The width of the active channel is confined by the narrow topography of the valley.</li><li>The primary human activities that have likely influenced channel condition, bed-material transport, and the extent and area of bars are (1) historical gold mining throughout the basin, (2) historical and ongoing gravel mining from instream sites in the Tidal Reach and floodplain sites such as those in the Lower Applegate River Reach, (3) hydropower and flow control structures, (4) forest management and fires throughout the basin, and (5) dredging. These anthropogenic activities likely have varying effects on channel condition and the transport and deposition of sediment throughout the study area and over time.</li><li>Several vertical (aspect) aerial photographs (including the complete coverages of the study area taken in 1995, 2000, 2005, and 2009 and the partial coverages taken in 1967, 1968, 1969, and 1990) are available for assessing long-term changes in attributes such as channel condition, bar area, and vegetation cover. A Light Detection And Ranging (LiDAR) survey performed in 2007–2008 provides 1-m resolution topographic data for sections of the Grants Pass (RKM 178.5–167.6) and Lobster Creek (RKM 17.8–12 and 10–6.7) Reaches and the entire Tidal Reach.</li><li>Previous studies provide information for specific locations, including (1) an estimated average annual bed-material load of 76,000 m<sup>3</sup><span>&nbsp;</span>at the former Savage Rapids Dam site (RKM 173.1, Grants Pass Reach), (2) over 490 m of channel shifting from 1965 to 1991 in the Brushy Chutes area (RKM 142–141, Merlin Reach), (3) active sediment transport and channel processes in the Lobster Creek Reach, (4) lateral channel migration in the Tidal Reach, and (5) up to 1.8 m of bar aggradation from the town of Agness (RKM 45.1) to the Rogue River mouth following the flood in water year 1997.</li><li>Review of the repeat surveys conducted at the instream gravel-mining sites on Elephant and Wedderburn Bars tentatively indicated that these bars (1) experience some bed-material deposition in most years and more substantial deposition following high flows such as those in water years 1997 and 2006, and (2) are dynamic and subject to local scour and deposition.</li><li>Results from the specific gage analyses completed for five long-term USGS streamflow-gaging stations showed that only the Grants Pass station on the Rogue River (RKM 164.4, Grants Pass Reach) experienced substantial changes in the stage–discharge relationship across a range of flows from 1938 to 2009. Observed changes indicate channel incision at this site.</li><li>The Rogue and Applegate Rivers are dynamic and subject to channel shifting, aggradation, and incision, as indicated by channel cross sections surveyed during 2000–2010 on the Rogue River and 1933–2010 on the Applegate River. The elevation of the riverbed changed substantially (defined here as more than a net 0.5 m of incision or aggradation) at three locations on the Rogue River (near RKM 164.5, 139.2, and 1.3) and two on the Applegate River (near RKM 42 and 13.5).</li><li>Systematic delineation of bar features from vertical photographs taken in 1967–69, 2005, and 2009 indicated that most of the repeat mapping sites had a net loss in bar area over the analysis period, ranging from 22 percent at the Oak Flat site (Illinois River Reach) to 69 percent at the Thompson Creek site (Upper Applegate River Reach). Bar area remained stable at the Williams Creek site (Lower Applegate River Reach), but increased 11 percent at the Elephant Rock site (Tidal Reach). The declines in bar area were associated primarily with the establishment of vegetation on upper bar surfaces lacking obvious vegetation in the 1960s. Some of the apparent changes in bar area may also owe to some differences in streamflow and tide levels between the vertical photographs.</li><li>On the mainstem Rogue River, the median diameter of surface particles varied from 21 mm at the Wedderburn Bar in the Tidal Reach to more than 100 millimeters (mm) at some of the coarsest bars in the Galice Reach. Low armoring ratios tentatively indicated that sediment supply likely exceeds transport capacity at Orchard (Lobster Creek Reach) and Wedderburn (Tidal Reach) Bars. Conversely, relatively higher armoring ratios indicated that transport capacity likely is in balance with sediment supply at Roberston Bridge Bar (Merlin Reach) and exceeds sediment supply at Rogue River City (Grants Pass Reach), Solitude Riffle (Galice Reach), and Hooks Gulch (Galice Reach) Bars.</li><li>Limited particle data were collected in the study areas on the Applegate and Illinois Rivers. Particle size measurements and armoring ratios tentatively show that sediment supply likely exceeds transport capacity at Bakery Bar in the Lower Applegate Reach. Also, the bed material exiting the Applegate River is likely finer than the bed material in the Rogue River, whereas bed material exiting the Illinois River is likely coarser than the bed material in the Rogue River.</li><li>Together, these observations and findings indicate that (1) the size, area, and overall position of bars in the Rogue River study area are determined largely by valley physiography, such that unconfined alluvial sections have large channel-flanking bars, whereas confined sections have fewer and smaller bars, (2) segments within the Grants Pass, Merlin, Tidal, Upper Applegate River, and Lower Applegate River Reaches are prone to vertical and/or lateral channel adjustments, and (3) the balance between transport capacity and sediment supply varies throughout the study area.</li><li>High winter flows and the steep, confined character of much of the Rogue River within the study area result in a river corridor with a high capacity to transport bed material. In the Grants Pass and Galice Reaches, the extensive in-channel bedrock as well as the sparse number and coarse texture of bars indicate that these reaches are likely supply-limited, meaning that the river’s transport capacity exceeds the supply of bed material. In contrast, the Lobster Creek and Tidal Reaches and perhaps portions of the Merlin Reach receive bed-material inputs that more closely balance or even exceed the river’s transport capacity.</li><li>The lowermost reaches on the Illinois and Applegate Rivers are fully alluvial segments that are likely transport limited, meaning sediment supply likely exceeds the river's transport capacity. However, the steeper Upper Applegate River Reach is likely supply-limited as indicated by the sparse number and area of bars mapped in this reach and the intermittent bedrock outcrops in the channel. The sediment loads derived from these large tributaries draining the Klamath Mountains are probably important contributions to the overall transport of bed material in the Rogue River basin.</li><li>Compared to the slightly smaller Umpqua River basin (drainage area 12,103 km<sup>2</sup>) to the north, the Rogue River (13,390 km<sup>2</sup>) likely transports more bed material. Although this conclusion of greater bed-material transport in the Rogue River is tentative in the absence of either actual transport measurements or transport capacity calculations, empirical evidence, including the much greater area and frequency of bars along most of the Rogue River as well as the much shorter tidal reach on the Rogue River (6.7 km) compared to the Umpqua River (40 km) supports this inference.</li><li>More detailed investigations of bed-material transport rates and channel morphology would support assessments of channel condition, longitudinal trends in particle size, the relation between sediment supply and transport capacity, and the potential causes of bar area loss (such as vegetation establishment and potential changes in peak flow patterns). The reaches most practical for such assessments and relevant to several management and ecological issues are (1) the lower Rogue River basin, including the Lobster Creek and Tidal Reaches of the Rogue River as well as the Illinois River Reach and (2) the Lower Applegate River Reach.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111280","usgsCitation":"Jones, K.L., O'Connor, J., Keith, M., Mangano, J.F., and Wallick, J., 2012, Preliminary assessment of channel stability and bed-material transport in the Rogue River basin, southwestern Oregon: U.S. Geological Survey Open-File Report 2011-1280, viii, 96 p., https://doi.org/10.3133/ofr20111280.","productDescription":"viii, 96 p.","numberOfPages":"107","onlineOnly":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":116813,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1280.jpg"},{"id":115765,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1280/","linkFileType":{"id":5,"text":"html"}}],"projection":"UTM, Zone 10N","datum":"North American Datum 1983","country":"United States","state":"Oregon","county":"Jackson county, Josephine county","otherGeospatial":"Rogue River Basin, Applegate River, llinois River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.75,42 ], [ -124.75,43.25 ], [ -122,43.25 ], [ -122,42 ], [ -124.75,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a82e5e4b0c8380cd7bcd7","contributors":{"authors":[{"text":"Jones, Krista L. 0000-0002-0301-4497 kljones@usgs.gov","orcid":"https://orcid.org/0000-0002-0301-4497","contributorId":4550,"corporation":false,"usgs":true,"family":"Jones","given":"Krista","email":"kljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":356242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Mackenzie K.","contributorId":16560,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie K.","affiliations":[],"preferred":false,"id":356241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mangano, Joseph F. 0000-0003-4213-8406 jmangano@usgs.gov","orcid":"https://orcid.org/0000-0003-4213-8406","contributorId":4722,"corporation":false,"usgs":true,"family":"Mangano","given":"Joseph","email":"jmangano@usgs.gov","middleInitial":"F.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356238,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70007279,"text":"ds606 - 2012 - Diversity and distribution of mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera) of the South Platte River Basin, Colorado, Nebraska, and Wyoming, 1873-2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds606","displayToPublicDate":"2012-02-02T00:00:00","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":"606","title":"Diversity and distribution of mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera) of the South Platte River Basin, Colorado, Nebraska, and Wyoming, 1873-2010","docAbstract":"The U.S. Geological Survey, in cooperation with the C.P. Gillette Museum of Arthropod Diversity (Colorado State University, Fort Collins, Colorado), compiled collection record data to document the historical and present-day occurrence of mayfly, stonefly, and caddisfly species in the South Platte River Basin. Data were compiled from records collected between 1873 and 2010 to identify where regional knowledge about species occurrence in the basin is lacking and to encourage future researchers to locate additional populations of these poorly understood but very important organisms. This report provides a description of how data were compiled, a map of approximate collection locations, a listing of the most recent collection records from unique locations, general remarks for each species, a species list with selected summary information, and distribution maps of species collection records.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds606","collaboration":"Prepared in cooperation with the C.P. Gillette Museum of Arthropod Diversity","usgsCitation":"Zuellig, R.E., Heinold, B.D., Kondratieff, B.C., and Ruiter, D.E., 2012, Diversity and distribution of mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera) of the South Platte River Basin, Colorado, Nebraska, and Wyoming, 1873-2010: U.S. Geological Survey Data Series 606, vii, 109 p.; Appendix, https://doi.org/10.3133/ds606.","productDescription":"vii, 109 p.; Appendix","onlineOnly":"Y","temporalStart":"1873-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":116810,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_606.png"},{"id":115761,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/606/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Albers Equal Area","country":"United States","state":"Colorado;Nebraska;Wyoming","otherGeospatial":"South Platte River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106,38.5 ], [ -106,42 ], [ -100.5,42 ], [ -100.5,38.5 ], [ -106,38.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a034fe4b0c8380cd5040f","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":356216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heinold, Brian D.","contributorId":11067,"corporation":false,"usgs":true,"family":"Heinold","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":356217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kondratieff, Boris C.","contributorId":24868,"corporation":false,"usgs":false,"family":"Kondratieff","given":"Boris","email":"","middleInitial":"C.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":356218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruiter, David E.","contributorId":37835,"corporation":false,"usgs":true,"family":"Ruiter","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356219,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70007282,"text":"ofr20121023 - 2012 - Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0","interactions":[],"lastModifiedDate":"2012-02-03T00:10:05","indexId":"ofr20121023","displayToPublicDate":"2012-02-02T00:00:00","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":"2012-1023","title":"Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0","docAbstract":"In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center (RMGSC), in collaboration with Colorado State University, developed a geographic information system (GIS) application, Social Values for Ecosystem Services (SolVES). With version 2.0 (SolVES 2.0), RMGSC has improved and extended the functionality of SolVES, which was designed to assess, map, and quantify the perceived social values of ecosystem services. Social values such as aesthetics, biodiversity, and recreation can be evaluated for various stakeholder groups as distinguished by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with the previous version, SolVES 2.0 derives a quantitative, 10-point, social-values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys and calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. Additionally, SolVES 2.0 integrates Maxent maximum entropy modeling software to generate more complete social value maps and to produce robust statistical models describing the relationship between the social values maps and explanatory environmental variables. The performance of these models can be evaluated for a primary study area, as well as for similar areas where primary survey data are not available but where social value mapping could potentially be completed using value-transfer methodology. SolVES 2.0 also introduces the flexibility for users to define their own social values and public uses, model any number and type of environmental variable, and modify the spatial resolution of analysis. With these enhancements, SolVES 2.0 provides an improved public domain tool for decisionmakers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among different ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121023","collaboration":"Geographic Analysis and Monitoring Program, in collaboration with Colorado State University","usgsCitation":"Sherrouse, B.C., and Semmens, D.J., 2012, Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0: U.S. Geological Survey Open-File Report 2012-1023, vi, 55 p.; Downloadable GIS - SolVES 2.0, https://doi.org/10.3133/ofr20121023.","productDescription":"vi, 55 p.; Downloadable GIS - SolVES 2.0","onlineOnly":"Y","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":116812,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1023.png"},{"id":115764,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1023/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b91c7e4b08c986b319acb","contributors":{"authors":[{"text":"Sherrouse, Benson C.","contributorId":37831,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":356231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":356230,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70116322,"text":"70116322 - 2012 - Genetic diversity of a newly established population of golden eagles on the Channel Islands, California","interactions":[],"lastModifiedDate":"2018-08-20T18:13:01","indexId":"70116322","displayToPublicDate":"2012-02-01T14:10:38","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity of a newly established population of golden eagles on the Channel Islands, California","docAbstract":"Gene flow can have profound effects on the genetic diversity of a founding population depending on the number and relationship among colonizers and the duration of the colonization event. Here we used data from nuclear microsatellite and mitochondrial DNA control region loci to assess genetic diversity in golden eagles of the recently colonized Channel Islands, California. Genetic diversity in the Channel Island population was low, similar to signatures observed for other recent colonizing island populations. Differences in levels of genetic diversity and structure observed between mainland California and the islands suggests that few individuals were involved in the initial founding event, and may have comprised a family group. The spatial genetic structure observed between Channel Island and mainland California golden eagle populations across marker types, and genetic signature of population decline observed for the Channel Island population, suggest a single or relatively quick colonization event. Polarity in gene flow estimates based on mtDNA confirm an initial colonization of the Channel Islands by mainland golden eagles, but estimates from microsatellite data suggest that golden eagles on the islands were dispersing more recently to the mainland, possibly after reaching the carrying capacity of the island system. These results illustrate the strength of founding events on the genetic diversity of a population, and confirm that changes to genetic diversity can occur within just a few generations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2011.11.031","usgsCitation":"Sonsthagen, S.A., Coonan, T., Latta, B.C., Sage, G.K., and Talbot, S.L., 2012, Genetic diversity of a newly established population of golden eagles on the Channel Islands, California: Biological Conservation, v. 146, no. 1, p. 116-122, https://doi.org/10.1016/j.biocon.2011.11.031.","productDescription":"7 p.","startPage":"116","endPage":"122","numberOfPages":"7","ipdsId":"IP-034362","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":289750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289729,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2011.11.031"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.5,33.8 ], [ -120.5,34.52 ], [ -119.2,34.52 ], [ -119.2,33.8 ], [ -120.5,33.8 ] ] ] } } ] }","volume":"146","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53bfb600e4b06d97a6487d1c","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":495771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coonan, Timothy J.","contributorId":60955,"corporation":false,"usgs":true,"family":"Coonan","given":"Timothy J.","affiliations":[],"preferred":false,"id":495773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Latta, Brian C.","contributorId":25466,"corporation":false,"usgs":true,"family":"Latta","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":495772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":495774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":495770,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043303,"text":"70043303 - 2012 - Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring","interactions":[],"lastModifiedDate":"2018-03-08T13:02:00","indexId":"70043303","displayToPublicDate":"2012-02-01T10:35:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring","docAbstract":"agebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change – adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Applied Earth Observation and Geoinformation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2011.09.012","usgsCitation":"Homer, C.G., Aldridge, C.L., Meyer, D., and Schell, S., 2012, Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring: International Journal of Applied Earth Observation and Geoinformation, v. 14, no. 1, p. 233-244, https://doi.org/10.1016/j.jag.2011.09.012.","productDescription":"12 p.","startPage":"233","endPage":"244","numberOfPages":"12","ipdsId":"IP-014786","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":281235,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jag.2011.09.012"},{"id":281236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0569,40.9947 ], [ -111.0569,45.0059 ], [ -104.0522,45.0059 ], [ -104.0522,40.9947 ], [ -111.0569,40.9947 ] ] ] } } ] }","volume":"14","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd685ae4b0b29085101fb5","contributors":{"authors":[{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":473345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":473342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Debra K. 0000-0002-8841-697X","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":72282,"corporation":false,"usgs":true,"family":"Meyer","given":"Debra K.","affiliations":[],"preferred":false,"id":473344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schell, Spencer J.","contributorId":50432,"corporation":false,"usgs":true,"family":"Schell","given":"Spencer J.","affiliations":[],"preferred":false,"id":473343,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042896,"text":"70042896 - 2012 - Utilizing multichannel electrical resistivity methods to examine the dynamics of the fresh water–seawater interface in two Hawaiian groundwater systems","interactions":[],"lastModifiedDate":"2016-08-29T20:22:06","indexId":"70042896","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Utilizing multichannel electrical resistivity methods to examine the dynamics of the fresh water–seawater interface in two Hawaiian groundwater systems","docAbstract":"<p><span>Multichannel electrical resistivity (ER) measurements were conducted at two contrasting coastal sites in Hawaii to obtain new information on the spatial scales and dynamics of the fresh water&ndash;seawater interface and rates of coastal groundwater exchange. At Kiholo Bay (located on the dry, Kona side of the Big Island) and at a site in Maunalua Bay (Oahu), there is an evidence for abundant submarine groundwater discharge (SGD). However, the hydrologic and geologic controls on coastal groundwater discharge are likely to be different at these two sites. While at Kiholo Bay SGD is predominantly through lava tubes, at the Maunalua Bay site exchange occurs mostly through nearshore submarine springs. In order to calculate SGD fluxes, it is important to understand the spatial and temporal scales of coastal groundwater exchange. From ER time series data, subsurface salinity distributions were calculated using site-specific formation factors. A salinity mass balance box model was then used to calculate rates of point source (i.e., spatially discreet) and total fresh water discharge. From these data, mean SGD rates were calculated for Kiholo Bay (&sim;9,200&nbsp;m</span><sup><span>3</span></sup><span>/d) and for the Maunalua Bay site (&sim;5,900&nbsp;m</span><sup><span>3</span></sup><span>/d). While such results are on the same order of magnitude to geochemical tracer-derived SGD rates, the ER SGD rates provide enhanced details of coastal groundwater exchange that can enable a more cohesive whole watershed perspective.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JC007509","usgsCitation":"Dimova, N.T., Swarzenski, P.W., Dulaiova, H., and Glenn, C.R., 2012, Utilizing multichannel electrical resistivity methods to examine the dynamics of the fresh water–seawater interface in two Hawaiian groundwater systems: Journal of Geophysical Research C: Oceans, v. 117, no. C2, C02012; 12 p., https://doi.org/10.1029/2011JC007509.","productDescription":"C02012; 12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032654","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474583,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jc007509","text":"Publisher Index Page"},{"id":272289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Big Island, Kiholo Bay, Oahu, Wailupe Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.9,\n              19.83\n            ],\n            [\n              -155.9,\n              19.88\n            ],\n            [\n              -155.95,\n              19.88\n            ],\n            [\n              -155.95,\n              19.83\n            ],\n            [\n              -155.9,\n              19.83\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.8,\n              21.25\n            ],\n            [\n              -157.8,\n              21.3\n            ],\n            [\n              -157.75,\n              21.3\n            ],\n            [\n              -157.75,\n              21.25\n            ],\n            [\n              -157.8,\n              21.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"117","issue":"C2","noUsgsAuthors":false,"publicationDate":"2012-02-07","publicationStatus":"PW","scienceBaseUri":"51955851e4b0a933d82c4cd7","contributors":{"authors":[{"text":"Dimova, Natasha T.","contributorId":50769,"corporation":false,"usgs":true,"family":"Dimova","given":"Natasha","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":472529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dulaiova, Henrieta","contributorId":46635,"corporation":false,"usgs":true,"family":"Dulaiova","given":"Henrieta","affiliations":[],"preferred":false,"id":472528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glenn, Craig R.","contributorId":10850,"corporation":false,"usgs":true,"family":"Glenn","given":"Craig","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":472527,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193188,"text":"70193188 - 2012 - Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","interactions":[],"lastModifiedDate":"2017-12-01T09:59:57","indexId":"70193188","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","docAbstract":"<p><span>Ecological indicators are science-based tools used to assess how human activities have impacted environmental resources. For monitoring and environmental assessment, existing species assemblage data can be used to make these comparisons through time or across sites. An impediment to using assemblage data, however, is that these data are complex and need to be simplified in an ecologically meaningful way. Because multivariate statistics are mathematical relationships, statistical groupings may not make ecological sense and will not have utility as indicators. Our goal was to define a process to select defensible and ecologically interpretable statistical simplifications of assemblage data in which researchers and managers can have confidence. For this, we chose a suite of statistical methods, compared the groupings that resulted from these analyses, identified convergence among groupings, then we interpreted the groupings using species and ecological guilds. When we tested this approach using a statewide stream fish dataset, not all statistical methods worked equally well. For our dataset, logistic regression (Log), detrended correspondence analysis (DCA), cluster analysis (CL), and non-metric multidimensional scaling (NMDS) provided consistent, simplified output. Specifically, the Log, DCA, CL-1, and NMDS-1 groupings were ≥60% similar to each other, overlapped with the fluvial-specialist ecological guild, and contained a common subset of species. Groupings based on number of species (e.g., Log, DCA, CL and NMDS) outperformed groupings based on abundance [e.g., principal components analysis (PCA) and Poisson regression]. Although the specific methods that worked on our test dataset have generality, here we are advocating a process (e.g., identifying convergent groupings with redundant species composition that are ecologically interpretable) rather than the automatic use of any single statistical tool. We summarize this process in step-by-step guidance for the future use of these commonly available ecological and statistical methods in preparing assemblage data for use in ecological indicators.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2011.06.009","usgsCitation":"Smith, J.M., and Mather, M.E., 2012, Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools: Ecological Indicators, v. 13, no. 1, p. 253-262, https://doi.org/10.1016/j.ecolind.2011.06.009.","productDescription":"10 p.","startPage":"253","endPage":"262","ipdsId":"IP-008536","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":349610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61059fe4b06e28e9c2556b","contributors":{"authors":[{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":724247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":718143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156894,"text":"70156894 - 2012 - Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","interactions":[],"lastModifiedDate":"2022-11-07T17:40:56.947812","indexId":"70156894","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","docAbstract":"<p><span>The Hayward fault (HF) in California exhibits large (Mw 6.5&ndash;7.1) earthquakes with short recurrence times (161&plusmn;65 yr), probably kept short by a 26%&ndash;78% aseismic release rate (including postseismic). Its interseismic release rate varies locally over time, as we infer from many decades of surface creep data. Earliest estimates of creep rate, primarily from infrequent surveys of offset cultural features, revealed distinct spatial variation in rates along the fault, but no detectable temporal variation. Since the 1989 Mw 6.9 Loma Prieta earthquake (LPE), monitoring on 32 alinement arrays and 5 creepmeters has greatly improved the spatial and temporal resolution of creep rate. We now identify significant temporal variations, mostly associated with local and regional earthquakes. The largest rate change was a 6‐yr cessation of creep along a 5‐km length near the south end of the HF, attributed to a regional stress drop from the LPE, ending in 1996 with a 2‐cm creep event. North of there near Union City starting in 1991, rates apparently increased by 25% above pre‐LPE levels on a 16‐km‐long reach of the fault. Near Oakland in 2007 an Mw 4.2 earthquake initiated a 1&ndash;2 cm creep event extending 10&ndash;15 km along the fault. Using new better‐constrained long‐term creep rates, we updated earlier estimates of depth to locking along the HF. The locking depths outline a single, &sim;50‐km‐long locked or retarded patch with the potential for an Mw&sim;6.8 event equaling the 1868 HF earthquake. We propose that this inferred patch regulates the size and frequency of large earthquakes on HF.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110033","usgsCitation":"Lienkaemper, J.J., McFarland, F.S., Simpson, R.W., Bilham, R.G., Ponce, D.A., Boatwright, J., and Caskey, S., 2012, Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 31-41, https://doi.org/10.1785/0120110033.","productDescription":"11 p.","startPage":"31","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027196","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":307782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.38123406534956,\n              38.00934151742379\n            ],\n            [\n              -122.32149985140742,\n              37.926931149563714\n            ],\n            [\n              -122.25536554311417,\n              37.83600445938727\n            ],\n            [\n              -122.14016384479675,\n              37.721344572141575\n            ],\n            [\n              -121.90549371859511,\n              37.51180141349239\n            ],\n            [\n              -121.83935941030182,\n              37.57607899882744\n            ],\n            [\n              -122.06976280693638,\n              37.812412552098394\n            ],\n            [\n              -122.18069777568618,\n              37.93870972218559\n            ],\n            [\n              -122.35350032316217,\n              38.03959147739795\n            ],\n            [\n              -122.38123406534956,\n              38.00934151742379\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"55e6cc35e4b05561fa20a01b","contributors":{"authors":[{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Forrest S.","contributorId":32104,"corporation":false,"usgs":true,"family":"McFarland","given":"Forrest","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":571019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simpson, Robert W. simpson@usgs.gov","contributorId":1053,"corporation":false,"usgs":true,"family":"Simpson","given":"Robert","email":"simpson@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":571020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bilham, Roger G. 0000-0002-5547-4102","orcid":"https://orcid.org/0000-0002-5547-4102","contributorId":48200,"corporation":false,"usgs":true,"family":"Bilham","given":"Roger","email":"","middleInitial":"G.","affiliations":[],"preferred":true,"id":571021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":571022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571023,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caskey, S. John","contributorId":21483,"corporation":false,"usgs":true,"family":"Caskey","given":"S. John","affiliations":[],"preferred":false,"id":571024,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70007246,"text":"sir20115207 - 2012 - Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115207","displayToPublicDate":"2012-01-31T00:00:00","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":"2011-5207","title":"Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","docAbstract":"The six Middle Rio Grande Pueblos have prior and paramount rights to deliveries of water from the Rio Grande for their use. When the pueblos or the Bureau of Indian Affairs Designated Engineer identifies a need for additional flow on the Rio Grande, the Designated Engineer is tasked with deciding the timing and amount of releases of prior and paramount water from storage at El Vado Reservoir to meet the needs of the pueblos. Over the last three decades, numerous models have been developed by Federal, State, and local agencies in New Mexico to simulate, understand, and (or) manage flows in the Middle Rio Grande upstream from Elephant Butte Reservoir. In 2008, the Coalition of Six Middle Rio Grande Basin Pueblos entered into a cooperative agreement with the U.S. Geological Survey to conduct a comprehensive survey of these hydrologic models and their capacity to quantify and track various components of flow. The survey of hydrologic models provided in this report will help water-resource managers at the pueblos, as well as the Designated Engineer, make informed water-resource-management decisions that affect the prior and paramount water use. Analysis of 4 publicly available surface-water models and 13 publicly available groundwater models shows that, although elements from many models can be helpful in tracking flow in the Rio Grande, numerous data gaps and modeling needs indicate that accurate, consistent, and timely tracking of flow on the Rio Grande could be improved. Deficient or poorly constrained hydrologic variables are sources of uncertainty in hydrologic models that can be reduced with the acquisition of more refined data. Data gaps need to be filled to allow hydrologic models to be run on a real-time basis and thus ensure predictable water deliveries to meet needs for irrigation, domestic, stock, and other water uses. Timeliness of flow-data reporting is necessary to facilitate real-time model simulation, but even daily data are sometimes difficult to obtain because the data come from multiple sources. Each surface-water model produces results that could be helpful in quantifying the flow of the Rio Grande, specifically by helping to track water as it moves down the channel of the Rio Grande and by improving the understanding of river hydraulics for the specified reaches. The ability of each surface-water model to track flow on the Rio Grande varies according to the purpose for which each model was designed. The purpose of Upper Rio Grande Water Operations Model (URGWOM) - to simulate water storage and delivery operations in the Rio Grande - is more applicable to tracking flow on the Rio Grande than are any of the other surface-water models surveyed. Specifically, the strengths of URGWOM in relation to modeling flow are the details and attention given to the accounting of Rio Grande flow and San Juan-Chama flow at a daily time step. The most significant difficulty in using any of the surveyed surface-water models for the purpose of predicting the need for requested water releases is that none of the surface-water models surveyed consider water accounting on a real-time basis. Groundwater models that provide detailed simulations of shallow groundwater flow in the vicinity of the Rio Grande can provide large-scale estimates of flow between the Rio Grande and shallow aquifers, which can be an important component of the Rio Grande water budget as a whole. The groundwater models surveyed for this report cannot, however, be expected to provide simulations of flow at time scales of less than the simulated time step (1 month to 1 year in most cases). Of those of the currently used groundwater models, the purpose of model 13 - to simulate the shallow riparian groundwater environment - is the most appropriate for examining local-scale surface-water/groundwater interactions. The basin-scale models, however, are also important in understanding the large-scale water balances between the aquifers and the surface water. In the case of the Upper and Middle Rio Grande Valley, models 6, 10, and 12 are the most accurate and current groundwater models available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115207","collaboration":"Prepared in cooperation with the Coalition of Six Middle Rio Grande Basin Pueblos","usgsCitation":"Tillery, A., and Eggleston, J.R., 2012, Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010: U.S. Geological Survey Scientific Investigations Report 2011-5207, vii, 39 p., https://doi.org/10.3133/sir20115207.","productDescription":"vii, 39 p.","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":116455,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5207.gif"},{"id":115750,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5207/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator, zone 13","datum":"North American Datum of 1988","country":"United States","state":"Colorado;New Mexico","otherGeospatial":"Rio Grande Basin;Elephant Butte Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105,33 ], [ -105,39 ], [ -109,39 ], [ -109,33 ], [ -105,33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba295e4b08c986b31f7e8","contributors":{"authors":[{"text":"Tillery, Anne","contributorId":16120,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","affiliations":[],"preferred":false,"id":356177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eggleston, Jack R.","contributorId":20011,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":356178,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70007105,"text":"70007105 - 2012 - A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","interactions":[],"lastModifiedDate":"2021-01-04T18:07:50.71384","indexId":"70007105","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","docAbstract":"<p><span>Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (&lt;1 to 3.2&nbsp;kg&nbsp;Nr&nbsp;ha</span><sup>−1</sup><span>&nbsp;year</span><sup>−1</sup><span>&nbsp;in wet deposition). Out of the fourteen measured environmental variables for these 46 lakes, ordination analysis identified that nitrate, specific conductance, total phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (&lt;1&nbsp;μg&nbsp;L</span><sup>−1</sup><span>), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.</span></p>","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10933-011-9576-z","usgsCitation":"Arnett, H.A., Saros, J.E., and Mast, M.A., 2012, A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes: Journal of Paleolimnology, v. 47, no. 2, p. 277-291, https://doi.org/10.1007/s10933-011-9576-z.","productDescription":"15 p.","startPage":"277","endPage":"291","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":204684,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, Utah, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.02636718749999,\n              37.17782559332976\n            ],\n            [\n              -102.41455078125,\n              37.17782559332976\n            ],\n            [\n              -102.41455078125,\n              48.980216985374994\n            ],\n            [\n              -117.02636718749999,\n              48.980216985374994\n            ],\n            [\n              -117.02636718749999,\n              37.17782559332976\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-01-10","publicationStatus":"PW","scienceBaseUri":"5059e33ce4b0c8380cd45ecc","contributors":{"authors":[{"text":"Arnett, Heather A.","contributorId":74141,"corporation":false,"usgs":true,"family":"Arnett","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":355826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saros, Jasmine E.","contributorId":29958,"corporation":false,"usgs":true,"family":"Saros","given":"Jasmine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":355825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":355824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70007241,"text":"mineral2012 - 2012 - Mineral Commodity Summaries 2012","interactions":[],"lastModifiedDate":"2013-02-04T10:57:03","indexId":"mineral2012","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012","title":"Mineral Commodity Summaries 2012","docAbstract":"<p>Each chapter of the 2012 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2011 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.</p>\n<p>For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.</p>\n<p>Abbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C&mdash;Reserves and Resources\" includes \"Part A&mdash;Resource/Reserve Classification for Minerals\" and \"Part B&mdash;Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.</p>\n<p>The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2012 are welcomed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mineral2012","isbn":"9781411333499","usgsCitation":"Mineral Commodity Summaries 2012; 2012; MINERAL; 2012; ","productDescription":"191 p.; Appendixes; Individual Commodity Data Sheets; Available Online, Printed, and on CD-ROM","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":115736,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/","linkFileType":{"id":5,"text":"html"}},{"id":204589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/mineral_2012.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a574fe4b0c8380cd6dbc7"}
,{"id":70007247,"text":"70007247 - 2012 - Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere&ndash;wave&ndash;sediment transport (COAWST) modeling system","interactions":[],"lastModifiedDate":"2017-04-06T15:04:03","indexId":"70007247","displayToPublicDate":"2012-01-27T09:39:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere&ndash;wave&ndash;sediment transport (COAWST) modeling system","docAbstract":"The coupled ocean&ndash;atmosphere&ndash;wave&ndash;sediment transport (COAWST) modeling system was used to investigate atmosphere&ndash;ocean&ndash;wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor'Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor'easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor'Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ocean Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ocemod.2011.12.008","usgsCitation":"Olabarrieta, M., Warner, J., Armstrong, B., Zambon, J.B., and He, R., 2012, Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere&ndash;wave&ndash;sediment transport (COAWST) modeling system: Ocean Modelling, v. 43-44, p. 112-137, https://doi.org/10.1016/j.ocemod.2011.12.008.","productDescription":"26 p.","startPage":"112","endPage":"137","numberOfPages":"25","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474584,"rank":101,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5124","text":"External Repository"},{"id":204581,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":115753,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.ocemod.2011.12.008","linkFileType":{"id":5,"text":"html"}}],"volume":"43-44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6c98e4b0c8380cd74ce7","contributors":{"authors":[{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":356179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Armstrong, Brandy N. barmstrong@usgs.gov","contributorId":5897,"corporation":false,"usgs":true,"family":"Armstrong","given":"Brandy N.","email":"barmstrong@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambon, Joseph B.","contributorId":8222,"corporation":false,"usgs":true,"family":"Zambon","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":356181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Ruoying","contributorId":68029,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":356182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70007235,"text":"gip137 - 2012 - GloVis","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"gip137","displayToPublicDate":"2012-01-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"137","title":"GloVis","docAbstract":"The Global Visualization Viewer (GloVis) trifold provides basic information for online access to a subset of satellite and aerial photography collections from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center archive. The GloVis (http://glovis.usgs.gov/) browser-based utility allows users to search and download National Aerial Photography Program (NAPP), National High Altitude Photography (NHAP), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing-1 (EO-1), Global Land Survey, Moderate Resolution Imaging Spectroradiometer (MODIS), and TerraLook data. Minimum computer system requirements and customer service contact information also are included in the brochure.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip137","usgsCitation":"Houska, T., and Johnson, A., 2012, GloVis: U.S. Geological Survey General Information Product 137, 2 p., https://doi.org/10.3133/gip137.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116454,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_137.jpg"},{"id":115721,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/137/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a292ee4b0c8380cd5a71d","contributors":{"authors":[{"text":"Houska, Treva R. 0000-0002-4358-6131","orcid":"https://orcid.org/0000-0002-4358-6131","contributorId":45460,"corporation":false,"usgs":true,"family":"Houska","given":"Treva R.","affiliations":[],"preferred":false,"id":356155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, A.P.","contributorId":22495,"corporation":false,"usgs":true,"family":"Johnson","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":356154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70007222,"text":"sir20125005 - 2012 - A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","interactions":[],"lastModifiedDate":"2017-03-29T14:26:09","indexId":"sir20125005","displayToPublicDate":"2012-01-26T00:00:00","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":"2012-5005","title":"A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","docAbstract":"Recent advances in remote-sensing technology and Simplified Surface Energy Balance (SSEB) methods can provide accurate and repeatable estimates of evapotranspiration (ET) when used with satellite observations of irrigated lands. Estimates of ET are generally considered equivalent to consumptive use (CU) because they represent the part of applied irrigation water that is evaporated, transpired, or otherwise not available for immediate reuse. The U.S. Geological Survey compared ET estimates from SSEB methods to CU data collected for 1995 using indirect methods as part of the National Water Use Information Program (NWUIP). Ten-year (2000-2009) average ET estimates from SSEB methods were derived using Moderate Resolution Imaging Spectroradiometer (MODIS) 1-kilometer satellite land surface temperature and gridded weather datasets from the Global Data Assimilation System (GDAS). County-level CU estimates for 1995 were assembled and referenced to 1-kilometer grid cells to synchronize with the SSEB ET estimates. Both datasets were seasonally and spatially weighted to represent the irrigation season (June-September) and those lands that were identified in the county as irrigated. A strong relation (R2 greater than 0.7) was determined between NWUIP CU and SSEB ET data. Regionally, the relation is stronger in arid western states than in humid eastern states, and positive and negative biases are both present at state-level comparisons. SSEB ET estimates can play a major role in monitoring and updating county-based CU estimates by providing a quick and cost-effective method to detect major year-to-year changes at county levels, as well as providing a means to disaggregate county-based ET estimates to sub-county levels. More research is needed to identify the causes for differences in state-based relations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125005","collaboration":"Groundwater Resources Program","usgsCitation":"Maupin, M.A., Senay, G., Kenny, J., and Savoca, M.E., 2012, A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods: U.S. Geological Survey Scientific Investigations Report 2012-5005, iv, 8 p., https://doi.org/10.3133/sir20125005.","productDescription":"iv, 8 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116452,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5005.jpg"},{"id":115711,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5005/","linkFileType":{"id":5,"text":"html"}},{"id":338663,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5005/pdf/sir20125005.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e359e4b0c8380cd45fa9","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":356133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":356134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70007223,"text":"sim3190 - 2012 - Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"sim3190","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3190","title":"Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","docAbstract":"The efficacy of airborne spectroscopic, or \"hyperspectral,\" remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated mineral group mapping products described in this study are ideal for application to mineral resource and mineral-environmental assessments at regional and national scales.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3190","usgsCitation":"Rockwell, B.W., 2012, Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3190, Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data, https://doi.org/10.3133/sim3190.","productDescription":"Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data","numberOfPages":"35","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116450,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3190.png"},{"id":115712,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3190/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108,37.46666666666667 ], [ -108,38.083333333333336 ], [ -107.15,38.083333333333336 ], [ -107.15,37.46666666666667 ], [ -108,37.46666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059feeee4b0c8380cd4efbb","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":356135,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70007227,"text":"ds660 - 2012 - Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds660","displayToPublicDate":"2012-01-26T00:00:00","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":"660","title":"Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","docAbstract":"This report, prepared in cooperation with the U.S. Department of Energy, summarizes construction, geophysical, and lithologic data collected from about 4,509 feet of core from seven boreholes deepened or drilled by the U.S. Geological Survey (USGS), Idaho National Laboratory (INL) Project Office, from 2006 to 2009 at the INL. USGS 103, 105, 108, and 131 were deepened and cored from 759 to 1,307 feet, 800 to 1,409 feet, 760 to 1,218 feet, and 808 to 1,239 feet, respectively. Boreholes USGS 135, NRF-15, and NRF-16 were drilled and continuously cored from land surface to 1,198, 759, and 425 feet, respectively. Cores were photographed and digitally logged by using commercially available software. Borehole descriptions summarize location, completion date, and amount and type of core recovered.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds660","collaboration":"Prepared in cooperation with the U.S. Department of Energy, DOE/ID-22217","usgsCitation":"Hodges, M., Orr, S.M., Potter, K.E., and LeMaitre, T., 2012, Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho: U.S. Geological Survey Data Series 660, vi, 33 p.; Appendices; Downloadable Appendices A-G, https://doi.org/10.3133/ds660.","productDescription":"vi, 33 p.; Appendices; Downloadable Appendices A-G","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116448,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_660.jpg"},{"id":115709,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/660/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator projection, Zone 12","datum":"Datum is North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain;Idaho National Laboratory","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.5,43.25 ], [ -113.5,44 ], [ -112.5,44 ], [ -112.5,43.25 ], [ -113.5,43.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fa17e4b0c8380cd4d926","contributors":{"authors":[{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":356144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Stephanie M.","contributorId":22089,"corporation":false,"usgs":true,"family":"Orr","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":356142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potter, Katherine E.","contributorId":76886,"corporation":false,"usgs":true,"family":"Potter","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeMaitre, Tynan","contributorId":51455,"corporation":false,"usgs":true,"family":"LeMaitre","given":"Tynan","email":"","affiliations":[],"preferred":false,"id":356143,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70007228,"text":"ds657 - 2012 - Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds657","displayToPublicDate":"2012-01-26T00:00:00","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":"657","title":"Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","docAbstract":"The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa area. Municipal wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have been conducting a cooperative study of the groundwater-flow system and water quality of the aquifer since 1992. Cooperative reports between the City of Cedar Rapids and the U.S. Geological Survey have documented hydrologic and water-quality data, geochemistry, and groundwater models. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water-groundwater interaction, and pesticides in groundwater and surface water. Water-quality analyses were conducted for major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, and sulfate), nutrients (ammonia as nitrogen, nitrite as nitrogen, nitrite plus nitrate as nitrogen, and orthophosphate as phosphorus), dissolved organic carbon, and selected pesticides including two degradates of the herbicide atrazine. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance and water temperature) were measured in the field and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from January 2006 through December 2010. Methods of data collection, quality-assurance, and water-quality analyses are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, municipal wells, and the Cedar River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds657","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Littin, G.R., 2012, Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10: U.S. Geological Survey Data Series 657, vi, 32 p., https://doi.org/10.3133/ds657.","productDescription":"vi, 32 p.","onlineOnly":"Y","temporalStart":"2006-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":116449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_657.jpg"},{"id":115710,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/657/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Iowa","county":"Linn","city":"Cedar Rapids","otherGeospatial":"Cedar River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.75,41.96666666666667 ], [ -91.75,42.03333333333333 ], [ -91.66666666666667,42.03333333333333 ], [ -91.66666666666667,41.96666666666667 ], [ -91.75,41.96666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8cc3e4b08c986b3180ef","contributors":{"authors":[{"text":"Littin, Gregory R. grlittin@usgs.gov","contributorId":1732,"corporation":false,"usgs":true,"family":"Littin","given":"Gregory","email":"grlittin@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":356146,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005180,"text":"70005180 - 2012 - Using existing data to estimate aquifer properties, Great Lakes Region, USA","interactions":[],"lastModifiedDate":"2012-06-14T01:01:39","indexId":"70005180","displayToPublicDate":"2012-01-24T09:55:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Using existing data to estimate aquifer properties, Great Lakes Region, USA","docAbstract":"To determine specific storage and porosity, areally limited and time-consuming aquifer tests are frequently done. Hydrogeologic studies often do not have the resources to collect such data and rely on existing data sources for aquifer properties. An alternative tool for determining these aquifer properties is the analysis of earth tides. The objective of this study was to determine whether existing water-level and barometric-pressure data could be used to determine aquifer properties, such as porosity and specific storage, on a regional scale. In this study, national databases from the Great Lakes Region were queried for continuous records of groundwater-level and barometric-pressure data. Records from 37 selected wells were then analyzed for barometric efficiency and earth-tide responses. Specific-storage (S<sub>s</sub>) and porosity values were determined, and the quality of the results were assessed with a measure of the \"goodness of fit\" (percent variance) of reconstruction of the response. Records from wells completed in several aquifer systems were analyzed with varying degrees of success. Aquifer S<sub>s</sub> values ranging from 5.9 x 10<sup>-8</sup> to 3.8 x 10<sup>-6</sup>/m were derived, with percent variance of reconstruction ranging from 1% to 78%. Comparisons with aquifer and laboratory testing of S<sub>s</sub> and porosity are favorable if the percent variance of reconstruction is above about 30%. Although the earth-tide-analysis method is not suitable for every situation, the S<sub>s</sub> and porosity of aquifers can, in many places, be estimated with existing water-level and barometric-pressure data or with data that are relatively inexpensive to collect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Ground Water Assocation","publisherLocation":"Westerville, OH","doi":"10.1111/j.1745-6584.2011.00848.x","usgsCitation":"Darner, R.A., and Sheets, R., 2012, Using existing data to estimate aquifer properties, Great Lakes Region, USA: Ground Water, v. 50, no. 3, https://doi.org/10.1111/j.1745-6584.2011.00848.x.","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":257571,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257554,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00848.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Great Lakes","volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-07-28","publicationStatus":"PW","scienceBaseUri":"505bc04be4b08c986b32a03c","contributors":{"authors":[{"text":"Darner, Robert A. 0000-0003-1333-8265 radarner@usgs.gov","orcid":"https://orcid.org/0000-0003-1333-8265","contributorId":1972,"corporation":false,"usgs":true,"family":"Darner","given":"Robert","email":"radarner@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheets, Rodney A. rasheets@usgs.gov","contributorId":1848,"corporation":false,"usgs":true,"family":"Sheets","given":"Rodney A.","email":"rasheets@usgs.gov","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70007181,"text":"ofr20111312 - 2012 - Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"ofr20111312","displayToPublicDate":"2012-01-23T11:26:00","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":"2011-1312","title":"Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas","docAbstract":"<p>Since the early 1900s, the distribution of the Long-billed Curlew (<i>Numenius americanus</i>) has contracted dramatically in the eastern one-half of its historic range. The species has been designated as a \"Bird of Conservation Concern\" and focal species by the U.S. Fish and Wildlife Service, a species of concern by several states, and a \"Highly Imperiled\" species in the U.S. Shorebird Conservation Plan. The uncertain outlook for this species has contributed to a plethora of research on Long-billed Curlews, most of which have focused on breeding and nesting ecology of the species. Gaps remain in information about factors affecting population dynamics on the winter grounds and the linkages between Long-billed Curlew populations on the breeding range, migration routes, and winter range. To begin filling those gaps, a pilot study was done to evaluate (1) curlew use of nocturnal roost sites, (2) use of public outreach to locate curlews and contribute to preliminary assessment of foraging habitat use, (3) six different methods to capture curlews, and (4) movements by curlews on wintering areas. The study area includes the lower Texas coast, which harbors the eastern-most dense populations of Long-billed Curlews in North America.</p>\n<p>Use of historical winter roost sites was not observed; however, there was documented limited use (up to 150 curlews) of several new roost sites, some of which were used on an intermittent or erratic basis. Reports elicited from the public indicated Long-billed Curlews wintering in coastal Texas often forage in open, grass-covered lots of partially developed residential areas, golf courses, and public parks within urban and suburban zones. Curlews were reported to use these sites in developed areas as far as 100 kilometers inland. Other reports indicated Long-billed Curlews foraging in farm fields, shallow coastal marsh, and on the beaches of Gulf of Mexico barrier islands.</p>\n<p>The effectiveness of six techniques for capture of Long-billed Curlews was evaluated in the study. Seven curlews were captured and banded with four of six methods attempted. At least one curlew each was captured with (1) noose ropes, (2) baited bow net, (3) Coda Netgun, and (4) whoosh net; no curlews were caught with a cast net or Super Talon netgun. The Coda Netgun proved to be the most effective methodology examined. Captured birds (7) were weighed, measured, and banded. Body masses (mean = 518 grams) were low compared to data previously published on body mass of Long-billed Curlews. There were 22 observations recorded of banded curlews. Resightings confirmed that birds were not harmed during capture. All of the 22 resightings occurred within two kilometers of the banding locations, suggesting that birds remained near their chosen foraging areas.</p>\n<p>Results from this 1-year pilot study yielded an intriguing combination of findings that warrant further investigation. Observations include reduced numbers of roosting birds along the Texas coast during dry conditions, highly dynamic use of nocturnal roost sites, use of widely divergent habitat types for foraging, low body mass of most captured birds, and apparent fidelity to general feeding areas. Future investigations of this eastern winter population of curlews would benefit from larger sample sizes and monitoring of individual birds.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111312","usgsCitation":"Woodin, M.C., Skoruppa, M.K., Edwardson, J.W., and Austin, J., 2012, Preliminary investigations of the winter ecology of Long-billed Curlews in coastal Texas: U.S. Geological Survey Open-File Report 2011-1312, vi, 17 p., https://doi.org/10.3133/ofr20111312.","productDescription":"vi, 17 p.","onlineOnly":"Y","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":116373,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1312.jpg"},{"id":115679,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1312/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.5,26.666666666666668 ], [ -99.5,29 ], [ -95.16666666666667,29 ], [ -95.16666666666667,26.666666666666668 ], [ -99.5,26.666666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8856e4b0c8380cd7d865","contributors":{"authors":[{"text":"Woodin, Marc C.","contributorId":56316,"corporation":false,"usgs":true,"family":"Woodin","given":"Marc","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":356027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skoruppa, Mary Kay","contributorId":24872,"corporation":false,"usgs":true,"family":"Skoruppa","given":"Mary","email":"","middleInitial":"Kay","affiliations":[],"preferred":false,"id":356025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwardson, Jeremy W.","contributorId":22091,"corporation":false,"usgs":true,"family":"Edwardson","given":"Jeremy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":356024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Austin, Jane E.","contributorId":43094,"corporation":false,"usgs":true,"family":"Austin","given":"Jane E.","affiliations":[],"preferred":false,"id":356026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70007190,"text":"ofr20111261 - 2012 - Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas","interactions":[],"lastModifiedDate":"2019-06-06T08:05:56","indexId":"ofr20111261","displayToPublicDate":"2012-01-23T00:00:00","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":"2011-1261","title":"Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas","docAbstract":"<p>Coal exploration drill-hole data from over 24,000 wells in 10 States are discussed by State in the chapters of this report, and the data are provided in an accompanying spreadsheet. The drill holes were drilled between 1962 and 1984 by Phillips Coal Company, a division of Phillips Petroleum Company (Phillips). The data were donated to the U.S. Geological Survey (USGS) in 2001 by the North American Coal Corporation, which purchased the Phillips assets as part of a larger dataset. Under the terms of the agreement with North American Coal Corporation, the data were deemed proprietary until February 2011, a period of 10 years after the donation (Appendix of Chapter A). Now that the required period of confidentiality has passed, the data have been digitized from tabulated data files to create unified and spatially consistent coal exploration drill-hole maps and reports for the States of Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas. The data are made publicly available by this report.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111261","usgsCitation":"Valentine, B.J., and Dennen, K., 2012, Shallow coal exploration drill-hole data--Alabama, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, and Texas: U.S. Geological Survey Open-File Report 2011-1261, Report: 104 p., 12 Appendixes, https://doi.org/10.3133/ofr20111261.","productDescription":"Report: 104 p., 12 Appendixes","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":116372,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1261.gif"},{"id":115683,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1261/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama; Georgia; Kentucky; Louisiana; Mississippi; Missouri; North Carolina; South Carolina; Tennessee; 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,{"id":70007169,"text":"ofr20111306 - 2012 - User's guide for mapIMG 3--Map image re-projection software package","interactions":[],"lastModifiedDate":"2012-02-02T00:16:02","indexId":"ofr20111306","displayToPublicDate":"2012-01-20T00:00:00","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":"2011-1306","title":"User's guide for mapIMG 3--Map image re-projection software package","docAbstract":"Version 0.0 (1995), Dan Steinwand, U.S. Geological Survey (USGS)/Earth Resources Observation Systems (EROS) Data Center (EDC)--Version 0.0 was a command line version for UNIX that required four arguments: the input metadata, the output metadata, the input data file, and the output destination path. Version 1.0 (2003), Stephen Posch and Michael P. Finn, USGS/Mid-Continent Mapping Center (MCMC--Version 1.0 added a GUI interface that was built using the Qt library for cross platform development. Version 1.01 (2004), Jason Trent and Michael P. Finn, USGS/MCMC--Version 1.01 suggested bounds for the parameters of each projection. Support was added for larger input files, storage of the last used input and output folders, and for TIFF/ GeoTIFF input images. Version 2.0 (2005), Robert Buehler, Jason Trent, and Michael P. Finn, USGS/National Geospatial Technical Operations Center (NGTOC)--Version 2.0 added Resampling Methods (Mean, Mode, Min, Max, and Sum), updated the GUI design, and added the viewer/pre-viewer. The metadata style was changed to XML and was switched to a new naming convention. Version 3.0 (2009), David Mattli and Michael P. Finn, USGS/Center of Excellence for Geospatial Information Science (CEGIS)--Version 3.0 brings optimized resampling methods, an updated GUI, support for less than global datasets, UTM support and the whole codebase was ported to Qt4.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111306","usgsCitation":"Finn, M.P., and Mattli, D.M., 2012, User's guide for mapIMG 3--Map image re-projection software package: U.S. Geological Survey Open-File Report 2011-1306, iv, 12 p., https://doi.org/10.3133/ofr20111306.","productDescription":"iv, 12 p.","startPage":"i","endPage":"12","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":116445,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1306.jpg"},{"id":115659,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1306/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbfdae4b08c986b329dd1","contributors":{"authors":[{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":356015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mattli, David M. dmattli@usgs.gov","contributorId":5606,"corporation":false,"usgs":true,"family":"Mattli","given":"David","email":"dmattli@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":356016,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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