{"pageNumber":"548","pageRowStart":"13675","pageSize":"25","recordCount":40783,"records":[{"id":70156728,"text":"70156728 - 2015 - Defining population structure and genetic signatures of decline in the giant garter snake (<i>Thamnophis gigas</i>): implications for conserving threatened species within highly altered landscapes","interactions":[],"lastModifiedDate":"2015-09-28T11:26:20","indexId":"70156728","displayToPublicDate":"2015-04-11T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Defining population structure and genetic signatures of decline in the giant garter snake (<i>Thamnophis gigas</i>): implications for conserving threatened species within highly altered landscapes","docAbstract":"<p><span>Anthropogenic habitat fragmentation can disrupt the ability of species to disperse across landscapes, which can alter the levels and distribution of genetic diversity within populations and negatively impact long-term viability. The giant gartersnake (</span><i class=\"EmphasisTypeItalic \">Thamnophis gigas</i><span>) is a state and federally threatened species that historically occurred in the wetland habitats of California&rsquo;s Great Central Valley. Despite the loss of 93&nbsp;% of historic wetlands throughout the Central Valley, giant gartersnakes continue to persist in relatively small, isolated patches of highly modified agricultural wetlands. Gathering information regarding genetic diversity and effective population size represents an essential component for conservation management programs aimed at this species. Previous mitochondrial sequence studies have revealed historical patterns of differentiation, yet little is known about contemporary population structure and diversity. On the basis of 15 microsatellite loci, we estimate population structure and compare indices of genetic diversity among populations spanning seven drainage basins within the Central Valley. We sought to understand how habitat loss may have affected genetic differentiation, genetic diversity and effective population size, and what these patterns suggest in terms of management and restoration actions. We recovered five genetic clusters that were consistent with regional drainage basins, although three northern basins within the Sacramento Valley formed a single genetic cluster. Our results show that northern drainage basin populations have higher connectivity than among central and southern basins populations, and that greater differentiation exists among the more geographically isolated populations in the central and southern portion of the species&rsquo; range. Genetic diversity measures among basins were significantly different, and were generally lower in southern basin populations. Levels of inbreeding and evidence of population bottlenecks were detected in about half the populations we sampled, and effective population size estimates were well below recommended minimum thresholds to avoid inbreeding. Efforts focused on maintaining and enhancing existing wetlands to facilitate dispersal between basins and increase local effective population sizes may be critical for these otherwise isolated populations.</span></p>","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-015-0720-6","usgsCitation":"Wood, D.A., Halstead, B., Casazza, M.L., Hansen, E.C., Wylie, G.D., and Vandergast, A.G., 2015, Defining population structure and genetic signatures of decline in the giant garter snake (<i>Thamnophis gigas</i>): implications for conserving threatened species within highly altered landscapes: Conservation Genetics, v. 16, no. 5, p. 1025-1039, https://doi.org/10.1007/s10592-015-0720-6.","productDescription":"15 p.","startPage":"1025","endPage":"1039","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062768","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":307719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-11","publicationStatus":"PW","scienceBaseUri":"55e57aace4b05561fa208688","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Eric C.","contributorId":146299,"corporation":false,"usgs":false,"family":"Hansen","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":16663,"text":"Eric C. Hansen Consulting","active":true,"usgs":false}],"preferred":false,"id":570291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wylie, Glenn D. 0000-0002-7061-6658 glenn_wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":3052,"corporation":false,"usgs":true,"family":"Wylie","given":"Glenn","email":"glenn_wylie@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570292,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":570287,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70146256,"text":"70146256 - 2015 - Delineation of fractures, foliation, and groundwater of the bedrock at a geothermal feasibility site on Roosevelt Island, New York County, New York","interactions":[],"lastModifiedDate":"2015-11-24T16:29:02","indexId":"70146256","displayToPublicDate":"2015-04-11T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Delineation of fractures, foliation, and groundwater of the bedrock at a geothermal feasibility site on Roosevelt Island, New York County, New York","docAbstract":"<p>Advanced borehole-geophysical methods were used to investigate the hydrogeology of the crystalline bedrock in three boreholes on Roosevelt Island, New York County, New York. Cornell University was evaluating the feasibility of using geothermal energy for a future campus at the site. The borehole-logging techniques were used to delineate bedrock fractures, foliation, and groundwater-flow zones of the Fordham Gneiss in test boreholes at the site. Three fracture populations dominated by small (0.04 in or less) fractures were delineated in the three boreholes. A sub-horizontal population with low to moderate dipping fractures, a northeast dipping population with moderate to high angle fractures, and a small northwest dipping high angle fracture population. One large southwest dipping transmissive fracture underlies the entire study area with a mean dip azimuth of 235&ordm; southwest and a dip angle of 31&ordm; (N325&ordm;W 31&ordm;SW). The mean foliation dip azimuth was 296&ordm; northwest with a mean dip angle of 73&ordm; (N26&ordm;E 73&ordm;NW). Groundwater appears to flow through a network of fractures dominated by a large fracture underlying the site that is affected by tidal variations from the nearby East River. The total number of fractures penetrated by each borehole was 95, 63, and 68, with fracture indices of 0.26, 0.20, and 0.20 in GT-1 (NY292), GT-2 (NY293), and GT-3 (NY294), respectively. Aquifer test data indicate the specific capacity of boreholes GT-1 (NY292), GT-2 (NY293), and GT-3 (NY294) was 1.9, 1.5, and 3.7 gal/min/ft, respectively. The large contribution of flow from the leaking casing in borehole GT-3 (NY294) caused the doubling in specific capacity compared to boreholes GT-1 (NY292) and GT-2 (NY293). The transmissivities of the large fracture intersected by the three boreholes tested (GT-1, GT-2, and GT-3), calculated from aquifer-test analyses of time-drawdown data and flowmeter differencing, were 133, 124, and 65 feet squared per day (ft2/d), respectively. Gringarten analysis indicated the large fracture intersects a low transmissivity boundary or distant fracture network with an average transmissivity of 69 ft2/d, this distant hydraulic boundary averages about 200 ft away from boreholes GT-1 and GT-2. Field measurements of specific conductance of the three boreholes under ambient conditions at the site indicate an increase in conductivity toward the southwest part of the site. Specific conductance was 5, 6, and 23 millisiemens per centimeter (mS/cm) in boreholes GT-2, GT-3, and GT-1, respectively. Three borehole radar reflection logs collected at each of the boreholes indicated increased penetration with depth and the large fracture intersecting all three boreholes was imaged as far as 80 ft from the boreholes. A borehole radar attenuation tomogram from GT-1 to GT-2 indicated the large fracture intersected by the boreholes extends between the boreholes with a low angle southwest dip.</p>","conferenceTitle":"22nd Conference on the Geology of Long Island and Metropolitan New York","conferenceDate":"April 11, 2015","conferenceLocation":"Stony Brook, NY","language":"English","collaboration":"Cornell University; USGS","usgsCitation":"Stumm, F., Chu, A., Como, M.D., Noll, M.L., and Joesten, P.K., 2015, Delineation of fractures, foliation, and groundwater of the bedrock at a geothermal feasibility site on Roosevelt Island, New York County, New York, 22nd Conference on the Geology of Long Island and Metropolitan New York, Stony Brook, NY, April 11, 2015, 23 p.","productDescription":"23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063658","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":311700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Roosevelt Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.94210815429688,\n              40.77274188001071\n            ],\n            [\n              -73.95343780517578,\n              40.761300880922235\n            ],\n            [\n              -73.95978927612305,\n              40.75297891717686\n            ],\n            [\n              -73.96150588989258,\n              40.750768220446936\n            ],\n            [\n              -73.96150588989258,\n              40.748947591479705\n            ],\n            [\n              -73.95463943481445,\n              40.75440932883489\n            ],\n            [\n              -73.9493179321289,\n              40.76091081214379\n            ],\n            [\n              -73.94056320190428,\n              40.770011820529064\n            ],\n            [\n              -73.93918991088867,\n              40.77248187917859\n            ],\n            [\n              -73.94039154052734,\n              40.77352187640244\n            ],\n            [\n              -73.94210815429688,\n              40.77274188001071\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5655983ae4b071e7ea53def9","contributors":{"authors":[{"text":"Stumm, Frederick 0000-0002-5388-8811 fstumm@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-8811","contributorId":1077,"corporation":false,"usgs":true,"family":"Stumm","given":"Frederick","email":"fstumm@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chu, Anthony 0000-0001-8623-2862 achu@usgs.gov","orcid":"https://orcid.org/0000-0001-8623-2862","contributorId":2517,"corporation":false,"usgs":true,"family":"Chu","given":"Anthony","email":"achu@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Como, Michael D. 0000-0002-7911-5390 mcomo@usgs.gov","orcid":"https://orcid.org/0000-0002-7911-5390","contributorId":4651,"corporation":false,"usgs":true,"family":"Como","given":"Michael","email":"mcomo@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noll, Michael L. 0000-0003-2050-3134 mnoll@usgs.gov","orcid":"https://orcid.org/0000-0003-2050-3134","contributorId":4652,"corporation":false,"usgs":true,"family":"Noll","given":"Michael","email":"mnoll@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joesten, Peter K. pjoesten@usgs.gov","contributorId":1929,"corporation":false,"usgs":true,"family":"Joesten","given":"Peter","email":"pjoesten@usgs.gov","middleInitial":"K.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70125112,"text":"tm14A1 - 2015 - Scoops3D: software to analyze 3D slope stability throughout a digital landscape","interactions":[],"lastModifiedDate":"2023-05-16T14:19:41.323077","indexId":"tm14A1","displayToPublicDate":"2015-04-10T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"14-A1","title":"Scoops3D: software to analyze 3D slope stability throughout a digital landscape","docAbstract":"<p><span>The computer program, Scoops3D, evaluates slope stability throughout a digital landscape represented by a digital elevation model (DEM). The program uses a three-dimensional (3D) method of columns approach to assess the stability of many (typically millions) potential landslides within a user-defined size range. For each potential landslide (or failure), Scoops3D assesses the stability of a rotational, spherical slip surface encompassing many DEM cells using a 3D version of either Bishop&rsquo;s simplified method or the Ordinary (Fellenius) method of limit-equilibrium analysis. Scoops3D has several options for the user to systematically and efficiently search throughout an entire DEM, thereby incorporating the effects of complex surface topography. In a thorough search, each DEM cell is included in multiple potential failures, and Scoops3D records the lowest stability (factor of safety) for each DEM cell, as well as the size (volume or area) associated with each of these potential landslides. It also determines the least-stable potential failure for the entire DEM. The user has a variety of options for building a 3D domain, including layers or full 3D distributions of strength and pore-water pressures, simplistic earthquake loading, and unsaturated suction conditions. Results from Scoops3D can be readily incorporated into a geographic information system (GIS) or other visualization software. This manual includes information on the theoretical basis for the slope-stability analysis, requirements for constructing and searching a 3D domain, a detailed operational guide (including step-by-step instructions for using the graphical user interface [GUI] software, Scoops3D-i) and input/output file specifications, practical considerations for conducting an analysis, results of verification tests, and multiple examples illustrating the capabilities of Scoops3D. Easy-to-use software installation packages are available for the Windows or Macintosh operating systems; these packages install the compiled Scoops3D program, the GUI (Scoops3D-i), and associated documentation. Several Scoops3D examples, including all input and output files, are available as well. The source code is written in the Fortran 90 language and can be compiled to run on any computer operating system with an appropriate compiler.</span></p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Modeling methods in Book 14 <i>Landslide and Debris-Flow Assessment</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm14A1","usgsCitation":"Reid, M.E., Christian, S.B., Brien, D.L., and Henderson, S.T., 2015, Scoops3D: software to analyze 3D slope stability throughout a digital landscape: U.S. Geological Survey Techniques and Methods 14-A1, Report: xiv, 218 p.; Readme; Windows install package; Mac install disk image; examples folder, https://doi.org/10.3133/tm14A1.","productDescription":"Report: xiv, 218 p.; Readme; Windows install package; Mac install disk image; examples folder","numberOfPages":"236","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049458","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":299583,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm14A1.jpg"},{"id":299582,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/14/a01/downloads/tm14-a1_Scoops3Dexamples_1.3.zip","text":"Examples folder","size":"35 MB"},{"id":299580,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/14/a01/downloads/Scoops3D_1.3.01win_installer.exe","text":"Windows install package version 1.3.01","size":"35 MB"},{"id":299579,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/tm/14/a01/downloads/tm14-a1_ReadMe_Scoops3D_1.3.01.txt","size":"15 KB","linkFileType":{"id":2,"text":"txt"}},{"id":299578,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/14/a01/pdf/tm14-a1.pdf","size":"18.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":299581,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/14/a01/downloads/tm14-a1_Scoops3D_1.1mac.dmg","text":"Mac install disk image version 1.1","size":"51 MB"},{"id":299577,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/14/a01/"}],"publicComments":"This report is Chapter 1 of Section A: Modeling methods in Book 14 <i>Landslide and Debris-Flow Assessment</i>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5528e61de4b026915857cb00","contributors":{"authors":[{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":544604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christian, Sarah B.","contributorId":20739,"corporation":false,"usgs":true,"family":"Christian","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":544605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brien, Dianne L. dbrien@usgs.gov","contributorId":3296,"corporation":false,"usgs":true,"family":"Brien","given":"Dianne","email":"dbrien@usgs.gov","middleInitial":"L.","affiliations":[{"id":363,"text":"Landslide Hazards Program","active":false,"usgs":true}],"preferred":false,"id":544606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henderson, Scott T.","contributorId":119002,"corporation":false,"usgs":true,"family":"Henderson","given":"Scott","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":544607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70142432,"text":"sir20155041 - 2015 - Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon","interactions":[],"lastModifiedDate":"2015-04-09T16:21:03","indexId":"sir20155041","displayToPublicDate":"2015-04-09T17:15:00","publicationYear":"2015","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":"2015-5041","title":"Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon","docAbstract":"<p>This report presents Phase 2 of the review and development of the mass balance water-quality model, originally developed in 2001, that guided establishment of the phosphorus (P) total maximum daily load (TMDL) for Upper Klamath and Agency Lakes, Oregon. The purpose of Phase 2 was to incorporate a longer (19-year) set of external phosphorus loading data into the lake TMDL model than had originally been available, and to develop a proof-of-concept method for modeling algal mortality and the consequent decrease in chlorophyll <i>a</i> that had not been possible with the 2001 TMDL model formulation.</p>\n<p>Using the extended 1991&ndash;2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll <i>a</i> model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model&nbsp;predictions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155041","usgsCitation":"Wherry, S.A., Wood, T.M., and Anderson, C.W., 2015, Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon: U.S. Geological Survey Scientific Investigations Report 2015-5041, vii, 55 p., https://doi.org/10.3133/sir20155041.","productDescription":"vii, 55 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057247","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":299551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155041.JPG"},{"id":299549,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5041/"},{"id":299550,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5041/pdf/sir2015-5041.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.86927795410156,\n              42.44778143462245\n            ],\n            [\n              -121.81022644042969,\n              42.38137240541685\n            ],\n       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swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":139268,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544543,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70140562,"text":"ofr20151004 - 2015 - A case study of data integration for aquatic resources using semantic web technologies","interactions":[],"lastModifiedDate":"2018-08-10T16:42:35","indexId":"ofr20151004","displayToPublicDate":"2015-04-09T16:00:00","publicationYear":"2015","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":"2015-1004","title":"A case study of data integration for aquatic resources using semantic web technologies","docAbstract":"<p>Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151004","usgsCitation":"Gordon, J.M., Chkhenkeli, N., Govoni, D.L., Lightsom, F.L., Ostroff, A.C., Schweitzer, P.N., Thongsavanh, P., Varanka, D.E., and Zednik, S., 2015, A case study of data integration for aquatic resources using semantic web technologies: U.S. Geological Survey Open-File Report 2015-1004, v, 55 p., https://doi.org/10.3133/ofr20151004.","productDescription":"v, 55 p.","startPage":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045446","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and 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Synthesis","active":true,"usgs":true}],"preferred":false,"id":544519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chkhenkeli, Nina nchkhenkeli@usgs.gov","contributorId":5904,"corporation":false,"usgs":true,"family":"Chkhenkeli","given":"Nina","email":"nchkhenkeli@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":544522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Govoni, David L. dgovoni@usgs.gov","contributorId":5192,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":544526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lightsom, Frances L. 0000-0003-4043-3639 flightsom@usgs.gov","orcid":"https://orcid.org/0000-0003-4043-3639","contributorId":1535,"corporation":false,"usgs":true,"family":"Lightsom","given":"Frances","email":"flightsom@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ostroff, Andrea C. 0000-0002-1632-6174 aostroff@usgs.gov","orcid":"https://orcid.org/0000-0002-1632-6174","contributorId":2756,"corporation":false,"usgs":true,"family":"Ostroff","given":"Andrea","email":"aostroff@usgs.gov","middleInitial":"C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":544523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schweitzer, Peter N. pschweitzer@usgs.gov","contributorId":5905,"corporation":false,"usgs":true,"family":"Schweitzer","given":"Peter","email":"pschweitzer@usgs.gov","middleInitial":"N.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":544524,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thongsavanh, Phethala thongsav@usgs.gov","contributorId":5154,"corporation":false,"usgs":true,"family":"Thongsavanh","given":"Phethala","email":"thongsav@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":544525,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":544521,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zednik, Stephan","contributorId":139117,"corporation":false,"usgs":false,"family":"Zednik","given":"Stephan","email":"","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":544527,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70141356,"text":"sir20155028 - 2015 - New argon-argon (<sup>40</sup>Ar/<sup>39</sup>Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2015-04-09T09:06:19","indexId":"sir20155028","displayToPublicDate":"2015-04-09T10:00:00","publicationYear":"2015","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":"2015-5028","title":"New argon-argon (<sup>40</sup>Ar/<sup>39</sup>Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho","docAbstract":"<p>In 2011, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, collected samples for 12 new argon-argon radiometric ages from eastern Snake River Plain olivine tholeiite basalt flows in the subsurface at the Idaho National Laboratory. The core samples were collected from flows that had previously published paleomagnetic data. Samples were sent to Rutgers University for argon-argon radiometric dating analyses.</p>\n<p>Paleomagnetic and stratigraphic data were used to constrain the results of the age dating experiments to derive the preferred age for each basalt flow. Knowledge of the ages of subsurface basalt flows is needed to improve numerical models of groundwater flow and contaminant transport in the eastern Snake River Plain aquifer. This could be accomplished by increasing the ability to correlate basalt flow from corehole to corehole in the subsurface. The age of basalt flows also can be used in volcanic recurrence and landscape evolution studies that are important to better understand future hazards that could occur at the Idaho National Laboratory.</p>\n<p>Results indicate that ages ranged from 60 &plusmn; 16 thousand years ago for Quaking Aspen Butte to 621 &plusmn; 9 thousand years ago for State Butte.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155028","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Hodges, M., Turrin, B.D., Champion, D.E., and Swisher, C.C., 2015, New argon-argon (<sup>40</sup>Ar/<sup>39</sup>Ar) radiometric age dates from selected subsurface basalt flows at the Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2015-5028, v, 25 p.; Appendix, https://doi.org/10.3133/sir20155028.","productDescription":"v, 25 p.; Appendix","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-044883","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":299524,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5028/"},{"id":299528,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5028/pdf/sir2015-5028.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299529,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5028/download/sir2015-5028_AppendixA.zip","text":"Appendix A","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix A"},{"id":299530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155028.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.345703125,\n              43.389081939117496\n            ],\n            [\n              -114.345703125,\n              44.38669150215206\n            ],\n            [\n              -112.5,\n              44.38669150215206\n            ],\n            [\n              -112.5,\n              43.389081939117496\n            ],\n            [\n              -114.345703125,\n              43.389081939117496\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5527949de4b026915857c83c","contributors":{"authors":[{"text":"Hodges, Mary K. V. 0000-0001-8708-0354 mkhodges@usgs.gov","orcid":"https://orcid.org/0000-0001-8708-0354","contributorId":3023,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K. V.","email":"mkhodges@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turrin, Brent D.","contributorId":139307,"corporation":false,"usgs":false,"family":"Turrin","given":"Brent","email":"","middleInitial":"D.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":544467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":544469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swisher, Carl C. 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,{"id":70134309,"text":"pp1807 - 2015 - Revised hydrogeologic framework of the Floridan aquifer system in Florida and parts of Georgia, Alabama, and South Carolina","interactions":[],"lastModifiedDate":"2019-02-19T14:35:30","indexId":"pp1807","displayToPublicDate":"2015-04-08T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1807","title":"Revised hydrogeologic framework of the Floridan aquifer system in Florida and parts of Georgia, Alabama, and South Carolina","docAbstract":"<p><span>The hydrogeologic framework for the Floridan aquifer system has been revised throughout its extent in Florida and parts of Georgia, Alabama, and South Carolina. The updated framework generally conforms to the original framework established by the U.S. Geological Survey in the 1980s, except for adjustments made to the internal boundaries of the Upper and Lower Floridan aquifers and the individual higher and contrasting lower permeability zones within these aquifers. The system behaves as one aquifer over much of its extent; although subdivided vertically into two aquifer units, the Upper and Lower Floridan aquifers. In the previous framework, discontinuous numbered middle confining units (MCUI&ndash;VII) were used to subdivide the system. In areas where less-permeable rocks do not occur within the middle part of the system, the system was previously considered one aquifer and named the Upper Floridan aquifer. In intervening years, more detailed data have been collected in local areas, resulting in some of the same lithostratigraphic units in the Floridan aquifer system being assigned to the Upper or Lower Floridan aquifer in different parts of the State of Florida. Additionally, some of the numbered middle confining units are found to have hydraulic properties within the same order of magnitude as the aquifers. A new term &ldquo;composite unit&rdquo; is introduced for lithostratigraphic units that cannot be defined as either a confining or aquifer unit over their entire extent. This naming convention is a departure from the previous framework, in that stratigraphy is used to consistently subdivide the aquifer system into upper and lower aquifers across the State of Florida. This lithostratigraphic mapping approach does not change the concept of flow within the system. The revised boundaries of the Floridan aquifer system were mapped by considering results from local studies and regional correlations of lithostratigraphic and hydrogeologic units or zones. Additional zones within the aquifers have been incorporated into the framework to allow finer delineation of permeability variations within the aquifer system. These additional zones can be used to progressively divide the system for assessing groundwater and surface-water interaction, saltwater intrusion, and offshore movement of groundwater at greater detail if necessary. The lateral extent of the updip boundary of the Floridan aquifer system is modified from previous work based on newer data and inclusion of parts of the updip clastic facies. The carbonate and clastic facies form a gradational sequence, generally characterized by limestone of successively younger units that extend progressively farther updip. Because of the gradational nature of the carbonate-clastic sequence, some of the updip clastic aquifers have been included in the Floridan aquifer system, the Southeastern Coastal Plain aquifer system, or both. Thus, the revised updip limit includes some of these clastic facies. Additionally, the updip limit of the most productive part of the Floridan aquifer system was revised and indicates the approximate updip limit of the carbonate facies. The extent and altitude of the freshwater-saltwater interface in the aquifer system has been mapped to define the freshwater part of the flow system.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1807","collaboration":"Groundwater Resources Program","usgsCitation":"Williams, L.J., and Kuniansky, E.L., 2016, Revised hydrogeologic framework of the Floridan aquifer system in Florida and parts of Georgia, Alabama, and South Carolina (ver. 1.1, March 2016): U.S. Geological Survey Professional Paper 1807, 140 p., 23 pls., https://dx.doi.org/10.3133/pp1807.","productDescription":"Report: xii, 140 p.; 23 Plates: 32.5 x 30.0 inches or smaller","numberOfPages":"156","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-032570","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":501285,"rank":9,"type":{"id":30,"text":"Data 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Plates"},{"id":299499,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1807/pdf/pp1807.pdf","text":"Report","size":"20.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":361352,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/760/","text":"Data Series 760","linkHelpText":"- Companion Report - Geophysical Log Database for the Floridan Aquifer System and Southeastern Coastal Plain Aquifer System in Florida and Parts of Georgia, Alabama, and South Carolina"},{"id":299512,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/0926","text":"Data Series 926","description":"Data Series 926","linkHelpText":"- Companion Report - Digital Surfaces and Thicknesses of Selected Hydrogeologic Units of the Floridan Aquifer System in Florida and Parts of Georgia, Alabama, and South Carolina"},{"id":318430,"rank":8,"type":{"id":25,"text":"Version 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href=\"http://ga.water.usgs.gov/\">http://ga.water.usgs.gov/</a></p>","publishedDate":"2015-04-08","revisedDate":"2016-03-01","noUsgsAuthors":false,"publicationDate":"2015-04-08","publicationStatus":"PW","scienceBaseUri":"5526431fe4b026915857c638","contributors":{"authors":[{"text":"Williams, Lester J. lesterw@usgs.gov","contributorId":2395,"corporation":false,"usgs":true,"family":"Williams","given":"Lester","email":"lesterw@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":544407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's 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,{"id":70148104,"text":"70148104 - 2015 - Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta","interactions":[],"lastModifiedDate":"2018-09-25T11:04:36","indexId":"70148104","displayToPublicDate":"2015-04-08T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta","docAbstract":"<p>Juvenile Chinook Salmon Oncorhynchus tshawytscha emigrating from natal tributaries of the Sacramento River, California, must negotiate the Sacramento-San Joaquin River Delta (hereafter, the Delta), a complex network of natural and man-made channels linking the Sacramento River with San Francisco Bay. Fish that enter the interior and southern Delta&mdash;the region to the south of the Sacramento River where water pumping stations are located&mdash;survive at a lower rate than fish that use alternative migration routes. Consequently, total survival decreases as the fraction of the population entering the interior Delta increases, thus spurring management actions to reduce the proportion of fish that are entrained into the interior Delta. To better inform management actions, we modeled entrainment probability as a function of hydrodynamic variables. We fitted alternative entrainment models to telemetry data that identified when tagged fish in the Sacramento River entered two river channels leading to the interior Delta (Georgiana Slough and the gated Delta Cross Channel). We found that the probability of entrainment into the interior Delta through both channels depended strongly on the river flow and tidal stage at the time of fish arrival at the river junction. Fish that arrived during ebb tides had a low entrainment probability, whereas fish that arrived during flood tides (i.e., when the river's flow was reversed) had a high probability of entering the interior Delta. We coupled our entrainment model with a flow simulation model to evaluate the effect of nighttime closures of the Delta Cross Channel gates on the daily probability of fish entrainment into the interior Delta. Relative to 24-h gate closures, nighttime closures increased daily entrainment probability by 3 percentage points on average if fish arrived at the river junction uniformly throughout the day and by only 1.3 percentage points if 85% of fish arrived at night. We illustrate how our model can be used to evaluate the effects of alternative water management actions on fish entrainment into the interior Delta.</p>","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2014.1001038","usgsCitation":"Perry, R.W., Brandes, P., Burau, J.R., Sandstrom, P.T., and Skalski, J.R., 2015, Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta: Transactions of the American Fisheries Society, v. 144, no. 3, p. 445-455, https://doi.org/10.1080/00028487.2014.1001038.","productDescription":"11 p.","startPage":"445","endPage":"455","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056864","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":300640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.91734313964844,\n              38.05403884511629\n            ],\n            [\n              -121.89743041992189,\n              38.053227812983906\n            ],\n            [\n              -121.86927795410156,\n              38.07079816372681\n            ],\n            [\n              -121.8651580810547,\n              38.07431172756913\n            ],\n            [\n              -121.84078216552733,\n              38.079446632654914\n           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jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandstrom, Philip T. psandstrom@usgs.gov","contributorId":5907,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Philip","email":"psandstrom@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":547407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skalski, John R.","contributorId":94131,"corporation":false,"usgs":false,"family":"Skalski","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":547408,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70139404,"text":"sir20145224 - 2015 - Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","interactions":[],"lastModifiedDate":"2018-03-21T15:43:13","indexId":"sir20145224","displayToPublicDate":"2015-04-08T10:30:00","publicationYear":"2015","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":"2014-5224","title":"Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","docAbstract":"<p>From 1966 to 2002, activities at the Standard Chlorine of Delaware chemical facility in New Castle County, Delaware resulted in the contamination of groundwater, soils, and wetland sediment. In 2005, the U.S. Geological Survey (USGS), in partnership with the U.S. Environmental Protection Agency, Region 3, and the Delaware Department of Natural Resources and Environmental Control began a multi-year investigation of the hydrogeologic framework and hydrology of the confined aquifer system. The goals of the ongoing study at the site (the Potomac Aquifer Study) are to determine the hydraulic connection between the Columbia and Potomac aquifers, determine the direction of groundwater flow in the Potomac aquifer, and identify factors affecting the fate of contaminated groundwater. This report describes progress made towards these goals based on available data collected through September 2012.</p>\n<p>The regional hydrogeologic framework indicates that the site is underlain by Coastal Plain sediments of the Columbia, Merchantville, and Potomac Formations. Two primary aquifers underlying the site, the Columbia and the upper Potomac, are separated by the Merchantville Formation confining unit. Local groundwater flow in the surficial (Columbia) aquifer is controlled by topography and generally flows northward and discharges to nearby surface water. Regional flow within the Potomac aquifer is towards the southeast, and is strongly influenced by major water withdrawals locally. Previous investigations at the site indicated that contaminants, primarily benzene and chlorinated benzene compounds, were present in the Columbia aquifer in most locations; however, there were only limited detections in the upper Potomac aquifer as of 2004. From 2005 through 2012, the USGS designed a monitoring network, assisted with exploratory drilling, collected data at monitoring wells, conducted geophysical surveys, evaluated water-level responses in wells during pumping of a production well, and evaluated major aquifer withdrawals. Data collected through these efforts were used to refine the local conceptual flow system. The refined conceptual flow system for the site includes: (a) identification of gaps in confining units in the study area, (b) identification and correlation of multiple water-bearing sand intervals within the upper Potomac Formation, (c) connections between groundwater and surface water, (d) connections between shallow and deeper groundwater, (e) new water-level (or potentiometric surface) maps and inferred flow directions, and (f) identification of major local pumping well influences. The implications of the revised conceptual flow system on the occurrence and movement of site contaminants are that the resulting detection of contaminants in the upper Potomac aquifer at specific well locations can be attributed primarily to either advective lateral transport, direct vertical contaminant transport, or a combination of vertical and lateral movement resulting from changes in water withdrawal rates over time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145224","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Brayton, M.J., Cruz, R.M., Myers, L., Degnan, J.R., and Raffensperger, J.P., 2015, Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12: U.S. Geological Survey Scientific Investigations Report 2014-5224, vii, 61 p., https://doi.org/10.3133/sir20145224.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2012-09-30","ipdsId":"IP-059549","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":299486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145224.jpg"},{"id":299484,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5224/"},{"id":299485,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5224/pdf/sir2014-5224.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"State Plane Delaware Projection","datum":"North American Datum of 1983","country":"United States","state":"Delaware","county":"New Castle County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.60430526733398,\n              39.63187001350982\n            ],\n            [\n              -75.65872192382812,\n              39.637422462817\n            ],\n            [\n              -75.70489883422852,\n              39.60886226158157\n            ],\n            [\n              -75.71365356445311,\n              39.59464387992515\n            ],\n            [\n              -75.65108299255371,\n              39.55554482419571\n            ],\n            [\n              -75.59306144714355,\n              39.571623755318214\n            ],\n            [\n              -75.58670997619629,\n              39.579231826349016\n            ],\n            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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5526431de4b026915857c634","contributors":{"authors":[{"text":"Brayton, Michael J. mbrayton@usgs.gov","contributorId":2993,"corporation":false,"usgs":true,"family":"Brayton","given":"Michael","email":"mbrayton@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cruz, Roberto M. 0000-0003-1235-3295 rmcruz@usgs.gov","orcid":"https://orcid.org/0000-0003-1235-3295","contributorId":5757,"corporation":false,"usgs":true,"family":"Cruz","given":"Roberto","email":"rmcruz@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Luke lmyers@usgs.gov","contributorId":5758,"corporation":false,"usgs":true,"family":"Myers","given":"Luke","email":"lmyers@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":199119,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff","email":"jpraffen@usgs.gov","middleInitial":"P.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539392,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70141848,"text":"sir20155024 - 2015 - Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","interactions":[],"lastModifiedDate":"2015-04-15T08:44:40","indexId":"sir20155024","displayToPublicDate":"2015-04-08T10:00:00","publicationYear":"2015","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":"2015-5024","title":"Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","docAbstract":"<p>This report presents the results of a study to provide information on the hydrologic effects of potential 21st-century changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio (from Circleville, Ohio, to the headwaters). A precipitation-runoff model, calibrated on the basis of historical climate and streamflow data, was used to simulate the effects of climate change on streamflows and reservoir water levels at several locations in the basin. Two levels of simulations were done. The first level of simulation (level 1) accounted only for anticipated 21st-century changes in climate and operations of three City of Columbus upground reservoirs located in northwest Delaware County, Ohio. The second level of simulation (level 2) accounted for development-driven changes in land cover and water use in addition to changes in climate and reservoir operations.</p>\n<p>A statistical change-factor approach was used to construct future climate time series that were used in the precipitation-runoff model to compute time series of future streamflows and reservoir water levels. Monthly change factors were computed by determining differences or fractional changes between baseline historical climate time series and future climate time series consisting of outputs from selected global climate models that were included in the World Climate Research Programme&rsquo;s Coupled Model Intercomparison Project phase 3 (CMIP3). Eight sets of change factors were determined on the basis of outputs from four global climate models, each of which was run under two greenhouse-gas scenarios (the &ldquo;A1b&rdquo; and &ldquo;A2&rdquo; scenarios from the Intergovernmental Panel on Climate Change&rsquo;s 4th assessment). The 4 global climate models whose data were used in this study were selected to represent a wide range of potential climate outcomes as compared to the entire range of potential climate outcomes associated with the 16 global climate models represented in the CMIP3 multimodel dataset.</p>\n<p>Future land-cover and water-use data were estimated for use in the level-2 precipitation-runoff simulations to account for development-driven changes in land cover and water use. Future land-cover characteristics were estimated for selected future years based on population projections and zoning plans for communities in the basin. Future water-use data for major water suppliers and wastewater-treatment facilities were estimated from current per capita water use, population projections for 2035, and population projections for 2090 assuming full build-out. A statistical change-factor-based approach was used to estimate future water-use characteristics by major water suppliers and wastewater-treatment facilities on the basis of reference-period historical water uses. Annual change factors that were determined for future years other than 2035 and 2090 (when the change factors could be explicitly computed) were estimated by interpolating or extrapolating linearly in time. Water uses by entities other than major water suppliers and wastewater-treatment facilities were assumed to remain unchanged because of uncertainty about if and (or) how they might change.</p>\n<p>Results from the level-1 simulations were analyzed primarily to facilitate evaluation of climate-driven temporal changes in annual, seasonal, and monthly streamflow and water-level characteristics, as well as in maximum and minimum 7-, 30-, and 180-day average streamflow and reservoir water levels. Results from the level-2 simulations were analyzed to help evaluate and contrast (relative to level-1 results) the effects of the added development-related factors on maximums and minimum 7-, 30-, and 180-day average streamflows and reservoir water levels and duration characteristics of 7- and 30-day average streamflows and reservoir water levels. Results for 12 stream locations and 5 reservoirs in the Upper Scioto River Basin are presented primarily as a series of plots.</p>\n<p>Although it is beyond the scope of this study to address results in detail for each model-output location, selected results are discussed to illustrate potential uses and interpretations of the graph products provided in this report. In addition, general trends and patterns in streamflow and water-level characteristics are identified where possible.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155024","collaboration":"Prepared in cooperation with the Mid-Ohio Regional Planning Commission; the Ohio Water Development Authority; the City of Columbus, Ohio; and Del-Co Water Company","usgsCitation":"Ebner, A.D., Koltun, G., and Ostheimer, C., 2015, Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2015-5024, Report: vii, 34 p.; Appendixes A-G; Downloads Directory, https://doi.org/10.3133/sir20155024.","productDescription":"Report: vii, 34 p.; Appendixes A-G; Downloads Directory","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060946","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":299483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155024.jpg"},{"id":299479,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixe.pdf","text":"Appendix E","size":"1.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix E","linkHelpText":"Plots of seasonal maximum and minimum 7-, 30-, and 180-day average streamflows and water levels as a function of plotting year."},{"id":299480,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixf.pdf","text":"Appendix F","size":"214 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix F","linkHelpText":"Plots of simulated level-2 7-day running average streamflows and water levels as a function of exceedance quantile."},{"id":299478,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixd.pdf","text":"Appendix D","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix D","linkHelpText":"Plots of maximum and minimum 7-, 30-, and 180-day average streamflows and water levels as a function of plotting year."},{"id":299481,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixg.pdf","text":"Appendix G","size":"226 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix G","linkHelpText":"Plots of simulated level-2 30-day running average streamflows and water levels as a function of exceedance quantile."},{"id":299482,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/downloads","text":"Downloads Directory","size":"5.44 MB","description":"Downloads Directory","linkHelpText":"Contains Appendixes A-G ZIP file"},{"id":299473,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5024/"},{"id":299474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5024/pdf/sir2015-5024.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299475,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixa.pdf","text":"Appendix A","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix A","linkHelpText":"Description of the precipitation-runoff model."},{"id":299476,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixb.pdf","text":"Appendix B","size":"129 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix B","linkHelpText":"Plots of ensemble means of level-1 simulated annual mean streamflows and water levels as a function of time."},{"id":299477,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixc.pdf","text":"Appendix C","size":"1.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix C","linkHelpText":"Boxplots of the medians of site-, month-, and emission-specific level-1 ensemble mean streamflows and water levels as a function of epoch."}],"projection":"Universal Transverse Mercator projection, Zone 17","datum":"North American Datum of 1983","country":"United States","state":"Ohio","otherGeospatial":"Upper Scioto River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.72602081298828,\n              40.80497409762779\n            ],\n            [\n              -83.00823211669922,\n              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F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":1852,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","email":"gfkoltun@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostheimer, Chad J. ostheime@usgs.gov","contributorId":127446,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad J.","email":"ostheime@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544329,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155963,"text":"70155963 - 2015 - Developmental exposure to bisphenol A (BPA) alters sexual differentiation in painted turtles (Chrysemys picta)","interactions":[],"lastModifiedDate":"2018-08-09T12:43:43","indexId":"70155963","displayToPublicDate":"2015-04-08T03:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1738,"text":"General and Comparative Endocrinology","active":true,"publicationSubtype":{"id":10}},"title":"Developmental exposure to bisphenol A (BPA) alters sexual differentiation in painted turtles (Chrysemys picta)","docAbstract":"<p>Environmental chemicals can disrupt <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200004267\">endocrine signaling</a> and adversely impact sexual differentiation in wildlife. Bisphenol A (BPA) is an <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200003277\">estrogenic</a> chemical commonly found in a variety of habitats. In this study, we used painted turtles (<i>Chrysemys picta</i>), which have temperature-dependent sex determination (TSD), as an animal model for <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200013779\">ontogenetic</a> <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200010309\">endocrine disruption</a> by BPA. We hypothesized that BPA would override TSD and disrupt sexual development. We incubated farm-raised turtle eggs at the male-producing temperature (26&nbsp;&deg;C), randomly assigned individuals to treatment groups: control, vehicle control, <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200019383\">17&beta;-estradiol</a> (E2, 20&nbsp;ng/g-egg) or 0.01, 1.0, 100&nbsp;&mu;g&nbsp;BPA/g-egg and harvested tissues at hatch. Typical female gonads were present in 89% of the E2-treated &ldquo;males&rdquo;, but in none of the control males (<i>n</i>&nbsp;=&nbsp;35). Gonads of BPA-exposed turtles had varying amounts of ovarian-like cortical (OLC) tissue and disorganized testicular tubules in the medulla. Although the percentage of males with OLCs increased with BPA dose (BPA-low&nbsp;=&nbsp;30%, BPA-medium&nbsp;=&nbsp;33%, BPA-high&nbsp;=&nbsp;39%), this difference was not significant (<i>p</i>&nbsp;=&nbsp;0.85). In all three BPA treatments, <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200021360\">SOX9</a> patterns revealed disorganized medullary testicular tubules and &beta;-catenin expression in a thickened cortex. Liver <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200008069\">vitellogenin</a>, a female-specific liver protein commonly used as an exposure <a class=\"linkText\" href=\"http://www.sciencedirect.com/science/article/pii/S0016648015000933#200020754\">biomarker</a>, was not induced by any of the treatments. Notably, these results suggest that developmental exposure to BPA disrupts sexual differentiation in painted turtles. Further examination is necessary to determine the underlying mechanisms of sex reversal in reptiles and how these translate to EDC exposure in wild populations.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ygcen.2015.04.003","usgsCitation":"Jandegian, C.M., Deem, S.L., Bhandari, R.K., Holliday, C.M., Nicks, D., Rosenfeld, C.S., Selcer, K., Tillitt, D.E., vom Saal, F.S., Velez, V., Yang, Y., and Holliday, D.K., 2015, Developmental exposure to bisphenol A (BPA) alters sexual differentiation in painted turtles (Chrysemys picta): General and Comparative Endocrinology, v. 216, p. 77-85, https://doi.org/10.1016/j.ygcen.2015.04.003.","productDescription":"9 p.","startPage":"77","endPage":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061239","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":306671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfafe4b08400b1fe13e4","contributors":{"authors":[{"text":"Jandegian, Caitlin M. cjandegian@usgs.gov","contributorId":5941,"corporation":false,"usgs":true,"family":"Jandegian","given":"Caitlin","email":"cjandegian@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deem, Sharon L.","contributorId":139277,"corporation":false,"usgs":false,"family":"Deem","given":"Sharon","email":"","middleInitial":"L.","affiliations":[{"id":12719,"text":"Whitney R. Harris, World Ecology Center, Uni. of Missouri St. Louis","active":true,"usgs":false}],"preferred":false,"id":567437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhandari, Ramji K. rbhandari@usgs.gov","contributorId":5930,"corporation":false,"usgs":true,"family":"Bhandari","given":"Ramji","email":"rbhandari@usgs.gov","middleInitial":"K.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holliday, Casey M.","contributorId":146327,"corporation":false,"usgs":false,"family":"Holliday","given":"Casey","email":"","middleInitial":"M.","affiliations":[{"id":16670,"text":"Pathology and Anatomical Sciences, School of Medicine, University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicks, Diane 0000-0001-8080-2449 dnicks@usgs.gov","orcid":"https://orcid.org/0000-0001-8080-2449","contributorId":4299,"corporation":false,"usgs":true,"family":"Nicks","given":"Diane","email":"dnicks@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenfeld, Cheryl S.","contributorId":141188,"corporation":false,"usgs":false,"family":"Rosenfeld","given":"Cheryl","email":"","middleInitial":"S.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":567441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Selcer, Kyle","contributorId":146328,"corporation":false,"usgs":false,"family":"Selcer","given":"Kyle","email":"","affiliations":[{"id":16671,"text":"Biological Sciences, Duquesne University, Pittsburgh, PA","active":true,"usgs":false}],"preferred":false,"id":567442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567435,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"vom Saal, Fredrick S.","contributorId":146329,"corporation":false,"usgs":false,"family":"vom Saal","given":"Fredrick","email":"","middleInitial":"S.","affiliations":[{"id":16672,"text":"Biological Sciences, University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567443,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Velez, Vanessa vvelez@usgs.gov","contributorId":3588,"corporation":false,"usgs":true,"family":"Velez","given":"Vanessa","email":"vvelez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567444,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yang, Ying","contributorId":146330,"corporation":false,"usgs":false,"family":"Yang","given":"Ying","email":"","affiliations":[{"id":16673,"text":"Bond Life Sciences Center, University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567445,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Holliday, Dawn K.","contributorId":141187,"corporation":false,"usgs":false,"family":"Holliday","given":"Dawn","email":"","middleInitial":"K.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":567446,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70140547,"text":"70140547 - 2015 - Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers","interactions":[],"lastModifiedDate":"2018-08-10T15:46:12","indexId":"70140547","displayToPublicDate":"2015-04-07T23:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers","docAbstract":"<p><span>The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout&nbsp;</span><i>Salvelinus fontinalis</i><span>, Brown Trout&nbsp;</span><i>Salmo trutta</i><span>, Smallmouth Bass&nbsp;</span><i>Micropterus dolomieu</i><span>, panfishes (seven centrarchid species), and Walleye&nbsp;</span><i>Sander vitreus</i><span>&nbsp;by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22&ndash;56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.</span></p>","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2014.987887","usgsCitation":"Esselman, P.C., Stevenson, R.J., Lupi, F., Riseng, C.M., and Wiley, M., 2015, Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers: North American Journal of Fisheries Management, v. 35, no. 2, p. 302-320, https://doi.org/10.1080/02755947.2014.987887.","productDescription":"19 p.","startPage":"302","endPage":"320","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057022","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472157,"rank":0,"type":{"id":41,"text":"Open Access 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Jan","contributorId":139110,"corporation":false,"usgs":false,"family":"Stevenson","given":"R.","email":"","middleInitial":"Jan","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":540046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lupi, Frank","contributorId":87100,"corporation":false,"usgs":true,"family":"Lupi","given":"Frank","affiliations":[],"preferred":false,"id":540047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riseng, Catherine M.","contributorId":30144,"corporation":false,"usgs":true,"family":"Riseng","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":540049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiley, Michael J.","contributorId":30112,"corporation":false,"usgs":true,"family":"Wiley","given":"Michael J.","affiliations":[],"preferred":false,"id":540048,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70145259,"text":"70145259 - 2015 - RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)","interactions":[],"lastModifiedDate":"2017-10-12T20:04:28","indexId":"70145259","displayToPublicDate":"2015-04-07T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)","docAbstract":"<p>The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.</p>","language":"English","publisher":"European Geosciences Union","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.5194/gmd-8-865-2015","usgsCitation":"Long, A.J., 2015, RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15): Geoscientific Model Development, v. 8, p. 865-880, https://doi.org/10.5194/gmd-8-865-2015.","productDescription":"16 p.","startPage":"865","endPage":"880","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056483","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":472158,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-8-865-2015","text":"Publisher Index Page"},{"id":299446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-30","publicationStatus":"PW","scienceBaseUri":"5524f19ce4b027f0aee3d45d","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70144431,"text":"sir20155038 - 2015 - Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","interactions":[],"lastModifiedDate":"2015-04-06T15:06:47","indexId":"sir20155038","displayToPublicDate":"2015-04-06T15:00:00","publicationYear":"2015","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":"2015-5038","title":"Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","docAbstract":"<p>Groundwater recharge is one of the most difficult components of a water budget to ascertain, yet is an important boundary condition necessary for the quantification of water resources. In Minnesota, improved estimates of recharge are necessary because approximately 75 percent of drinking water and 90 percent of agricultural irrigation water in Minnesota are supplied from groundwater. The water that is withdrawn must be supplied by some combination of (1) increased recharge, (2) decreased discharge to streams, lakes, and other surface-water bodies, and (3) removal of water that was stored in the system. Recent pressure on groundwater resources has highlighted the need to provide more accurate recharge estimates for various tools that can assess the sustainability of long-term water use. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, used the Soil-Water-Balance model to calculate gridded estimates of potential groundwater recharge across Minnesota for 1996‒2010 at a 1-kilometer (0.621-mile) resolution. The potential groundwater recharge estimates calculated for Minnesota from the Soil-Water Balance model included gridded values (1-kilometer resolution) of annual mean estimates (that is, the means for individual years from 1996 through 2010) and mean annual estimates (that is, the mean for the 15-year period 1996&minus;2010).</p>\n<p>The Soil-Water-Balance model uses a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated on a daily basis. A key advantage of this approach includes the use of commonly available geographic information system data layers that incorporate land cover, soil properties, and daily meteorological data to produce temporally and spatially variable gridded estimates of potential recharge. The Soil-Water-Balance model was calibrated by using a combination of parameter estimation techniques, making manual adjustments of model parameters, and using parameter values from previously published Soil-Water-Balance models. Each calibration simulation compared the potential recharge estimate from the model against base-flow estimates derived from three separate hydrograph separation techniques. A total of 35 Minnesota watersheds were selected for the model calibration.</p>\n<p>Meteorological data necessary for the model included daily precipitation, minimum daily temperature, and maximum daily temperature. All of the meteorological data were provided by the Daymet dataset, which included daily continuous surfaces of key climatological data. Land-cover data were provided by the 2001 and 2006 National Land Cover Database: the 2001 classification was used from 1994 through 2003, and the 2006 classification was used from 2004 through 2010. Soil data used in the model included hydrologic soils group and the available soil-water capacity. These soil data were obtained from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database.</p>\n<p>The statewide mean annual potential recharge rate from 1996&ndash;2010 was 4.9 inches per year. Potential recharge estimates increased from west to east across Minnesota. The mean annual potential recharge estimates across Minnesota at a 1-km resolution for the overall simulation period (1996&ndash;2010) ranged from less than 0.1 to 17.8 inches per year. Some of the lowest potential recharge rates for the simulation period were in the Red River of the North Basin of northwestern Minnesota, and generally were between 1.0 and 1.5 inches per year. The highest potential recharge rates were in northeastern Minnesota and the Anoka Sand Plain in central Minnesota. Eighty-eight percent of the potential recharge rates (by grid cell) were between 2 and 8 inches per year from 1996&ndash;2010. Only about 3 percent of all the potential recharge estimates (by grid cell) were less than 2 inches per year, and 9 percent of estimates were greater than 8 inches per year.</p>\n<p>On an annual basis, however, potential recharge rates were as high as 27.2 inches per year. The highest annual mean recharge estimate across the State was for 2010, and the lowest mean recharge estimate was for 2003. Although precipitation variability partially explained the annual differences in potential recharge estimates, precipitation alone did not account for these differences, and other factors such as antecedent moisture conditions likely were important. Also, because precipitation gradients across the State can vary from year to year, the dominant land-cover class and hydrologic soil group combinations for a particular region had a large effect on the resulting potential recharge value. During 1996&ndash;2010, April had the greatest monthly mean potential recharge compared to all other months, accounting for a mean of 30 percent of annual potential recharge in this single month.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155038","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Smith, E.A., and Westenbroek, S.M., 2015, Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010: U.S. Geological Survey Scientific Investigations Report 2015-5038, vii, 85 p., https://doi.org/10.3133/sir20155038.","productDescription":"vii, 85 p.","startPage":"85","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-034584","costCenters":[{"id":392,"text":"Minnesota Water Science 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,{"id":70175912,"text":"70175912 - 2015 - Near-surface versus fault zone damage following the 1999 Chi-Chi earthquake: Observation and simulation of repeating earthquakes","interactions":[],"lastModifiedDate":"2016-08-20T16:25:32","indexId":"70175912","displayToPublicDate":"2015-04-06T08:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Near-surface versus fault zone damage following the 1999 Chi-Chi earthquake: Observation and simulation of repeating earthquakes","docAbstract":"<p><span>We observe crustal damage and its subsequent recovery caused by the 1999&thinsp;</span><i>M</i><span>7.6 Chi-Chi earthquake in central Taiwan. Analysis of repeating earthquakes in Hualien region, ~70&thinsp;km east of the Chi-Chi earthquake, shows a remarkable change in wave propagation beginning in the year 2000, revealing damage within the fault zone and distributed across the near surface. We use moving window cross correlation to identify a dramatic decrease in the waveform similarity and delays in the&nbsp;</span><i>S</i><span>&nbsp;wave coda. The maximum delay is up to 59&thinsp;ms, corresponding to a 7.6% velocity decrease averaged over the wave propagation path. The waveform changes on either side of the fault are distinct. They occur in different parts of the waveforms, affect different frequencies, and the size of the velocity reductions is different. Using a finite difference method, we simulate the effect of postseismic changes in the wavefield by introducing&nbsp;</span><i>S</i><span>&nbsp;wave velocity anomaly in the fault zone and near the surface. The models that best fit the observations point to pervasive damage in the near surface and deep, along-fault damage at the time of the Chi-Chi earthquake. The footwall stations show the combined effect of near-surface and the fault zone damage, where the velocity reduction (2&ndash;7%) is twofold to threefold greater than the fault zone damage observed in the hanging wall stations. The physical models obtained here allow us to monitor the temporal evolution and recovering process of the Chi-Chi fault zone damage.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JB011719","usgsCitation":"Chen, K.H., Furumura, T., and Rubinstein, J.L., 2015, Near-surface versus fault zone damage following the 1999 Chi-Chi earthquake: Observation and simulation of repeating earthquakes: Journal of Geophysical Research B: Solid Earth, v. 120, no. 4, p. 2426-2445, https://doi.org/10.1002/2014JB011719.","productDescription":"20 p.","startPage":"2426","endPage":"2445","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060456","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":472159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014jb011719","text":"Publisher Index Page"},{"id":327125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Taiwan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              120,\n              22\n            ],\n            [\n              120,\n              25\n            ],\n            [\n              122,\n              25\n            ],\n            [\n              122,\n              22\n            ],\n            [\n              120,\n              22\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-06","publicationStatus":"PW","scienceBaseUri":"57b97f28e4b03fd6b7db87d1","contributors":{"authors":[{"text":"Chen, Kate Huihsuan","contributorId":173903,"corporation":false,"usgs":false,"family":"Chen","given":"Kate","email":"","middleInitial":"Huihsuan","affiliations":[{"id":27317,"text":"Department of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan","active":true,"usgs":false}],"preferred":false,"id":646543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furumura, Takashi","contributorId":173904,"corporation":false,"usgs":false,"family":"Furumura","given":"Takashi","email":"","affiliations":[{"id":27318,"text":"Earthquake Research Institute, The University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":646544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":646542,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70145260,"text":"70145260 - 2015 - Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","interactions":[],"lastModifiedDate":"2015-11-23T15:30:52","indexId":"70145260","displayToPublicDate":"2015-04-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","docAbstract":"<p>Pyrite and other minerals containing sulfur and trace metals occur in several rock formations throughout Middle and East Tennessee. Pyrite (FeS2) weathers in the presence of oxygen and water to form iron hydroxides and sulfuric acid. The weathering and interaction of the acid on the rocks and other minerals at road cuts can result in drainage with low pH (&lt; 4) and high concentrations of trace metals. Acid-rock drainage can cause environmental problems and damage transportation infrastructure. The formation and remediation of acid-drainage from roads cuts has not been researched as thoroughly as acid-mine drainage. The U.S Geological Survey, in cooperation with the Tennessee Department of Transportation, is conducting an investigation to better understand the geologic, hydrologic, and biogeochemical factors that control acid formation at road cuts. Road cuts with the potential for acid-rock drainage were identifed and evaluated in Middle and East Tennessee. The pyrite-bearing formations evaluated were the Chattanooga Shale (Devonian black shale), the Fentress Formation (coal-bearing), and the Precambrian Anakeesta Formation and similar Precambrian rocks. Conceptual models of the formation and transport of acid-rock drainage (ARD) from road cuts were developed based on the results of a literature review, site reconnaissance, and the initial rock and water sampling. The formation of ARD requires a combination of hydrologic, geochemical, and microbial interactions which affect drainage from the site, acidity of the water, and trace metal concentrations. The basic modes of ARD formation from road cuts are; 1 - seeps and springs from pyrite-bearing formations and 2 - runoff over the face of a road cut in a pyrite-bearing formation. Depending on site conditions at road cuts, the basic modes of ARD formation can be altered and the additional modes of ARD formation are; 3 - runoff over and through piles of pyrite-bearing material, either from construction or breakdown material weathered from shale, and 4 - the deposition of secondary-sulfate minerals can store trace metals and, during rainfall, result in increased acidity and higher concentrations of trace metals in storm runoff. Understanding the factors that control ARD formation and transport are key to addressing the problems associated with the movement of ARD from the road cuts to the environment. The investigation will provide the Tennessee Department of Transportation with a regional characterization of ARD and provide insights into the geochemical and biochemical attributes for the control and remediation of ARD from road cuts.</p>","largerWorkTitle":"Proceedings of the 2015 Tennessee Water Resources Symposium","conferenceTitle":"2015 Tennessee Water Resources Symposium","conferenceDate":"April 1-3, 2015","conferenceLocation":"Montgomery Bell State Park Burns, Tennessee","language":"English","publisher":"Tennessee Section of the American Water Resources Association","collaboration":"Tenn. Department of Transportation","usgsCitation":"Bradley, M., Worland, S., and Byl, T., 2015, Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee, <i>in</i> Proceedings of the 2015 Tennessee Water Resources Symposium, Montgomery Bell State Park Burns, Tennessee, April 1-3, 2015, p. 2C-8-2C-9.","productDescription":"1 p.","startPage":"2C-8","endPage":"2C-9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062621","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":311666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":299403,"type":{"id":15,"text":"Index Page"},"url":"https://tnawra.er.usgs.gov/Library/Proceedings24th.pdf"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        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mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worland, Scott","contributorId":150038,"corporation":false,"usgs":false,"family":"Worland","given":"Scott","affiliations":[],"preferred":false,"id":580500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byl, Tom","contributorId":150039,"corporation":false,"usgs":false,"family":"Byl","given":"Tom","affiliations":[],"preferred":false,"id":580501,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70142541,"text":"sir20155042 - 2015 - Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","interactions":[],"lastModifiedDate":"2015-04-02T16:56:44","indexId":"sir20155042","displayToPublicDate":"2015-04-02T17:45:00","publicationYear":"2015","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":"2015-5042","title":"Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","docAbstract":"<p>From 2011 to 2013, the U.S. Geological Survey&rsquo;s Idaho National Laboratory (INL) Project Office, in cooperation with the U.S. Department of Energy, collected depth-discrete measurements of fluid pressure and temperature in 11 boreholes located in the eastern Snake River Plain aquifer. Each borehole was instrumented with a multilevel monitoring system (MLMS) consisting of a series of valved measurement ports, packer bladders, casing segments, and couplers.</p>\n<p>Multilevel monitoring at the INL has been ongoing since 2006 and this report summarizes data collected from 2011 to 2013 in 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected from 11 multilevel monitoring wells, including 177 hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within borehole USGS 134 was not monitored because of a valve failure.</p>\n<p>Head and temperature profiles reveal unique patterns for vertical examination of the aquifer&rsquo;s complex basalt and sediment stratigraphy, proximity to aquifer recharge and discharge, and groundwater flow. These features contribute to some of the localized variability even though the general profile shape remained consistent over the period of record. Twenty-two major head inflections were described for 9 of 11 MLMS boreholes and almost always coincided with low‑permeability sediment layers and occasionally thick layers of dense basalt. However, the presence of a sediment layer or dense basalt layer was insufficient for identifying the location of a major head change within a borehole without knowing the true areal extent and relative transmissivity of the lithologic unit. Temperature profiles for boreholes completed within the Big Lost Trough indicate linear conductive trends; whereas, temperature profiles for boreholes completed within volcanic rift zones and near the southern boundary of the Idaho National Laboratory, indicate mostly convective heat transfer. Select boreholes along the southern boundary show a temperature reversal and cooler water deeper in the aquifer resulting from the vertical movement of groundwater.</p>\n<p>Vertical head and temperature change were quantified for each of the 11 multilevel monitoring systems. Vertical head gradients defined for the major inflections in the head profiles were as high as 2.9 feet per foot. In general, fractured basalt zones displayed relatively small vertical head differences and show a high occurrence within volcanic rift zones. Poor connectivity between fractures and higher vertical gradients were generally attributed to sediment layers and layers of dense basalt, or both. Groundwater temperatures in all boreholes ranged from 10.8 to 16.3 &deg;C.</p>\n<p>Normalized mean head values were analyzed for all 11 multilevel monitoring wells for the period of record (2007&ndash;13). The mean head values suggest a moderately positive correlation among all boreholes and generally reflect regional fluctuations in water levels in response to seasonal climatic changes. Boreholes within volcanic rift zones and near the southern boundary (USGS 103, USGS 105, USGS 108, USGS 132, USGS 135, USGS 137A) display a temporal correlation that is strongly positive. Boreholes in the Big Lost Trough display some variations in temporal correlations that may result from proximity to the mountain front to the northwest and episodic flow in the Big Lost River drainage system. For example, during June 2012, boreholes MIDDLE 2050A and MIDDLE 2051 showed head buildup within the upper zones when compared to the June 2010 profile event, which correlates to years when surface water was reported for the Big Lost River several months preceding the measurement period. With the exception of borehole USGS 134, temporal correlation between MLMS wells completed within the Big Lost Trough is generally positive. Temporal correlation for borehole USGS 134 shows the least agreement with other MLMS boreholes located within the Big Lost Trough; however, borehole USGS 134 is close to the mountain front where tributary valley subsurface inflow is suspected.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155042","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Twining, B.V., and Fisher, J.C., 2015, Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13: U.S. Geological Survey Scientific Investigations Report 2015-5042, Report: vii, 49 p.; 8 Appendices, https://doi.org/10.3133/sir20155042.","productDescription":"Report: vii, 49 p.; 8 Appendices","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-056607","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":299324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155042.jpg"},{"id":299323,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppH.pdf","text":"Appendix H","size":"161 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299314,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5042/"},{"id":299315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir2015-5042.pdf","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":299316,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppA.pdf","text":"Appendix A","size":"98 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299317,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppB.pdf","text":"Appendix B","size":"202 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299318,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppC.pdf","text":"Appendix C","size":"125 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299319,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppD.pdf","text":"Appendix D","size":"109 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299320,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppE.pdf","text":"Appendix E","size":"592 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299321,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppF.pdf","text":"Appendix F","size":"103 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299322,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppG.pdf","text":"Appendix G","size":"148 KB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.104248046875,\n              43.52664646047308\n            ],\n            [\n              -113.104248046875,\n              43.880077621969065\n            ],\n            [\n              -112.61123657226562,\n              43.880077621969065\n            ],\n            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jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70144294,"text":"ofr20151058 - 2015 - An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","interactions":[],"lastModifiedDate":"2015-04-09T08:31:36","indexId":"ofr20151058","displayToPublicDate":"2015-04-02T11:00:00","publicationYear":"2015","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":"2015-1058","title":"An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","docAbstract":"<p>Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series.</p>\n<p>To facilitate comparisons between measurement results and time-series data, streamflows corresponding to the times of the streamflow measurements were computed from the time-series data by time-based linear interpolation. Prior to doing interpolations, measurement times for the Hannibal Lock and Dam location were adjusted for traveltime to account for the fact that the streamflow measurements were made about 1.5 mi downstream from the location corresponding to the modeled/computed time-series data. Measured and interpolated streamflows were tabulated along with residuals (the difference between measured and interpolated streamflows) and selected summary statistics.</p>\n<p>Overall, streamflows interpolated from the USGS computed 15-minute time-series data (hereafter referred to as the USGS 15-minute time-series data) had the smallest root-mean-square error (RMSE) (3,939 cubic feet per second [ft<sup>3</sup>/s]) and the second smallest mean absolute residual (2,636 ft<sup>3</sup>/s), whereas streamflows interpolated from the USACE 12 UTC time series had the largest RMSE (14,590 ft<sup>3</sup>/s) and the largest mean absolute residual (10,800 ft<sup>3</sup>/s). The larger RMSEs for streamflows interpolated from the USACE 12 UTC time series likely resulted in part from the coarser time step of that time series. Streamflows interpolated from the USGS downsampled 1-hour time series had the second smallest RMSE (4,025 ft<sup>3</sup>/s) and the smallest mean absolute residual (2,600 ft<sup>3</sup>/s). Somewhat surprisingly, streamflows interpolated from the NWS 6-hour model time series had the third smallest RMSE (4,483 ft<sup>3</sup>/s) and mean absolute residual (4,050 ft<sup>3</sup>/s) in spite of being determined from a time series with a coarser time step than the USACE 1-hour modeled and computed time series.</p>\n<p>Measured streamflows at the Sardis gage and at the Hannibal Lock and Dam measurement location were plotted versus residuals (expressed as a percentage of the measured streamflows) of corresponding interpolated time-series streamflow values. Results for each of the time series exhibited some anomaly, possibly indicating the need and (or) potential for improvement in the streamflow computational/modeling processes.</p>\n<p>Streamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151058","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Koltun, G., 2015, An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio: U.S. Geological Survey Open-File Report 2015-1058, viii, 23 p., https://doi.org/10.3133/ofr20151058.","productDescription":"viii, 23 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063449","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":299300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151058.jpg"},{"id":299296,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1058/"},{"id":299297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1058/pdf/ofr2015-1058.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Ohio","otherGeospatial":"Ohio River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.96099853515624,\n              39.57817336212527\n            ],\n            [\n              -80.96099853515624,\n              39.68182601089365\n            ],\n            [\n              -80.82092285156249,\n              39.68182601089365\n            ],\n            [\n              -80.82092285156249,\n              39.57817336212527\n            ],\n            [\n              -80.96099853515624,\n              39.57817336212527\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1be4b027f0aee3b86b","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":1852,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","email":"gfkoltun@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543454,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70144432,"text":"70144432 - 2015 - Do management actions to restore rare habitat benefit native fish conservation?  Distribution of juvenile native fish among shoreline habitats of the Colorado River","interactions":[],"lastModifiedDate":"2015-12-07T10:14:29","indexId":"70144432","displayToPublicDate":"2015-04-02T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Do management actions to restore rare habitat benefit native fish conservation?  Distribution of juvenile native fish among shoreline habitats of the Colorado River","docAbstract":"<p><span>Many management actions in aquatic ecosystems are directed at restoring or improving specific habitats to benefit fish populations. In the Grand Canyon reach of the Colorado River, experimental flow operations as part of the Glen Canyon Dam Adaptive Management Program have been designed to restore sandbars and associated backwater habitats. Backwaters can have warmer water temperatures than other habitats, and native fish, including the federally endangered humpback chub&nbsp;</span><i>Gila cypha</i><span>, are frequently observed in backwaters, leading to a common perception that this habitat is critical for juvenile native fish conservation. However, it is unknown how fish densities in backwaters compare with that in other habitats or what proportion of juvenile fish populations reside in backwaters. Here, we develop and fit multi-species hierarchical models to estimate habitat-specific abundances and densities of juvenile humpback chub, bluehead sucker</span><i>Catostomus discobolus</i><span>, flannelmouth sucker&nbsp;</span><i>Catostomus latipinnis</i><span>&nbsp;and speckled dace&nbsp;</span><i>Rhinichthys osculus</i><span>&nbsp;in a portion of the Colorado River. Densities of all four native fish were greatest in backwater habitats in 2009 and 2010. However, backwaters are rare and ephemeral habitats, so they contain only a small portion of the overall population. For example, the total abundance of juvenile humpback chub in this study was much higher in talus than in backwater habitats. Moreover, when we extrapolated relative densities based on estimates of backwater prevalence directly after a controlled flood, the majority of juvenile humpback chub were still found outside of backwaters. This suggests that the role of controlled floods in influencing native fish population trends may be limited in this section of the Colorado River.&nbsp;</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.2842","usgsCitation":"Dodrill, M.J., Yackulic, C.B., Gerig, B., Pine, W.E., Korman, J., and Finch, C., 2015, Do management actions to restore rare habitat benefit native fish conservation?  Distribution of juvenile native fish among shoreline habitats of the Colorado River: River Research and Applications, v. 31, no. 10, p. 1203-1217, https://doi.org/10.1002/rra.2842.","productDescription":"15 p.","startPage":"1203","endPage":"1217","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052358","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":299274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.8902587890625,\n              36.097938036628065\n            ],\n            [\n              -111.8902587890625,\n              36.289670126842225\n            ],\n            [\n              -111.74057006835936,\n              36.289670126842225\n            ],\n            [\n              -111.74057006835936,\n              36.097938036628065\n            ],\n            [\n              -111.8902587890625,\n              36.097938036628065\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"551e5a1ee4b027f0aee3b873","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerig, Brandon","contributorId":139958,"corporation":false,"usgs":false,"family":"Gerig","given":"Brandon","affiliations":[{"id":13331,"text":"University of Florida, Dept. of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":543583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finch, Colton","contributorId":139961,"corporation":false,"usgs":false,"family":"Finch","given":"Colton","affiliations":[{"id":13334,"text":"Uni. of Florida, Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543584,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70143862,"text":"ofr20151053 - 2015 - A method for determining average beach slope and beach slope variability for U.S. sandy coastlines","interactions":[],"lastModifiedDate":"2017-06-12T11:21:02","indexId":"ofr20151053","displayToPublicDate":"2015-04-02T07:30:00","publicationYear":"2015","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":"2015-1053","title":"A method for determining average beach slope and beach slope variability for U.S. sandy coastlines","docAbstract":"<p><span>The U.S. Geological Survey (USGS) National Assessment of Hurricane-Induced Coastal Erosion Hazards compares measurements of beach morphology with storm-induced total water levels to produce forecasts of coastal change for storms impacting the Gulf of Mexico and Atlantic coastlines of the United States. The wave-induced water level component (wave setup and swash) is estimated by using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon and others (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. For instance, seasonal and storm-induced changes in beach slope can lead to differences on the order of 1 meter (m) in wave-induced water level elevation, making accurate specification of this parameter and its associated uncertainty essential to skillful forecasts of coastal change. A method for calculating spatially and temporally averaged beach slopes is presented here along with a method for determining total uncertainty for each 200-m alongshore section of coastline.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151053","usgsCitation":"Doran, K.S., Long, J.W., and Overbeck, J., 2015, A method for determining average beach slope and beach slope variability for U.S. sandy coastlines: U.S. Geological Survey Open-File Report 2015-1053, Report: iv, 5 p.; Data Releases, https://doi.org/10.3133/ofr20151053.","productDescription":"Report: iv, 5 p.; Data Releases","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063337","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438707,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72805P1","text":"USGS data release","linkHelpText":"Beach Slopes of Florida: Miami to Jupiter"},{"id":299260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151053.jpg"},{"id":342384,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F72805P1","text":"Beach slopes of Florida: Miami to Jupiter"},{"id":342385,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F7XK8CK2","text":"Beach slopes of Florida: Bradenton Beach to Clearwater Beach"},{"id":299257,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1053/"},{"id":299258,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1053/pdf/ofr2015-1053.pdf","text":"Report","size":"377 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299259,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F7M906Q6","text":"Beach Slopes of North Carolina: Salvo to Duck","description":"Dataset website"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.84686279296874,\n              35.21420969483077\n            ],\n            [\n              -75.84686279296874,\n              36.10015727402227\n            ],\n            [\n              -75.21240234375,\n              36.10015727402227\n            ],\n            [\n              -75.21240234375,\n              35.21420969483077\n            ],\n            [\n              -75.84686279296874,\n              35.21420969483077\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a18e4b027f0aee3b869","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":127855,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":543875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":543876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overbeck, Jacquelyn R.","contributorId":140046,"corporation":false,"usgs":true,"family":"Overbeck","given":"Jacquelyn R.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":543877,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70146790,"text":"70146790 - 2015 - Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin","interactions":[],"lastModifiedDate":"2017-11-22T18:01:11","indexId":"70146790","displayToPublicDate":"2015-04-01T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin","docAbstract":"<p>Evaluating the effectiveness of habitat management actions is critical to adaptive management strategies for conservation of imperiled species. We quantified the response of a Great Basin population of the Columbia spotted frog (<i>Rana luteiventris</i>) to multiple habitat improvement actions aimed to reduce threats and reverse population declines. We used mark-recapture data for 1,394 adult frogs that had been marked by state, federal, and university biologists in 9 ponds representing a single population over a 16-year period from 1997 to 2012. With the use of demographic models, we assessed population-level effects of 1) a grazing exclosure constructed around 6 stock ponds that had been used to water livestock for decades before being fully fenced in 2003, and 2) the construction of 3 new stock ponds in 2003 to provide alternative water sources for livestock and, secondarily, to provide additional frog habitat. These management actions were implemented in response to a decline of more than 80% in population size from 1997 to 2002. We found evidence that excluding cattle from ponds and surrounding riparian habitats resulted in higher levels of frog production (more egg masses), higher adult frog recruitment and survival, and higher population growth rate. We also found that frogs colonized the newly constructed stock ponds within 3 years and frogs began breeding in 2 of them after 5 years. The positive effects of the cattle exclosure and additional production from the new ponds, although notable, did not result in full recovery of the population even 9 years later. This slow recovery may be partly explained by the effects of weather on recruitment rates, particularly the negative effects of harsher winters with late springs and higher fall temperatures. Although our findings point to potential successes of habitat management aimed at slowing or reversing rapidly declining frog populations, our study also suggests that recovering from severe population declines can take many years because of demographic and environmental processes.&nbsp;</p>","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.868","usgsCitation":"Pilliod, D., and Scherer, R.D., 2015, Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin: Journal of Wildlife Management, v. 79, no. 4, p. 579-590, https://doi.org/10.1002/jwmg.868.","productDescription":"12 p.","startPage":"579","endPage":"590","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059456","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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,{"id":70146795,"text":"70146795 - 2015 - Desert tortoise use of burned habitat in the Eastern Mojave desert","interactions":[],"lastModifiedDate":"2016-04-13T13:08:25","indexId":"70146795","displayToPublicDate":"2015-04-01T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Desert tortoise use of burned habitat in the Eastern Mojave desert","docAbstract":"<p>Wildfires burned 24,254&thinsp;ha of critical habitat designated for the recovery of the threatened Mojave desert tortoise (<i>Gopherus agassizii</i>) in southern Nevada during 2005. The proliferation of non-native annual grasses has increased wildfire frequency and extent in recent decades and continues to accelerate the conversion of tortoise habitat across the Mojave Desert. Immediate changes to vegetation are expected to reduce quality of critical habitat, yet whether tortoises will use burned and recovering habitat differently from intact unburned habitat is unknown. We compared movement patterns, home-range size, behavior, microhabitat use, reproduction, and survival for adult desert tortoises located in, and adjacent to, burned habitat to understand how tortoises respond to recovering burned habitat. Approximately 45% of home ranges in the post-fire environment contained burned habitat, and numerous observations (<i>n</i>&thinsp;=&thinsp;12,223) corroborated tortoise use of both habitat types (52% unburned, 48% burned). Tortoises moved progressively deeper into burned habitat during the first 5 years following the fire, frequently foraging in burned habitats that had abundant annual plants, and returning to adjacent unburned habitat for cover provided by intact perennial vegetation. However, by years 6 and 7, the live cover of the short-lived herbaceous perennial desert globemallow (<i>Sphaeralcea ambigua</i>) that typically re-colonizes burned areas declined, resulting in a contraction of tortoise movements from the burned areas. Health and egg production were similar between burned and unburned areas indicating that tortoises were able to acquire necessary resources using both areas. This study documents that adult Mojave desert tortoises continue to use habitat burned once by wildfire. Thus, continued management of this burned habitat may contribute toward the recovery of the species in the face of many sources of habitat loss.</p>","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.874","usgsCitation":"Drake, K.K., Esque, T., Nussear, K.E., DeFalco, L., Scoles-Sciulla, S.J., Modlin, A.T., and Medica, P.A., 2015, Desert tortoise use of burned habitat in the Eastern Mojave desert: Journal of Wildlife Management, v. 79, no. 4, p. 618-629, https://doi.org/10.1002/jwmg.874.","productDescription":"12 p.","startPage":"618","endPage":"629","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057109","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":299811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","county":"Clark County","otherGeospatial":"Mojave Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.51025390625,\n              36.32397712011264\n            ],\n            [\n              -115.323486328125,\n              36.32397712011264\n            ],\n            [\n              -115.1312255859375,\n              36.33725319397006\n            ],\n            [\n              -114.91149902343751,\n              36.348314860643015\n            ],\n            [\n              -114.61212158203124,\n              36.361586786517776\n            ],\n            [\n              -114.46380615234375,\n              36.38812384894608\n            ],\n            [\n              -114.38690185546875,\n              36.41244153535644\n            ],\n            [\n              -114.36767578124999,\n              36.4477991295848\n            ],\n            [\n              -114.400634765625,\n              36.491973470593685\n            ],\n            [\n              -114.4061279296875,\n              36.53832942872816\n            ],\n            [\n              -114.36767578124999,\n              36.5978891330702\n            ],\n            [\n              -114.36767578124999,\n              36.752089156946326\n            ],\n            [\n              -114.3621826171875,\n              36.88621127842176\n            ],\n            [\n              -115.95932006835938,\n              36.90213639045954\n            ],\n            [\n              -115.93803405761717,\n              36.32729635065908\n            ],\n            [\n              -115.51025390625,\n              36.32397712011264\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"79","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553774aae4b0b22a1580850b","contributors":{"authors":[{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":140024,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":545360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeFalco, Lesley ldefalco@usgs.gov","contributorId":139012,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":545363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scoles-Sciulla, Sara J. 0000-0003-1693-5030 sscoles@usgs.gov","orcid":"https://orcid.org/0000-0003-1693-5030","contributorId":2614,"corporation":false,"usgs":true,"family":"Scoles-Sciulla","given":"Sara","email":"sscoles@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Modlin, Andrew T. amodlin@usgs.gov","contributorId":5967,"corporation":false,"usgs":true,"family":"Modlin","given":"Andrew","email":"amodlin@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Medica, Philip A.","contributorId":55780,"corporation":false,"usgs":true,"family":"Medica","given":"Philip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":545366,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70144897,"text":"70144897 - 2015 - Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?","interactions":[],"lastModifiedDate":"2018-10-30T14:31:51","indexId":"70144897","displayToPublicDate":"2015-04-01T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?","docAbstract":"<p><span>Increased land use by polar bears (</span><i>Ursus maritimus</i><span>) due to climate-change-induced reduction of their sea-ice habitat illustrates the impact of climate change on species distributions and the difficulty of conserving a large, highly specialized carnivore in the face of this global threat. Some authors have suggested that terrestrial food consumption by polar bears will help them withstand sea-ice loss as they are forced to spend increasing amounts of time on land. Here, we evaluate the nutritional needs of polar bears as well as the physiological and environmental constraints that shape their use of terrestrial ecosystems. Only small numbers of polar bears have been documented consuming terrestrial foods even in modest quantities. Over much of the polar bear's range, limited terrestrial food availability supports only low densities of much smaller, resident brown bears (</span><i>Ursus arctos</i><span>), which use low-quality resources more efficiently and may compete with polar bears in these areas. Where consumption of terrestrial foods has been documented, polar bear body condition and survival rates have declined even as land use has increased. Thus far, observed consumption of terrestrial food by polar bears has been insufficient to offset lost ice-based hunting opportunities but can have ecological consequences for other species. Warming-induced loss of sea ice remains the primary threat faced by polar bears.</span></p>","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/140202","usgsCitation":"Rode, K.D., Robbins, C.T., Nelson, L., and Amstrup, S.C., 2015, Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?: Frontiers in Ecology and the Environment, v. 13, no. 3, p. 138-145, https://doi.org/10.1890/140202.","productDescription":"8 p.","startPage":"138","endPage":"145","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057990","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":472161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/140202","text":"Publisher Index Page"},{"id":299253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic","volume":"13","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551d0899e4b0256c24f4214c","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":543837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, Charles T.","contributorId":32436,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":543838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Lynne","contributorId":140043,"corporation":false,"usgs":false,"family":"Nelson","given":"Lynne","email":"","affiliations":[],"preferred":false,"id":543839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":543840,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70147071,"text":"70147071 - 2015 - Targeting climate diversity in conservation planning to build resilience to climate change","interactions":[],"lastModifiedDate":"2018-09-18T10:34:24","indexId":"70147071","displayToPublicDate":"2015-04-01T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Targeting climate diversity in conservation planning to build resilience to climate change","docAbstract":"<p>Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.</p>","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES14-00313.1","usgsCitation":"Heller, N.E., Kreitler, J.R., Ackerly, D., Weiss, S., Recinos, A., Branciforte, R., Flint, L.E., Flint, A.L., and Micheli, E., 2015, Targeting climate diversity in conservation planning to build resilience to climate change: Ecosphere, v. 6, no. 4, p. 1-20, https://doi.org/10.1890/ES14-00313.1.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058616","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472162,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1890/es14-00313.1","text":"External Repository"},{"id":299894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-24","publicationStatus":"PW","scienceBaseUri":"553f5dbbe4b0a658d7938cfc","contributors":{"authors":[{"text":"Heller, Nicole E.","contributorId":140429,"corporation":false,"usgs":false,"family":"Heller","given":"Nicole","email":"","middleInitial":"E.","affiliations":[{"id":13495,"text":"Dwight Center for Conservation Science at Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":545619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":545618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerly, David","contributorId":139541,"corporation":false,"usgs":false,"family":"Ackerly","given":"David","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":545620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiss, Stuart","contributorId":7590,"corporation":false,"usgs":true,"family":"Weiss","given":"Stuart","email":"","affiliations":[],"preferred":false,"id":545621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Recinos, Amanda","contributorId":140430,"corporation":false,"usgs":false,"family":"Recinos","given":"Amanda","email":"","affiliations":[{"id":13496,"text":"GreenInfo Network","active":true,"usgs":false}],"preferred":false,"id":545622,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Branciforte, Ryan","contributorId":140431,"corporation":false,"usgs":false,"family":"Branciforte","given":"Ryan","email":"","affiliations":[{"id":13497,"text":"Bay Area Open Space Council","active":true,"usgs":false}],"preferred":false,"id":545623,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545625,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Micheli, Elisabeth","contributorId":105615,"corporation":false,"usgs":true,"family":"Micheli","given":"Elisabeth","email":"","affiliations":[],"preferred":false,"id":545626,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70160762,"text":"70160762 - 2015 - Summer diel diet and feeding periodicity of four species of cyprinids in the Salmon River, New York","interactions":[],"lastModifiedDate":"2015-12-30T11:50:25","indexId":"70160762","displayToPublicDate":"2015-04-01T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Summer diel diet and feeding periodicity of four species of cyprinids in the Salmon River, New York","docAbstract":"<p>The diel diet composition and feeding periodicity of<i> Luxilus cornutus</i> (common shiner),<i> Exoglossum maxillingua</i> (cutlip minnow), <i>Semotilus corporalis</i> (fallfish), and <i>Notropis hudsonius</i> (spottail shiner) were examined in the Salmon River, New York over a 24 h period during the summer. Chironomids were the major prey of common shiner (60.6%) and cutlip minnow (54.7%), whereas terrestrial invertebrates (30.0%) and amphipods (38.4%) were the primary food of fallfish and spottail shiner, respectively. Diet overlap was high between common shiner and cutlip minnow (Morisita's index  =  0.88) and moderate between fallfish and common shiner (0.54) and fallfish and cutlip minnow (0.50). Diel temperal variation in diet composition was greatest (0.64) for spottail shiner. Three species exhibited diel variation in food consumption. Fallfish had a distinct feeding peak, whereas peak food consumption of common shiner and cutlip minnow occurred over a more extended period. Spottail shiner did not have a distinct feeding peak but food consumption was highest from 2400 to 0800 h. Each of the four species exhibited some degree of variation in their diel feeding ecology in regards to either diet composition or food consumption.</p>","language":"English","publisher":"University of Notre Dam","publisherLocation":"Notre Dam, Indiana","doi":"10.1674/amid-173-02-326-334.1","usgsCitation":"Johnson, J.H., 2015, Summer diel diet and feeding periodicity of four species of cyprinids in the Salmon River, New York: American Midland Naturalist, v. 173, no. 2, p. 326-334, https://doi.org/10.1674/amid-173-02-326-334.1.","productDescription":"9 p.","startPage":"326","endPage":"334","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053580","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Salmon River","geographicExtents":"{\n  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