{"pageNumber":"537","pageRowStart":"13400","pageSize":"25","recordCount":46856,"records":[{"id":70094688,"text":"sir20145024 - 2014 - Delineation of brine contamination in and near the East Poplar oil field, Fort Peck Indian Reservation, northeastern Montana, 2004-09","interactions":[],"lastModifiedDate":"2014-04-02T10:46:06","indexId":"sir20145024","displayToPublicDate":"2014-04-02T09:06:00","publicationYear":"2014","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":"2014-5024","title":"Delineation of brine contamination in and near the East Poplar oil field, Fort Peck Indian Reservation, northeastern Montana, 2004-09","docAbstract":"<p>The extent of brine contamination in the shallow aquifers in and near the East Poplar oil field is as much as 17.9 square miles and appears to be present throughout the entire saturated zone in contaminated areas. The brine contamination affects 15–37 billion gallons of groundwater. Brine contamination in the shallow aquifers east of the Poplar River generally moves to the southwest toward the river and then southward in the Poplar River valley. The likely source of brine contamination in the shallow aquifers is brine that is produced with crude oil in the East Poplar oil field study area. Brine contamination has not only affected the water quality from privately owned wells in and near the East Poplar oil field, but also the city of Poplar’s public water-supply wells.</p>\n<br/>\n<p>Three water-quality types characterize water in the shallow aquifers; a fourth water-quality type in the study area characterizes the brine. Type 1 is uncontaminated water that is suitable for most domestic purposes and typically contains sodium bicarbonate and sodium/magnesium sulfate as the dominant ions. Type 2 is moderately contaminated water that is suitable for some domestic purposes, but not used for drinking water, and typically contains sodium and chloride as the dominant ions. Type 3 is considerably contaminated water that is unsuitable for any domestic purpose and always contains sodium and chloride as the dominant ions. Type 3 quality of water in the shallow aquifers is similar to Type 4, which is the brine that is produced with crude oil.<p>\n<br/>\n<p>Electromagnetic apparent conductivity data were collected in the 106 square-mile area and used to determine extent of brine contamination. These data were collected and interpreted in conjunction with water-quality data collected through 2009 to delineate brine plumes in the shallow aquifers. Monitoring wells subsequently were drilled in some areas without existing water wells to confirm most of the delineated brine plumes; however, several possible plumes do not contain either existing water wells or monitoring wells. Analysis of groundwater samples from wells confirms the presence of 12.1 square miles of contamination, as much as 1.7 square miles of which is considerably contaminated (Type 3). Electromagnetic apparent conductivity data in areas with no wells delineate an additional 5.8 square miles of possible contamination, 2.1 square miles of which might be considerably contaminated (Type 3). Storage-tank facilities, oil wells, brine-injection wells, pipelines, and pits are likely sources of brine in the study area. It is not possible to identify discrete oil-related features as likely sources of brine plumes because several features commonly are co-located. During the latter half of the twentieth century, many brine plumes migrated beyond the immediate source area and likely mix together in modern and ancestral Poplar River valley subareas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145024","collaboration":"Prepared in cooperation with the Fort Peck Tribes Office of Environmental Protection","usgsCitation":"Thamke, J., and Smith, B.D., 2014, Delineation of brine contamination in and near the East Poplar oil field, Fort Peck Indian Reservation, northeastern Montana, 2004-09: U.S. Geological Survey Scientific Investigations Report 2014-5024, Report: viii, 40 p.; Appendix, https://doi.org/10.3133/sir20145024.","productDescription":"Report: viii, 40 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-009092","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":285271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145024.jpg"},{"id":285268,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5024/pdf/sir2014-5024.pdf"},{"id":285269,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5024/"},{"id":285270,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5024/appendix"}],"datum":"NAD 27","country":"United States","state":"Montana","city":"Fort Peck","otherGeospatial":"Fort Peck Indian Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.0,48.0 ], [ -107.0,49.0 ], [ -105.0,49.0 ], [ -105.0,48.0 ], [ -107.0,48.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517032e4b05569d805a1b3","contributors":{"authors":[{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":490807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490806,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70055512,"text":"70055512 - 2014 - Sedimentary facies of the upper Cambrian (Furongian; Jiangshanian and Sunwaptan) Tunnel City Group, Upper Mississippi Valley: new insight on the old stormy debate","interactions":[],"lastModifiedDate":"2014-05-13T15:29:24","indexId":"70055512","displayToPublicDate":"2014-04-01T15:26:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3368,"text":"Sedimentary Geology","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary facies of the upper Cambrian (Furongian; Jiangshanian and Sunwaptan) Tunnel City Group, Upper Mississippi Valley: new insight on the old stormy debate","docAbstract":"New data from detailed measured sections permit a comprehensive revision of the sedimentary facies of the Furongian (upper Cambrian; Jiangshanian and Sunwaptan stages) Tunnel City Group (Lone Rock Formation and Mazomanie Formation) of Wisconsin and Minnesota. Heterogeneous sandstones, comprising seven lithofacies along a depositional transect from shoreface to transitional-offshore environments, record sedimentation in a storm-dominated, shallow-marine epicontinental sea. The origin of glauconite in the Birkmose Member and Reno Member of the Lone Rock Formation was unclear, but its formation and preserved distribution are linked to inferred depositional energy rather than just net sedimentation rate. Flat-pebble conglomerate, abundant in lower Paleozoic strata, was associated with the formation of a condensed section during cratonic flooding. Hummocky cross-stratification was a valuable tool used to infer depositional settings and relative paleobathymetry, and the model describing formation of this bedform is expanded to address flow types dominant during its genesis, in particular the importance of an early unidirectional component of combined flow. The depositional model developed here for the Lone Rock Formation and Mazomanie Formation is broadly applicable to other strata common to the early Paleozoic that document sedimentation along flooded cratonic interiors or shallow shelves.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Sedimentary Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.sedgeo.2013.09.008","usgsCitation":"Eoff, J.D., 2014, Sedimentary facies of the upper Cambrian (Furongian; Jiangshanian and Sunwaptan) Tunnel City Group, Upper Mississippi Valley: new insight on the old stormy debate: Sedimentary Geology, v. 302, p. 102-121, https://doi.org/10.1016/j.sedgeo.2013.09.008.","productDescription":"20 p.","startPage":"102","endPage":"121","ipdsId":"IP-044560","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":287100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287099,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.sedgeo.2013.09.008"}],"country":"United States","state":"Minnesota;Wisconsin","volume":"302","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53733f04e4b049706127892d","contributors":{"authors":[{"text":"Eoff, Jennifer D. jeoff@usgs.gov","contributorId":3418,"corporation":false,"usgs":true,"family":"Eoff","given":"Jennifer","email":"jeoff@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486116,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70100456,"text":"fs20143020 - 2014 - The 3D Elevation Program: summary for Missouri","interactions":[],"lastModifiedDate":"2016-08-17T15:45:20","indexId":"fs20143020","displayToPublicDate":"2014-04-01T15:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3020","title":"The 3D Elevation Program: summary for Missouri","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Missouri, elevation data are critical for agriculture and precision farming; natural resources conservation; flood risk management; homeland security, law enforcement, and disaster response; infrastructure and construction management; water supply and quality; and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143020","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Missouri: U.S. Geological Survey Fact Sheet 2014-3020, 2 p., https://doi.org/10.3133/fs20143020.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052811","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":492228,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101000,"text":"70101000 - 2014 - Does the timing of attainment of maturity influence sexual size dimorphism and adult sex ratio in turtles?","interactions":[],"lastModifiedDate":"2014-04-21T13:35:05","indexId":"70101000","displayToPublicDate":"2014-04-01T14:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1019,"text":"Biological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Does the timing of attainment of maturity influence sexual size dimorphism and adult sex ratio in turtles?","docAbstract":"The attainment of sexual maturity has been shown to affect measures of sexual size dimorphism (SSD) and adult sex ratios in several groups of vertebrates. Using data for turtles, we tested the model that sex ratios are expected to be male-biased when females are larger than males and female-biased when males are larger than females because of the relationship of each with the attainment of maturity. Our model is based on the premise that the earlier-maturing sex remains smaller, on average throughout life, and predominates numerically unless the sexes are strongly affected by differential mortality, differential emigration, and immigration, or biased primary sex ratios. Based on data for 24 species in seven families, SSD and sex ratios were significantly negatively correlated for most analyses, even after the effect of phylogenetic bias was removed. The analyses provide support for the model that SSD and adult sex ratios are correlated in turtles as a result of simultaneous correlation of each with sexual differences in attainment of maturity (bimaturism). Environmental sex determination provides a possible mechanism for the phenomenon in turtles and some other organisms.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Journal of the Linnean Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/bij.12275","usgsCitation":"Lovich, J.E., Gibbons, J., and Agha, M., 2014, Does the timing of attainment of maturity influence sexual size dimorphism and adult sex ratio in turtles?: Biological Journal of the Linnean Society, v. 112, no. 1, p. 142-149, https://doi.org/10.1111/bij.12275.","productDescription":"8 p.","startPage":"142","endPage":"149","ipdsId":"IP-054110","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/bij.12275","text":"Publisher Index Page"},{"id":285905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285903,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/bij.12275"}],"volume":"112","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-04-08","publicationStatus":"PW","scienceBaseUri":"53517034e4b05569d805a1cb","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":492502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbons, J. Whitfield","contributorId":46584,"corporation":false,"usgs":true,"family":"Gibbons","given":"J. Whitfield","affiliations":[],"preferred":false,"id":492504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false},{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":492503,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048664,"text":"70048664 - 2014 - Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale","interactions":[],"lastModifiedDate":"2018-09-27T10:51:00","indexId":"70048664","displayToPublicDate":"2014-04-01T13:36:17","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale","docAbstract":"We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R<sub>2</sub> for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0090944","usgsCitation":"White, I.R., Kennen, J., May, J., Brown, L.R., Cuffney, T.F., Jones, K.A., and Orlando, J., 2014, Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale: PLoS ONE, v. 9, no. 3, p. 1-21, https://doi.org/10.1371/journal.pone.0090944.","productDescription":"e90944; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-045602","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":473070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0090944","text":"Publisher Index Page"},{"id":287148,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0090944"},{"id":287150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"North Central Appalachians;Northeastern Highlands;Northern Piedmont;Ridge And Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80,3.1352777777777776 ], [ -80,0.0011111111111111111 ], [ -72,0.0011111111111111111 ], [ -72,3.1352777777777776 ], [ -80,3.1352777777777776 ] ] ] } } ] }","volume":"9","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-27","publicationStatus":"PW","scienceBaseUri":"53749079e4b0870f4d23cfff","contributors":{"authors":[{"text":"White, Ian R.","contributorId":21862,"corporation":false,"usgs":true,"family":"White","given":"Ian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason T. 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":14791,"corporation":false,"usgs":true,"family":"May","given":"Jason T.","affiliations":[],"preferred":false,"id":485344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Kimberly A. kjones@usgs.gov","contributorId":937,"corporation":false,"usgs":true,"family":"Jones","given":"Kimberly","email":"kjones@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":485342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":485346,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70074259,"text":"sir20145010 - 2014 - Equations for estimating selected streamflow statistics in Rhode Island","interactions":[],"lastModifiedDate":"2016-08-19T16:45:20","indexId":"sir20145010","displayToPublicDate":"2014-04-01T13:28:00","publicationYear":"2014","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":"2014-5010","title":"Equations for estimating selected streamflow statistics in Rhode Island","docAbstract":"<p>Regional regression equations were developed for estimating selected natural&mdash;unaffected by alteration&mdash;streamflows of specific flow durations and low-flow frequency statistics for ungaged stream sites in Rhode Island. Selected at-site streamflow statistics are provided for 41 long-term streamgages, 21 short-term streamgages, and 135 partial-record stations in Rhode Island, eastern Connecticut, and southeastern and south-central Massachusetts. The regression equations for estimating selected streamflow statistics and the at-site statistics estimated for each of the 197 sites may be used by Federal, State, and local water managers in addressing water issues in and near Rhode Island.</p>\n<p>Multiple and simple linear regression equations were developed to estimate the 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 15-, 10-, 5-, 2-, and 1-percent flow durations and the 7Q2 (7-day, 2-year) and 7Q10 (7-day, 10-year) low-flow-frequency statistics. An additional 49 selected statistics, for which regression equations were not developed, also were estimated for the long- and short-term streamgages and partial-record stations for flow durations between the 99.99 and 0.01 percent and for the mean annual, mean monthly, and median monthly streamflows. A total of 70 selected streamflow statistics were estimated for 41 long-term streamgages, 21 short-term streamgages, and 135 partial-record stations in and near Rhode Island. Estimates of the long-term streamflow statistics for the 21 short-term streamgages and 135 partial-record stations were developed by the Maintenance of Variance Extension, type 1 (MOVE.1), record-extension technique.</p>\n<p>The equations used to estimate selected streamflow statistics were developed by relating the 19 flow-duration and 2 low-flow-frequency statistics to 31 different basin characteristics (physical, land-cover, and climatic) at the 41 long-term and 19 of 21 short-term streamgages (a total of 60 streamgages) in and near Rhode Island. The 135 partial-record stations were not used in the regression analyses. The regression analyses were done by using a user-weighted least-squares technique in the weighted-multiple-linear regression program for the 90- to 1-percent flow-duration statistics. For the 99-, 98-, and 95-percent flow durations and the 7Q2 and 7Q10 statistics, left-censored regression analyses were used to account for zero flows at a few streamgages. The regression analyses determined that two basin characteristics&mdash;drainage area and stream density&mdash;were the only significant explanatory variables for 16 of the 19 flow-duration and the 2 low-flow regression equations. For the 10-, 15-, and 20-percent flow-duration regression equations, drainage area was the only significant explanatory variable. The standard error of the estimate for the 21 regression equations ranged from 17.58 to 141.83 percent. The 99- to 85-percent flow durations and the low-flow statistics 7Q2 and 7Q10 had the highest standard errors of the estimate, ranging from 48.68 to 141.83 percent. The standard error of the estimate for the medium- to high-flow statistics&mdash;the 80- to 1-percent flow durations&mdash;ranged from 17.58 to 37.65 percent, with the standard errors for the 60- to 1-percent flow durations all being less than about 21 percent. Data also are provided to allow the user to calculate the 90-percent prediction intervals for the 21 streamflow statistics.</p>\n<p>The equations, which are based on data from streams with little to no flow alterations, will provide an estimate of the natural flows for a selected site. They will not estimate flows for altered sites with dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, and wastewater discharges. If the equations are used to estimate streamflow statistics for altered sites, the user should adjust the flow estimates for the alterations. The regression equations should be used only for ungaged sites with drainage areas between 0.52 and 294 square miles and stream densities between 0.94 and 3.49 miles per square mile; these are the ranges of the explanatory variables in the equations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145010","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Bent, G.C., Steeves, P.A., and Waite, A.M., 2014, Equations for estimating selected streamflow statistics in Rhode Island: U.S. Geological Survey Scientific Investigations Report 2014-5010, Report: viii, 65 p.; Tables: 5 Excel files, https://doi.org/10.3133/sir20145010.","productDescription":"Report: viii, 65 p.; Tables: 5 Excel files","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-046041","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285231,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145010.jpg"},{"id":285224,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5010/pdf/sir2014-5010.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":285225,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5010/"},{"id":285226,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5010/tables/sir2014-5010_bent_table03.xlsx","text":"Table 3","size":"70 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 3"},{"id":285227,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5010/tables/sir2014-5010_bent_table06.xlsx","text":"Table 6","size":"155 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 6"},{"id":285228,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5010/tables/sir2014-5010_bent_table08.xlsx","text":"Table 8","size":"45 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 8"},{"id":285229,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5010/tables/sir2014-5010_bent_table09.xlsx","text":"Table 9","size":"83 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 9"},{"id":285230,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5010/tables/sir2014-5010_bent_table10.xlsx","text":"Table 10","size":"19 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 10"}],"scale":"25000","datum":"North American Datum of 1983","country":"United States","state":"Rhode 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Center","active":true,"usgs":true}],"preferred":true,"id":489428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, Andrew M. awaite@usgs.gov","contributorId":2215,"corporation":false,"usgs":true,"family":"Waite","given":"Andrew","email":"awaite@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":489429,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70101273,"text":"70101273 - 2014 - Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana","interactions":[],"lastModifiedDate":"2017-01-12T11:27:18","indexId":"70101273","displayToPublicDate":"2014-04-01T13:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana","docAbstract":"<p><span>This study explores the feasibility of using airborne lidar surveys to construct high-resolution digital elevation models (DEMs) and develop an automated procedure to extract levee longitudinal elevation profiles for both federal levees in Atchafalaya Basin and local levees in Lafourche Parish, south Lousiana. This approach can successfully accommodate a high degree of levee sinuosity and abrupt changes in levee orientation (direction) in planar coordinates, variations in levee geometries, and differing DEM resolutions. The federal levees investigated in Atchafalaya Basin have crest elevations between 5.3 and 12&nbsp;m while the local counterparts in Lafourche Parish are between 0.76 and 2.3&nbsp;m. The vertical uncertainty in the elevation data is considered when assessing federal crest elevation against the U.S. Army Corps of Engineers minimum height requirements to withstand the 100-year flood. Only approximately 5% of the crest points of the two federal levees investigated in the Atchafalaya Basin region met this requirement.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2014.02.010","usgsCitation":"Palaseanu-Lovejoy, M., Thatcher, C., and Barras, J., 2014, Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana: ISPRS Journal of Photogrammetry and Remote Sensing, v. 91, p. 114-126, https://doi.org/10.1016/j.isprsjprs.2014.02.010.","productDescription":"13 p.","startPage":"114","endPage":"126","ipdsId":"IP-046351","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":286191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0434,28.9254 ], [ -94.0434,33.0195 ], [ -88.8162,33.0195 ], [ -88.8162,28.9254 ], [ -94.0434,28.9254 ] ] ] } } ] }","volume":"91","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517052e4b05569d805a305","contributors":{"authors":[{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":492653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Cindy A.","contributorId":79604,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy A.","affiliations":[],"preferred":false,"id":492654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barras, John A. jbarras@usgs.gov","contributorId":2425,"corporation":false,"usgs":true,"family":"Barras","given":"John A.","email":"jbarras@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":492652,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70101660,"text":"70101660 - 2014 - Combined effects of compact cevelopment, transportation investments, and road user pricing on vehicle miles traveled in urbanized areas","interactions":[],"lastModifiedDate":"2014-04-11T13:10:40","indexId":"70101660","displayToPublicDate":"2014-04-01T13:04:44","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3647,"text":"Transportation Research Record","active":true,"publicationSubtype":{"id":10}},"title":"Combined effects of compact cevelopment, transportation investments, and road user pricing on vehicle miles traveled in urbanized areas","docAbstract":"Vehicle miles traveled (VMT) is the primary determinant of traffic congestion, vehicle crashes, greenhouse gas emissions, and other effects of transportation. Two previous studies have sought to explain VMT levels in urbanized areas. This study updates and expands on previous work with more recent data, additional metrics, and structural equation modeling (SEM) to explain VMT levels in 315 urbanized areas. According to SEM, population, income, and gasoline prices are primary exogenous drivers of VMT. Development density is a primary endogenous driver. Urbanized areas with more freeway capacity are significantly less dense and have significantly higher VMT per capita. Areas with more transit service coverage and service frequency have higher development densities and per capita transit use, which leads to lower VMT per capita. The indirect effect of transit on VMT through land use, the so-called land use multiplier, is more than three times greater than the direct effect through transit ridership.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transportation Research Record","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Metapress","doi":"10.3141/2397-14","usgsCitation":"Ewing, R., Hamidi, S., Gallivan, F., Nelson, A.C., and Grace, J.B., 2014, Combined effects of compact cevelopment, transportation investments, and road user pricing on vehicle miles traveled in urbanized areas: Transportation Research Record, v. 2397, p. 117-124, https://doi.org/10.3141/2397-14.","productDescription":"8 p.","startPage":"117","endPage":"124","ipdsId":"IP-021995","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":286294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286290,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3141/2397-14"}],"country":"United States","volume":"2397","noUsgsAuthors":false,"publicationDate":"2013-01-01","publicationStatus":"PW","scienceBaseUri":"5351702fe4b05569d805a19e","contributors":{"authors":[{"text":"Ewing, Reid","contributorId":106010,"corporation":false,"usgs":true,"family":"Ewing","given":"Reid","affiliations":[],"preferred":false,"id":492728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamidi, Shima","contributorId":30909,"corporation":false,"usgs":true,"family":"Hamidi","given":"Shima","affiliations":[],"preferred":false,"id":492725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallivan, Frank","contributorId":48097,"corporation":false,"usgs":true,"family":"Gallivan","given":"Frank","email":"","affiliations":[],"preferred":false,"id":492726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Arthur C.","contributorId":75061,"corporation":false,"usgs":true,"family":"Nelson","given":"Arthur","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":492727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492724,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70096236,"text":"sir20145022 - 2014 - Monitoring and research to describe geomorphic effects of the 2011 controlled flood on the Green River in the Canyon of Lodore, Dinosaur National Monument, Colorado and Utah","interactions":[],"lastModifiedDate":"2014-04-01T12:58:10","indexId":"sir20145022","displayToPublicDate":"2014-04-01T12:42:00","publicationYear":"2014","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":"2014-5022","title":"Monitoring and research to describe geomorphic effects of the 2011 controlled flood on the Green River in the Canyon of Lodore, Dinosaur National Monument, Colorado and Utah","docAbstract":"<p>In 2011, a large magnitude flow release from Flaming Gorge Reservoir, Wyoming and Utah, occurred in response to high snowpack in the middle Rocky Mountains. This was the third highest recorded discharge along the Green River downstream of Flaming Gorge Dam, Utah, since its initial closure in November 1962 and motivated a research effort to document effects of these flows on channel morphology and sedimentology at four long-term monitoring sites within the Canyon of Lodore in Dinosaur National Monument, Colorado and Utah. Data collected in September 2011 included raft-based bathymetric surveys, ground-based surveys of banks, channel cross sections and vegetation-plot locations, sand-bar stratigraphy, and painted rock recovery on gravel bars. As part of this surveying effort, Global Navigation Satellite System (GNSS) data were collected at benchmarks on the canyon rim and along the river corridor to establish a high-resolution survey control network. This survey control network allows for the collection of repeatable spatial and elevation data necessary for high accuracy geomorphic change detection. Nearly 10,000 ground survey points and more than 20,000 bathymetric points (at 1-meter resolution) were collected over a 5-day field campaign, allowing for the construction of reach-scale digital elevation models (DEMs). Additionally, we evaluated long-term geomorphic change at these sites using repeat topographic surveys of eight monumented cross sections at each of the four sites.</p>\n<br/>\n<p>Analysis of DEMs and channel cross sections show a spatially variable pattern of erosion and deposition, both within and between reaches. As much as 5 meters of scour occurred in pools downstream from flow constrictions, especially in channel segments where gravel bars were absent. By contrast, some channel cross sections were stable during the 2011 floods, and have shown almost no change in over a decade of monitoring. Partial mobility of gravel bars occurred, and although in some locations vegetation such as tamarisk (<i>Tamarix ramosissima</i>) was damaged, wholesale bed motion necessary to fully clear these surfaces was not evident. In flow recirculation zones, eddy sandbars aggraded one meter or more, increasing the area of bars exposed during typical dam operations. Yet overall, the 2011 flood resulted in a decrease in reach-scale sand storage because bed degradation exceeded bar deposition. The 2011 response is consistent with that of a similar event in 1999, which was followed by sand-bar erosion and sediment accumulation on the bed during subsequent years of normal dam operational flows. Although the 1999 and 2011 floods were exceptional in the post-dam system, they did not exceed the pre-dam 2-year flood, isolating their effects to the modern active channel with minor erosion or reworking of pre-dam deposits stabilized through vegetation encroachment.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145022","collaboration":"Prepared in cooperation with Utah State University and Northern Arizona University","usgsCitation":"Mueller, E.R., Grams, P.E., Schmidt, J.C., Hazel, J., Kaplinski, M., Alexander, J.A., and Kohl, K., 2014, Monitoring and research to describe geomorphic effects of the 2011 controlled flood on the Green River in the Canyon of Lodore, Dinosaur National Monument, Colorado and Utah: U.S. Geological Survey Scientific Investigations Report 2014-5022, Report: vii, 66 p.; Appendix table 2.1; Digital products, https://doi.org/10.3133/sir20145022.","productDescription":"Report: vii, 66 p.; Appendix table 2.1; Digital products","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042269","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":285209,"type":{"id":7,"text":"Companion Files"},"url":"https://www.gcmrc.gov/research_areas/sediment_geomorphology/downloads/sir2014-5022/"},{"id":285207,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5022/pdf/sir2014-5022.pdf"},{"id":285208,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5022/downloads/sir2014-5022_appendix2-1.xlsx"},{"id":285210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145022.jpg"},{"id":285206,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5022/"}],"country":"United States","state":"Colorado;Utah","otherGeospatial":"Canyon Of Lodore;Dinosaur National Monument;Flaming Gorge Reservoir;Green River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.600243,40.449943 ], [ -109.600243,41.002142 ], [ -108.666903,41.002142 ], [ -108.666903,40.449943 ], [ -109.600243,40.449943 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517056e4b05569d805a337","contributors":{"authors":[{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hazel, Joseph E. Jr.","contributorId":91819,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph E.","suffix":"Jr.","affiliations":[],"preferred":false,"id":491484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaplinski, Matt","contributorId":65817,"corporation":false,"usgs":true,"family":"Kaplinski","given":"Matt","affiliations":[],"preferred":false,"id":491483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexander, Jason A.","contributorId":18270,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kohl, Keith 0000-0001-6812-0373 kkohl@usgs.gov","orcid":"https://orcid.org/0000-0001-6812-0373","contributorId":1323,"corporation":false,"usgs":true,"family":"Kohl","given":"Keith","email":"kkohl@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":491478,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70148120,"text":"70148120 - 2014 - Guidelines for a priori grouping of species in hierarchical community models","interactions":[],"lastModifiedDate":"2015-06-03T10:40:16","indexId":"70148120","displayToPublicDate":"2014-04-01T11:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Guidelines for a priori grouping of species in hierarchical community models","docAbstract":"<p>Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process borrows from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.</p>","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford","doi":"10.1002/ece3.976","usgsCitation":"Pacifici, K., Zipkin, E., Collazo, J., Irizarry, J.I., and DeWan, A.A., 2014, Guidelines for a priori grouping of species in hierarchical community models: Ecology and Evolution, v. 4, no. 7, p. 877-888, https://doi.org/10.1002/ece3.976.","productDescription":"12 p.","startPage":"877","endPage":"888","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049249","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473073,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.976","text":"External Repository"},{"id":301009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-22","publicationStatus":"PW","scienceBaseUri":"55702539e4b0d9246a9fd1a0","contributors":{"authors":[{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":548136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipkin, Elise ezipkin@usgs.gov","contributorId":470,"corporation":false,"usgs":true,"family":"Zipkin","given":"Elise","email":"ezipkin@usgs.gov","affiliations":[],"preferred":true,"id":548139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collazo, Jaime jaime_collazo@usgs.gov","contributorId":2613,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":547445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irizarry, Julissa I.","contributorId":141056,"corporation":false,"usgs":false,"family":"Irizarry","given":"Julissa","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":548140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWan, Amielle A.","contributorId":24486,"corporation":false,"usgs":true,"family":"DeWan","given":"Amielle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":548141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70100421,"text":"70100421 - 2014 - A 17-year record of environmental tracers in spring discharge, Shenandoah National Park, Virginia, USA: use of climatic data and environmental conditions to interpret discharge, dissolved solutes, and tracer concentrations","interactions":[],"lastModifiedDate":"2018-03-21T15:11:32","indexId":"70100421","displayToPublicDate":"2014-04-01T11:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"A 17-year record of environmental tracers in spring discharge, Shenandoah National Park, Virginia, USA: use of climatic data and environmental conditions to interpret discharge, dissolved solutes, and tracer concentrations","docAbstract":"A 17-year record (1995–2012) of a suite of environmental tracer concentrations in discharge from 34 springs located along the crest of the Blue Ridge Mountains in Shenandoah National Park (SNP), Virginia, USA, reveals patterns and trends that can be related to climatic and environmental conditions. These data include a 12-year time series of monthly sampling at five springs, with measurements of temperature, specific conductance, pH, and discharge recorded at 30-min intervals. The monthly measurements include age tracers (CFC-11, CFC-12, CFC-113, CFC-13, SF<sub>6</sub>, and SF<sub>5</sub>CF<sub>3</sub>), dissolved gases (N<sub>2</sub>, O<sub>2</sub>, Ar, CO<sub>2</sub>, and CH<sub>4</sub>), stable isotopes of water, and major and trace inorganic constituents. The chlorofluorocarbon (CFC) and sulfur hexafluoride (SF<sub>6</sub>) concentrations (in pptv) in spring discharge closely follow the concurrent monthly measurements of their atmospheric mixing ratios measured at the Air Monitoring Station at Big Meadows, SNP, indicating waters 0–3 years in age. A 2-year (2001–2003) record of unsaturated zone air displayed seasonal deviations from North American Air of ±10 % for CFC-11 and CFC-113, with excess CFC-11 and CFC-113 in peak summer and depletion in peak winter. The pattern in unsaturated zone soil CFCs is a function of gas solubility in soil water and seasonal unsaturated zone temperatures. Using the increase in the SF<sub>6</sub> atmospheric mixing ratio, the apparent (piston flow) SF<sub>6</sub> age of the water varied seasonally between about 0 (modern) in January and up to 3 years in July–August. The SF<sub>6</sub> concentration and concentrations of dissolved solutes (SiO<sub>2</sub>, Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>, Cl<sup>−</sup>, and HCO<sub>3</sub><sup>−</sup>) in spring discharge demonstrate a fraction of recent recharge following large precipitation events. The output of solutes in the discharge of springs minus the input from atmospheric deposition per hectare of watershed area (mol ha<sup>−1</sup> a<sup>−1</sup>) were approximately twofold greater in watersheds draining the regolith of Catoctin metabasalts than that of granitic gneisses and granitoid crystalline rocks. The stable isotopic composition of water in spring discharge broadly correlates with the Oceanic Niño Index. Below normal precipitation and enriched stable isotopic composition were observed during El Niño years.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10498-013-9202-y","usgsCitation":"Busenberg, E., and Plummer, N., 2014, A 17-year record of environmental tracers in spring discharge, Shenandoah National Park, Virginia, USA: use of climatic data and environmental conditions to interpret discharge, dissolved solutes, and tracer concentrations: Aquatic Geochemistry, v. 20, no. 2-3, p. 267-290, https://doi.org/10.1007/s10498-013-9202-y.","productDescription":"24 p.","startPage":"267","endPage":"290","numberOfPages":"24","ipdsId":"IP-044836","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":285189,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10498-013-9202-y"},{"id":285191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.1015,37.8742 ], [ -79.1015,39.0556 ], [ -78.0457,39.0556 ], [ -78.0457,37.8742 ], [ -79.1015,37.8742 ] ] ] } } ] }","volume":"20","issue":"2-3","noUsgsAuthors":false,"publicationDate":"2013-10-02","publicationStatus":"PW","scienceBaseUri":"53516eb2e4b05569d8059d17","contributors":{"authors":[{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":492200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":492201,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70148398,"text":"70148398 - 2014 - Animal reintroductions: an innovative assessment of survival","interactions":[],"lastModifiedDate":"2015-06-02T10:01:23","indexId":"70148398","displayToPublicDate":"2014-04-01T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Animal reintroductions: an innovative assessment of survival","docAbstract":"<p>Quantitative evaluations of reintroductions are infrequent and assessments of milestones reached before a project is completed, or abandoned due to lack of funding, are rare. However, such assessments, which are promoted in adaptive management frameworks, are critical. Quantification can provide defensible estimates of biological success, such as the number of survivors from a released cohort, with associated cost per animal. It is unlikely that the global issues of endangered wildlife and population declines will abate, therefore, assurance colonies and reintroductions are likely to become more common. If such endeavors are to be successful biologically or achieve adequate funding, implementation must be more rigorous and accountable. We use a novel application of a multistate, robust design capture-recapture model to estimate survival of reintroduced tadpoles through metamorphosis (i.e., the number of individuals emerging from the pond) and thereby provide a quantitative measure of effort and success for an \"in progress\" reintroduction of toads. Our data also suggest that tadpoles released at later developmental stages have an increased probability of survival and that eggs laid in the wild hatched at higher rates than eggs laid by captive toads. We illustrate how an interim assessment can identify problems, highlight successes, and provide information for use in adjusting the effort or implementing a Decision-Theoretic adaptive management strategy.</p>","language":"English","publisher":"Elsevier Science Ltd.","publisherLocation":"Kidlington, Oxford","doi":"10.1016/j.biocon.2014.02.034","usgsCitation":"Muths, E.L., Bailey, L., and Watry, M.K., 2014, Animal reintroductions: an innovative assessment of survival: Biological Conservation, v. 172, p. 200-208, https://doi.org/10.1016/j.biocon.2014.02.034.","productDescription":"9 p.","startPage":"200","endPage":"208","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052357","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":300968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"172","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"556ed3b5e4b0d9246a9fa7c0","contributors":{"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":547990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":547991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watry, Mary Kay","contributorId":141021,"corporation":false,"usgs":false,"family":"Watry","given":"Mary","email":"","middleInitial":"Kay","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":547992,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70125294,"text":"70125294 - 2014 - Population declines lead to replicate patterns of internal range structure at the tips of the distribution of the California red-legged frog (<i>Rana draytonii</i>)","interactions":[],"lastModifiedDate":"2014-09-16T10:47:24","indexId":"70125294","displayToPublicDate":"2014-04-01T10:45:50","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Population declines lead to replicate patterns of internal range structure at the tips of the distribution of the California red-legged frog (<i>Rana draytonii</i>)","docAbstract":"Demographic declines and increased isolation of peripheral populations of the threatened California red-legged frog (<i>Rana draytonii</i>) have led to the formation of internal range boundaries at opposite ends of the species’ distribution. While the population genetics of the southern internal boundary has been studied in some detail, similar information is lacking for the northern part of the range. In this study, we used microsatellite and mtDNA data to examine the genetic structuring and diversity of some of the last remaining <i>R. draytonii</i> populations in the northern Sierra Nevada, which collectively form the northern external range boundary. We compared these data to coastal populations in the San Francisco Bay Area, where the species is notably more abundant and still exists throughout much of its historic range. We show that ‘external’ Sierra Nevada populations have lower genetic diversity and are more differentiated from one another than their ‘internal’ Bay Area counterparts. This same pattern was mirrored across the distribution in California, where Sierra Nevada and Bay Area populations had lower allelic variability compared to those previously studied in coastal southern California. This genetic signature of northward range expansion was mirrored in the phylogeography of mtDNA haplotypes; northern Sierra Nevada haplotypes showed greater similarity to haplotypes from the south Coast Ranges than to the more geographically proximate populations in the Bay Area. These data cast new light on the geographic origins of Sierra Nevada <i>R. draytonii</i> populations and highlight the importance of distinguishing the genetic effects of contemporary demographic declines from underlying signatures of historic range expansion when addressing the most immediate threats to population persistence. Because there is no evidence of contemporary gene flow between any of the Sierra Nevada <i>R. draytonii</i> populations, we suggest that management activities should focus on maintaining and creating additional ponds to support breeding within typical dispersal distances of occupied habitat.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Applied Science Publishers","publisherLocation":"Barking, Essex England","doi":"10.1016/j.biocon.2014.02.026","usgsCitation":"Richmond, J.Q., Backlin, A.R., Tatarian, P.J., Solvesky, B.G., and Fisher, R.N., 2014, Population declines lead to replicate patterns of internal range structure at the tips of the distribution of the California red-legged frog (<i>Rana draytonii</i>): Biological Conservation, v. 172, p. 128-137, https://doi.org/10.1016/j.biocon.2014.02.026.","productDescription":"10 p.","startPage":"128","endPage":"137","numberOfPages":"10","ipdsId":"IP-053805","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":293920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293876,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2014.02.026"}],"volume":"172","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5419514ae4b091c7ffc8e7b8","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tatarian, Patricia J.","contributorId":8394,"corporation":false,"usgs":true,"family":"Tatarian","given":"Patricia","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":501166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solvesky, Ben G.","contributorId":78655,"corporation":false,"usgs":true,"family":"Solvesky","given":"Ben","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":501167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501163,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70129607,"text":"70129607 - 2014 - Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN","interactions":[],"lastModifiedDate":"2014-10-24T09:22:56","indexId":"70129607","displayToPublicDate":"2014-04-01T09:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN","docAbstract":"We developed a process model LM3-TAN to assess the combined effects of direct human influences and climate change on terrestrial and aquatic nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a soil denitrification, point N sources to streams (i.e., sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of the transport and fate of N in the vegetation–soil–river system in a comprehensive and consistent framework which is responsive to climatic variations and land-use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River Basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 16 monitoring stations as well as a reported budget for the entire basin. By accounting for interannual hydrologic variability, the model was able to capture interannual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream Susquehanna River Basin Commission station Marietta (40°02' N, 76°32' W), it captured the N loads well at multiple locations within the basin with different climate regimes, land-use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contributing to the various ecosystems are stored, lost, and exported via the river. Local analysis of six sub-basins showed combined effects of land use and climate on soil denitrification rates, with the highest rates in the Lower Susquehanna Sub-Basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna Sub-Basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification, indicating that anthropogenic N applications could drive substantial increase of N<sub>2</sub>O emission, an intermediate of the denitrification process.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-11-5809-2014","usgsCitation":"Lee, M., Malyshev, S., Shevliakova, E., Milly, P., and Jaffe, P.R., 2014, Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN: Biogeosciences, v. 11, p. 5809-5826, https://doi.org/10.5194/bg-11-5809-2014.","productDescription":"18 p.","startPage":"5809","endPage":"5826","numberOfPages":"18","ipdsId":"IP-058259","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":473077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-11-5809-2014","text":"Publisher Index Page"},{"id":295706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295705,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-11-5809-2014"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River","volume":"11","noUsgsAuthors":false,"publicationDate":"2014-10-20","publicationStatus":"PW","scienceBaseUri":"544b6a1ae4b03653c63fb1c3","contributors":{"authors":[{"text":"Lee, M.","contributorId":17932,"corporation":false,"usgs":true,"family":"Lee","given":"M.","affiliations":[],"preferred":false,"id":503907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malyshev, S.","contributorId":58210,"corporation":false,"usgs":true,"family":"Malyshev","given":"S.","affiliations":[],"preferred":false,"id":503908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, E.","contributorId":69910,"corporation":false,"usgs":true,"family":"Shevliakova","given":"E.","affiliations":[],"preferred":false,"id":503909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Milly, Paul C. D.","contributorId":100769,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C. D.","affiliations":[],"preferred":false,"id":503911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaffe, P. R.","contributorId":96204,"corporation":false,"usgs":true,"family":"Jaffe","given":"P.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":503910,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70128273,"text":"70128273 - 2014 - Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms","interactions":[{"subject":{"id":77062,"text":"sir20065148 - 2006 - Pesticide toxicity index for freshwater aquatic organisms, 2nd edition","indexId":"sir20065148","publicationYear":"2006","noYear":false,"title":"Pesticide toxicity index for freshwater aquatic organisms, 2nd edition"},"predicate":"SUPERSEDED_BY","object":{"id":70128273,"text":"70128273 - 2014 - Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms","indexId":"70128273","publicationYear":"2014","noYear":false,"title":"Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms"},"id":1}],"lastModifiedDate":"2015-04-13T11:35:23","indexId":"70128273","displayToPublicDate":"2014-04-01T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms","docAbstract":"<p>Pesticide mixtures are common in streams with agricultural or urban influence in the watershed. The Pesticide Toxicity Index (PTI) is a screening tool to assess potential aquatic toxicity of complex pesticide mixtures by combining measures of pesticide exposure and acute toxicity in an additive toxic-unit model. The PTI is determined separately for fish, cladocerans, and benthic invertebrates. This study expands the number of pesticides and degradates included in previous editions of the PTI from 124 to 492 pesticides and degradates, and includes two types of PTI for use in different applications, depending on study objectives. The Median-PTI was calculated from median toxicity values for individual pesticides, so is robust to outliers and is appropriate for comparing relative potential toxicity among samples, sites, or pesticides. The Sensitive-PTI uses the 5th percentile of available toxicity values, so is a more sensitive screening-level indicator of potential toxicity. PTI predictions of toxicity in environmental samples were tested using data aggregated from published field studies that measured pesticide concentrations and toxicity to <i>Ceriodaphnia dubia</i> in ambient stream water. <i>C. dubia</i> survival was reduced to &le; 50% of controls in 44% of samples with Median-PTI values of 0.1&ndash;1, and to 0% in 96% of samples with Median-PTI values &gt; 1. The PTI is a relative, but quantitative, indicator of potential toxicity that can be used to evaluate relationships between pesticide exposure and biological condition.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of The Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier Science","publisherLocation":"New York, NY","doi":"10.1016/j.scitotenv.2013.12.088","usgsCitation":"Nowell, L.H., Norman, J.E., Moran, P.W., Martin, J.D., and Stone, W.W., 2014, Pesticide Toxicity Index: a tool for assessing potential toxicity of pesticide mixtures to freshwater aquatic organisms: Science of the Total Environment, v. 476-477, p. 144-157, https://doi.org/10.1016/j.scitotenv.2013.12.088.","productDescription":"14 p.; appendixes","startPage":"144","endPage":"157","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046429","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":294975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294961,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.12.088"},{"id":294962,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0048969713015714"},{"id":299606,"type":{"id":3,"text":"Appendix"},"url":"https://water.usgs.gov/nawqa/pnsp/pubs/Nowell2014_STOTEN_PTI/Nowell2014_SuppInfo_PTI.zip","text":"Appendixes A-D"}],"volume":"476-477","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"543500b4e4b0a4f4b46a23b7","contributors":{"authors":[{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":502792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Julia E. 0000-0002-2820-6225 jnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2820-6225","contributorId":3832,"corporation":false,"usgs":true,"family":"Norman","given":"Julia","email":"jnorman@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":502795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Jeffrey D. 0000-0003-1994-5285 jdmartin@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-5285","contributorId":1066,"corporation":false,"usgs":true,"family":"Martin","given":"Jeffrey","email":"jdmartin@usgs.gov","middleInitial":"D.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502794,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70171348,"text":"70171348 - 2014 - Multibeam sonar (DIDSON) assessment of American shad (<i>Alosa sapidissima</i>) approaching a hydroelectric dam","interactions":[],"lastModifiedDate":"2016-05-30T13:11:24","indexId":"70171348","displayToPublicDate":"2014-04-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Multibeam sonar (DIDSON) assessment of American shad (<i>Alosa sapidissima</i>) approaching a hydroelectric dam","docAbstract":"<p><span>We investigated the fish community approaching the Veazie Dam on the Penobscot River, Maine, prior to implementation of a major dam removal and river restoration project. Multibeam sonar (dual-frequency identification sonar, DIDSON) surveys were conducted continuously at the fishway entrance from May to July in 2011. A 5% subsample of DIDSON data contained 43&thinsp;793 fish targets, the majority of which were of Excellent (15.7%) or Good (73.01%) observation quality. Excellent quality DIDSON targets (</span><i>n</i><span>&nbsp;= 6876) were apportioned by species using a Bayesian mixture model based on four known fork length distributions (river herring (alewife,</span><i>Alosa psuedoharengus</i><span>, and blueback herring,&nbsp;</span><i>Alosa aestivalis</i><span>), American shad,&nbsp;</span><i>Alosa sapidissima</i><span>) and two size classes (one sea-winter and multi-sea-winter) of Atlantic salmon (</span><i>Salmo salar</i><span>). 76.2% of targets were assigned to the American shad distribution; Atlantic salmon accounted for 15.64%, and river herring 8.16% of observed targets. Shad-sized (99.0%) and salmon-sized (99.3%) targets approached the fishway almost exclusively during the day, whereas river herring-sized targets were observed both during the day (51.1%) and at night (48.9%). This approach demonstrates how multibeam sonar imaging can be used to evaluate community composition and species-specific movement patterns in systems where there is little overlap in the length distributions of target species.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2013-0308","usgsCitation":"Grote, A.B., Bailey, M.M., Zydlewski, J.D., and Hightower, J.E., 2014, Multibeam sonar (DIDSON) assessment of American shad (<i>Alosa sapidissima</i>) approaching a hydroelectric dam: Canadian Journal of Fisheries and Aquatic Sciences, v. 71, no. 4, p. 545-558, https://doi.org/10.1139/cjfas-2013-0308.","productDescription":"14 p.","startPage":"545","endPage":"558","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046112","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d65e9e4b07e28b66848d3","contributors":{"authors":[{"text":"Grote, Ann B.","contributorId":169715,"corporation":false,"usgs":false,"family":"Grote","given":"Ann","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":630809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Michael M.","contributorId":169684,"corporation":false,"usgs":false,"family":"Bailey","given":"Michael","email":"","middleInitial":"M.","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":630810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":630684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":630811,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188051,"text":"70188051 - 2014 - Landsat-8: Science and product vision for terrestrial global change research","interactions":[],"lastModifiedDate":"2017-05-30T16:17:41","indexId":"70188051","displayToPublicDate":"2014-04-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Landsat-8: Science and product vision for terrestrial global change research","docAbstract":"<p><span>Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40&nbsp;year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2014.02.001","usgsCitation":"Roy, D.P., Wulder, M., Loveland, T., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D., Kennedy, R., Scambos, T.A., Schaaf, C.B., Schott, J.R., Sheng, Y., Vermote, E., Belward, A., Bindschadler, R., Cohen, W., Gao, F., Hipple, J.D., Hostert, P., Huntington, J., Justice, C., Kilic, A., Kovalskyy, V., Lee, Z.P., Lymburner, L., Masek, J.G., McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R., and Zhu, Z., 2014, Landsat-8: Science and product vision for terrestrial global change research: Remote Sensing of Environment, v. 145, p. 154-172, https://doi.org/10.1016/j.rse.2014.02.001.","productDescription":"19 p.","startPage":"154","endPage":"172","ipdsId":"IP-054700","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2014.02.001","text":"Publisher Index Page"},{"id":341888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"145","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c5e4b092b266f10d99","contributors":{"authors":[{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false},{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false},{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":696329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wulder, M.A.","contributorId":36287,"corporation":false,"usgs":true,"family":"Wulder","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":696533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":3005,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodcock, C. 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P.","contributorId":192458,"corporation":false,"usgs":false,"family":"Lee","given":"Z.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":696563,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Lymburner, Leo","contributorId":190978,"corporation":false,"usgs":false,"family":"Lymburner","given":"Leo","email":"","affiliations":[],"preferred":false,"id":696564,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Masek, J. G.","contributorId":105883,"corporation":false,"usgs":true,"family":"Masek","given":"J.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":696565,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"McCorkel, Joel","contributorId":192459,"corporation":false,"usgs":false,"family":"McCorkel","given":"Joel","email":"","affiliations":[],"preferred":false,"id":696566,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Shuai, Y.","contributorId":192460,"corporation":false,"usgs":false,"family":"Shuai","given":"Y.","email":"","affiliations":[],"preferred":false,"id":696567,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Trezza, R.","contributorId":192461,"corporation":false,"usgs":false,"family":"Trezza","given":"R.","email":"","affiliations":[],"preferred":false,"id":696568,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696569,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Wynne, R.H.","contributorId":147844,"corporation":false,"usgs":false,"family":"Wynne","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":696570,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Zhu, Z.","contributorId":10898,"corporation":false,"usgs":true,"family":"Zhu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":696571,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}}
,{"id":70095143,"text":"ofr20141041 - 2014 - Measurements of slope currents and internal tides on the Continental Shelf and slope off Newport Beach, California","interactions":[],"lastModifiedDate":"2014-03-31T15:11:50","indexId":"ofr20141041","displayToPublicDate":"2014-03-31T15:06:00","publicationYear":"2014","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":"2014-1041","title":"Measurements of slope currents and internal tides on the Continental Shelf and slope off Newport Beach, California","docAbstract":"An array of seven moorings housing current meters and oceanographic sensors was deployed for 6 months at 5 sites on the Continental Shelf and slope off Newport Beach, California, from July 2011 to January 2012. Full water-column profiles of currents were acquired at all five sites, and a profile of water-column temperature was also acquired at two of the five sites for the duration of the deployment. In conjunction with this deployment, the Orange County Sanitation District deployed four bottom platforms with current meters on the San Pedro Shelf, and these meters provided water-column profiles of currents. The data from this program will provide the basis for an investigation of the interaction between the deep water flow over the slope and the internal tide on the Continental Shelf.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141041","issn":"2331-1258","usgsCitation":"Rosenberger, K.J., Noble, M.A., and Norris, B., 2014, Measurements of slope currents and internal tides on the Continental Shelf and slope off Newport Beach, California: U.S. Geological Survey Open-File Report 2014-1041, vi, 65 p., https://doi.org/10.3133/ofr20141041.","productDescription":"vi, 65 p.","numberOfPages":"73","onlineOnly":"Y","ipdsId":"IP-046072","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":285157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141041.jpg"},{"id":285155,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1041/"},{"id":285156,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1041/pdf/ofr2014-1041.pdf"}],"country":"United States","state":"California","city":"Newport Beach","otherGeospatial":"Continental Shelf;Orange County Sanitation District;San Pedro Shelf","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.0,33.5 ], [ -118.0,33.633333 ], [ -117.8,33.633333 ], [ -117.8,33.5 ], [ -118.0,33.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517054e4b05569d805a31b","contributors":{"authors":[{"text":"Rosenberger, Kurt J. krosenberger@usgs.gov","contributorId":2575,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":491083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Marlene A. mnoble@usgs.gov","contributorId":1429,"corporation":false,"usgs":true,"family":"Noble","given":"Marlene","email":"mnoble@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norris, Benjamin","contributorId":65001,"corporation":false,"usgs":true,"family":"Norris","given":"Benjamin","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":491084,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048954,"text":"ds803 - 2014 - Groundwater-quality data in the Klamath Mountains study unit, 2010: results from the California GAMA Program","interactions":[],"lastModifiedDate":"2026-05-28T21:12:12.342599","indexId":"ds803","displayToPublicDate":"2014-03-28T15:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"803","title":"Groundwater-quality data in the Klamath Mountains study unit, 2010: results from the California GAMA Program","docAbstract":"<p>Groundwater quality in the 8,806-square-mile Klamath Mountains (KLAM) study unit was investigated by the U.S. Geological Survey (USGS) from October to December 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The KLAM study unit was the thirty-third study unit to be sampled as part of the GAMA-PBP.</p>\n\n<br>\n\n<p>The GAMA Klamath Mountains study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined by the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the KLAM study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallower groundwater may be more vulnerable to surficial contamination.</p>\n\n<br>\n\n<p>In the KLAM study unit, groundwater samples were collected from sites in Del Norte, Siskiyou, Humboldt, Trinity, Tehama, and Shasta Counties, California. Of the 39 sites sampled, 38 were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the primary aquifer system in the study unit (grid sites), and the remaining site was non-randomized (understanding site).</p>\n\n<br>\n\n<p>The groundwater samples were analyzed for basic field parameters, organic constituents (volatile organic compounds [VOCs] and pesticides and pesticide degradates), inorganic constituents (trace elements, nutrients, major and minor ions, total dissolved solids [TDS]), radon-222, gross alpha and gross beta radioactivity, and microbial indicators (total coliform and Escherichia coli [E. coli]). Isotopic tracers (stable isotopes of hydrogen and oxygen in water, isotopic ratios of dissolved strontium in water, and stable isotopes of carbon in dissolved inorganic carbon), dissolved noble gases, and age-dating tracers (tritium and carbon-14) were measured to help identify sources and ages of sampled groundwater.</p>\n\n<br>\n\n<p>Quality-control samples (field blanks, replicate sample pairs, and matrix spikes) were collected at 13 percent of the sites in the KLAM study unit, and the results were used to evaluate the quality of the data from the groundwater samples. Field blank samples rarely contained detectable concentrations of any constituent, indicating that contamination from sample collection or analysis was not a significant source of bias in the data for the groundwater samples. More than 99 percent of the replicate pair samples were within acceptable limits of variability. Matrix-spike sample recoveries were within the acceptable range (70 to 130 percent) for approximately 91 percent of the compounds.</p>\n\n<br>\n\n<p>This study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-health-based benchmarks established for aesthetic concerns by the CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.</p>\n\n<br>\n\n<p>All concentrations of organic constituents from grid sites sampled in the KLAM study unit were less than health-based benchmarks. In total, VOCs were detected in 16 of the 38 grid sites sampled (approximately 42 percent), pesticides and pesticide degradates were detected in 8 grid sites (about 21 percent), and microbial indicators were detected in 14 grid sites (approximately 37 percent).</p>\n\n<br>\n\n<p>Inorganic constituents (trace elements, major and minor ions, nutrients, and uranium and other radioactive constituents) and microbial indicators were sampled for at 38 grid sites, and all concentrations were less than health-based benchmarks, with the exception of one detection of boron greater than the CDPH notification level of 1,000 micrograms per liter (μg/L). Generally, concentrations of inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, and TDS) were less than the CDPH secondary maximum contaminant level (SMCL-CA). Exceptions include three detections of iron greater than the SMCL-CA of 300 μg/L, four detections of manganese greater than the SMCL-CA of 50 μg/L, one detection of chloride greater than the recommended SMCL-CA of 250 μg/L, and one detection of TDS greater than the recommended SMCL-CA of 500 μg/L.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds803","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., and Belitz, K., 2014, Groundwater-quality data in the Klamath Mountains study unit, 2010: results from the California GAMA Program: U.S. Geological Survey Data Series 803, x, 82 p., https://doi.org/10.3133/ds803.","productDescription":"x, 82 p.","numberOfPages":"96","ipdsId":"IP-036089","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":285118,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/803/pdf/ds803.pdf"},{"id":285117,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/803/"},{"id":285119,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds803.jpg"},{"id":504828,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99759.htm","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","otherGeospatial":"Klamath Mountains study unit","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.1,\n              42\n            ],\n            [\n              -121.8,\n              42\n            ],\n            [\n              -121.8,\n              40.1167\n            ],\n            [\n              -124.1,\n              40.1167\n            ],\n            [\n              -124.1,\n              42\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517044e4b05569d805a245","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":485868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":485867,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70099991,"text":"sir20145036 - 2014 - Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York","interactions":[],"lastModifiedDate":"2014-03-28T14:36:01","indexId":"sir20145036","displayToPublicDate":"2014-03-28T14:23:03","publicationYear":"2014","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":"2014-5036","title":"Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York","docAbstract":"<p>A three-dimensional groundwater-flow model is coupled with the particle-tracking program MODPATH to delineate zones of contribution to wells pumping from the Magothy aquifer and supplying water to a chlorinated volatile organic compound removal plant at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York. By use of driller’s logs, a transitional probability approach generated three alternative realizations of heterogeneity within the Magothy aquifer to assess uncertainty in model representation. Finer-grained sediments with low hydraulic conductivity were realized as laterally discontinuous, thickening towards the south, and comprising about 17 percent of the total aquifer volume.</p>\n\n<br>\n\n<p>Particle-tracking evaluations of a steady state present conditions model with alternative heterogeneity realizations were used to develop zones of contribution of remedial pumping wells. Because of heterogeneity and high rates of advection within the coarse-grained sediments, transport by dispersion and (or) diffusion was assumed to be negligible. Resulting zones of contribution of existing remedial wells are complex shapes, influenced by heterogeneity of each realization and other nearby hydrologic stresses. The use of two particle tracking techniques helped identify zones of contribution to wells. Backtracking techniques and observations of points of intersection of backward-tracked particles at shells of the GM–38 Hot Spot, as defined by surfaces of equal total volatile organic compound concentration, identified the source of water within the GM–38 Hot Spot to simulated wells. Forward-tracking techniques identified the fate of water within the GM–38 Hot Spot, including well capture and discharge to model constant head and drain boundaries. The percentage of backward-tracked particles, started at GM–38 wells that were sourced from within the Hot Spot, varied from 72.0 to 98.2, depending on the Hot Spot delineation used (present steady state model and Magothy aquifer heterogeneity realization A). The percentage of forward-tracked particles that were captured by GM–38 wells varied from 81.1 to 94.6, depending on the Hot Spot delineation used, with the remainder primarily captured by Bethpage Water District Plant 4 production wells (present steady state model and Magothy aquifer heterogeneity realization A). Less than 1 percent of forward-tracked particles ultimately discharge at model constant head and drain boundaries. The differences between forward- and backward-tracked particle percentage ranges are due to some forward-tracked particles not being captured by GM–38 wells, and some backward-tracked particles not intersecting specific regions of the Hot Spot.</p>\n\n<br>\n\n<p>During 2013, an aquifer test generated detailed time series of well pumping rates and corresponding water-level responses were recorded at numerous locations. These data were used to verify the present conditions steady state model and demonstrate the sensitivity of model results to transient-state changes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145036","collaboration":"Prepared in cooperation with the Naval Facilities Engineering Command","usgsCitation":"Misut, P., 2014, Simulation of zones of contribution to wells at site GM–38, Naval Weapons Industrial Reserve Plant, Bethpage, New York: U.S. Geological Survey Scientific Investigations Report 2014-5036, vii, 58 p., https://doi.org/10.3133/sir20145036.","productDescription":"vii, 58 p.","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-053917","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":285106,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5036/pdf/sir2014-5036.pdf"},{"id":285107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145036.jpg"},{"id":285104,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5036/"}],"country":"United States","state":"New York","otherGeospatial":"Bethpage","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.506,40.731 ], [ -73.506,40.769 ], [ -73.464,40.769 ], [ -73.464,40.731 ], [ -73.506,40.731 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517063e4b05569d805a3b7","contributors":{"authors":[{"text":"Misut, Paul","contributorId":93822,"corporation":false,"usgs":true,"family":"Misut","given":"Paul","affiliations":[],"preferred":false,"id":492102,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70095234,"text":"ofr20131020 - 2014 - High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts","interactions":[],"lastModifiedDate":"2014-03-28T13:46:51","indexId":"ofr20131020","displayToPublicDate":"2014-03-28T13:34:34","publicationYear":"2014","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":"2013-1020","title":"High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts","docAbstract":"Geophysical and geospatial data were collected in Buzzards Bay, in the shallow-water areas of Vineyard Sound, and in the nearshore areas off the eastern Elizabeth Islands and northern coast of Martha's Vineyard, Massachusetts, on the U.S. Geological Survey research vessel Rafael between 2007 and 2011, in a collaborative effort between the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management. This report describes results of this collaborative effort, which include mapping the geology of the inner shelf zone of the Elizabeth Islands and the sand shoals of Vineyard Sound and studying geologic processes that contribute to the evolution of this area. Data collected during these surveys include: bathymetry, acoustic backscatter, seismic-reflection profiles, sound velocity profiles, and navigation. The long-term goals of this project are (1) to provide high-resolution geophysical data that will support research on the influence of sea-level change and sediment supply on coastal evolution and (2) to inventory subtidal marine habitats and their distribution within the coastal zone of Massachusetts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131020","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Pendleton, E., Andrews, B., Danforth, W.W., and Foster, D.S., 2014, High-resolution geophysical data collected aboard the U.S. Geological Survey research vessel Rafael to supplement existing datasets from Buzzards Bay and Vineyard Sound, Massachusetts: U.S. Geological Survey Open-File Report 2013-1020, HTML Document, https://doi.org/10.3133/ofr20131020.","productDescription":"HTML Document","onlineOnly":"Y","ipdsId":"IP-043330","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":285101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131020.jpg"},{"id":285099,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1020/"},{"id":285100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1020/ofr2013-1020_title_page.html"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"MultiPolygon\", \"coordinates\": [[[[-70.79227441738965, 41.44497545414981], [-70.80612581695954, 41.43263440255333], [-70.81255303494635, 41.438314269611276], [-70.80517628590349, 41.44267786112675], [-70.79227441738965, 41.44497545414981]]], [[[-70.5741772862491, 41.47005818491886], [-70.58134701901037, 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,{"id":70094150,"text":"sim3289 - 2014 - Bathymetric maps and water-quality profiles of Table Rock and North Saluda Reservoirs, Greenville County, South Carolina","interactions":[],"lastModifiedDate":"2017-01-13T09:51:23","indexId":"sim3289","displayToPublicDate":"2014-03-28T10:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3289","title":"Bathymetric maps and water-quality profiles of Table Rock and North Saluda Reservoirs, Greenville County, South Carolina","docAbstract":"Lakes and reservoirs are the water-supply source for many communities. As such, water-resource managers that oversee these water supplies require monitoring of the quantity and quality of the resource. Monitoring information can be used to assess the basic conditions within the reservoir and to establish a reliable estimate of storage capacity. In April and May 2013, a global navigation satellite system receiver and fathometer were used to collect bathymetric data, and an autonomous underwater vehicle was used to collect water-quality and bathymetric data at Table Rock Reservoir and North Saluda Reservoir in Greenville County, South Carolina. These bathymetric data were used to create a bathymetric contour map and stage-area and stage-volume relation tables for each reservoir. Additionally, statistical summaries of the water-quality data were used to provide a general description of water-quality conditions in the reservoirs.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3289","issn":"2329-132X","collaboration":"Prepared in cooperation with Greenville Water","usgsCitation":"Clark, J.M., Journey, C.A., Nagle, D.D., and Lanier, T.H., 2014, Bathymetric maps and water-quality profiles of Table Rock and North Saluda Reservoirs, Greenville County, South Carolina: U.S. Geological Survey Scientific Investigations Map 3289, Map: 36.00 x 32.00 inches, https://doi.org/10.3133/sim3289.","productDescription":"Map: 36.00 x 32.00 inches","onlineOnly":"Y","ipdsId":"IP-052115","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":285090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3289.jpg"},{"id":285088,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3289/"},{"id":285089,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3289/pdf/sim3289.pdf"}],"scale":"4000","projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"South Carolina","county":"Greenville County","otherGeospatial":"North Saluda Reservoirs, Table Rock","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.75,35.0 ], [ -82.75,35.25 ], [ -82.25,35.25 ], [ -82.25,35.0 ], [ -82.75,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517027e4b05569d805a176","contributors":{"authors":[{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":490446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagle, Doug D. ddnagle@usgs.gov","contributorId":2697,"corporation":false,"usgs":true,"family":"Nagle","given":"Doug","email":"ddnagle@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":490447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lanier, Timothy H. 0000-0001-5104-3308 thlanier@usgs.gov","orcid":"https://orcid.org/0000-0001-5104-3308","contributorId":4171,"corporation":false,"usgs":true,"family":"Lanier","given":"Timothy","email":"thlanier@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490448,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70142794,"text":"70142794 - 2014 - Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013","interactions":[],"lastModifiedDate":"2018-03-23T14:24:18","indexId":"70142794","displayToPublicDate":"2014-03-28T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013","docAbstract":"<p>The assessment of Great Lakes prey fish stocks have been conducted annually with bottom trawls since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. These stock assessments provide data on the status and trends of prey fish that are consumed by important commercial and recreational fishes. Although all these annual surveys are conducted using bottom trawls, they differ among the lakes in the proportion of the lake covered, seasonal timing, trawl gear used, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique, population indices were standardized to the highest value for a time series within each lake for the following prey species: Cisco (Coregonus artedi), Bloater (C. hoyi), Rainbow Smelt (Osmerus mordax), Alewife (Alosa pseudoharengus), and Round Goby (Neogobius melanostomus). In this report, standardized indices are presented in graphical form along with synopses to provide a short, informal cross-basin summary of the status and trends of principal prey fishes. There was basin-wide agreement in the trends of age-1 and older biomass for all prey species, with the highest concordance occurring for coregonids and Rainbow Smelt, and weaker concordance for Alewife. For coregonids, the highest biomass occurred from the mid-1980s to the mid-1990s. Rainbow Smelt biomass declined slowly and erratically during the last quarter century. Alewife biomass was generally higher from the early 1980s through 1990s across the Great Lakes, but since the early 1990s, trends have been divergent across the lakes, though there has been a downward trend in all lakes since 2005. Recently, Lake Huron has shown resurgence in biomass of Bloater, achieving 75% of its maximum record in 2012 due to recruitment of a succession of strong and moderate year classes that appeared in 2005-2011. Also, strong recruitment of the 2010 year class of Alewife has led to a sharp increase in biomass of Alewife in Lake Michigan. In general, trends in year-class strengths were less concordant across the basin and only coregonids showed statistical agreement across the upper Great Lakes. The appearance of strong and moderate year-classes of Bloater in Lake Huron in 2005- 2011 countered the trend of continuing weak year-classes of coregonids in Lakes Michigan and Superior. Not shown in our analysis is the appearance of the 2013 year-class of Bloater in Huron, the largest to date. There was no agreement in cross-basin trends in year-class strengths for Rainbow Smelt and Alewife, although there was agreement between pairs of lakes. Although there was statistical agreement in trends of age-0 and older Round Goby biomass among lakes where this species has successfully invaded (Michigan, Huron, Erie and Ontario), temporal patterns of biomass in each lake were different. Round Goby may be approaching equilibrium in Lake Erie, peaking in Lake Huron, and expanding in Lake Michigan. The trend in Lake Ontario remains unclear. Declining abundance in Lake Erie has corresponded with evidence that Round Goby have become increasingly incorporated into piscivore diets, e.g., Lake Trout, Walleye, Smallmouth Bass, Yellow Perch, and Burbot in Lakes Michigan, Huron, Erie, and Ontario. Round Goby continue to be absent from spring bottom trawl assessments in Lake Superior, but their presence in the harbors and embayments of Duluth and Thunder Bay (U.S. Geological Survey and Ontario Ministry of Natural Resources, unpublished data), suggests that there is potential for future colonization.</p>","language":"English","publisher":"Great Lakes Fishery Commission","publisherLocation":"Ann Arbor, Michigan","doi":"10.3133/70142794","collaboration":"Great Lakes Fishery Commission","usgsCitation":"Gorman, O.T., and Weidel, B., 2014, Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013, 9 p., https://doi.org/10.3133/70142794.","productDescription":"9 p.","startPage":"1","endPage":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055696","costCenters":[{"id":324,"text":"Great Lakes Science 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,{"id":70099932,"text":"ofr20141065 - 2014 - Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington","interactions":[],"lastModifiedDate":"2023-05-26T15:30:08.282033","indexId":"ofr20141065","displayToPublicDate":"2014-03-27T16:12:50","publicationYear":"2014","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":"2014-1065","title":"Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington","docAbstract":"High-resolution topographic surveys allow fairly precise mapping of landslide deposits and their relative ages. Relative ages are determined by cross-cutting relations and the amount of smoothing—more smoothed slide deposits are older—of these deposits. The Tulalip Tribes, in partnership with the Puget Sound Lidar Consortium, acquired a high-resolution lidar (light detection and ranging) survey of the North Fork Stillaguamish River valley in 2013. This report presents a preliminary interpretation of the topography of this area using the lidar data at a scale of 1:24,000.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141065","usgsCitation":"Haugerud, R.A., 2014, Preliminary interpretation of pre-2014 landslide deposits in the vicinity of Oso, Washington: U.S. Geological Survey Open-File Report 2014-1065, Report: 4 pages; GIS Data Zip File, https://doi.org/10.3133/ofr20141065.","productDescription":"Report: 4 pages; GIS Data Zip File","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055838","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":417505,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99750.htm","linkFileType":{"id":5,"text":"html"}},{"id":285073,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1065/","linkFileType":{"id":5,"text":"html"}},{"id":285075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1065/pdf/ofr2014-1065.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":285077,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141065.png"},{"id":285076,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1065/downloads/ofr2014-1065_GIS.zip"}],"country":"United States","state":"Washington","city":"Oso","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.940536,48.258349 ], [ -121.940536,48.297727 ], [ -121.880529,48.297727 ], [ -121.880529,48.258349 ], [ -121.940536,48.258349 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351705be4b05569d805a371","contributors":{"authors":[{"text":"Haugerud, Ralph A. 0000-0001-7302-4351 rhaugerud@usgs.gov","orcid":"https://orcid.org/0000-0001-7302-4351","contributorId":2691,"corporation":false,"usgs":true,"family":"Haugerud","given":"Ralph","email":"rhaugerud@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492070,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70073968,"text":"ofr20141003 - 2014 - Hydrologic Drought Decision Support System (HyDroDSS)","interactions":[],"lastModifiedDate":"2014-03-27T14:22:43","indexId":"ofr20141003","displayToPublicDate":"2014-03-27T14:06:00","publicationYear":"2014","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":"2014-1003","title":"Hydrologic Drought Decision Support System (HyDroDSS)","docAbstract":"<p>The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought.</p>\n<br/>\n<p>This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime.</p>\n<br/>\n<p>Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow.</p>\n<br/>\n<p>Rank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done.</p>\n<br/>\n<p>Drought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used.</p>\n<br/>\n<p>This report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS.</p>\n<br/>\n<p>A case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141003","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Granato, G., 2014, Hydrologic Drought Decision Support System (HyDroDSS): U.S. Geological Survey Open-File Report 2014-1003, Report: x, 91 p.; Make CD by ISO package, https://doi.org/10.3133/ofr20141003.","productDescription":"Report: x, 91 p.; Make CD by ISO package","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042923","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141003.jpg"},{"id":285059,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1003/ofr2014-1003_CDROM.iso"},{"id":285057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1003/"},{"id":285058,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1003/pdf/ofr2014-1003.pdf"}],"projection":"Rhode Island state plane projection","country":"United States","state":"Rhode Island","city":"East Greenwich","otherGeospatial":"Hunt River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.575284,41.507592 ], [ -71.575284,41.674953 ], [ -71.426104,41.674953 ], [ -71.426104,41.507592 ], [ -71.575284,41.507592 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517047e4b05569d805a262","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":489307,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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