The southeastern USA is home to one of the richest—and most imperiled and threatened—freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20 years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2014.931745","usgsCitation":"Midway, S., Wagner, T., and Tracy, B., 2016, A hierarchical community occurrence model for North Carolina stream fish: Transactions of the American Fisheries Society, v. 143, no. 5, p. 1348-1357, https://doi.org/10.1080/00028487.2014.931745.","productDescription":"10 p.","startPage":"1348","endPage":"1357","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052105","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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B.H.","contributorId":72194,"corporation":false,"usgs":true,"family":"Tracy","given":"B.H.","email":"","affiliations":[],"preferred":false,"id":638989,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178685,"text":"70178685 - 2016 - Influence of slip-surface geometry on earth-flow deformation, Montaguto earth flow, southern Italy","interactions":[],"lastModifiedDate":"2016-12-02T12:08:30","indexId":"70178685","displayToPublicDate":"2014-08-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of slip-surface geometry on earth-flow deformation, Montaguto earth flow, southern Italy","docAbstract":"We investigated relations between slip-surface geometry and deformational structures and hydrologic features at the Montaguto earth flow in southern Italy between 1954 and 2010. We used 25 boreholes, 15 static cone-penetration tests, and 22 shallow-seismic profiles to define the geometry of basal- and lateral-slip surfaces; and 9 multitemporal maps to quantify the spatial and temporal distribution of normal faults, thrust faults, back-tilted surfaces, strike-slip faults, flank ridges, folds, ponds, and springs. We infer that the slip surface is a repeating series of steeply sloping surfaces (risers) and gently sloping surfaces (treads). Stretching of earth-flow material created normal faults at risers, and shortening of earth-flow material created thrust faults, back-tilted surfaces, and ponds at treads. Individual pairs of risers and treads formed quasi-discrete kinematic zones within the earth flow that operated in unison to transmit pulses of sediment along the length of the flow. The locations of strike-slip faults, flank ridges, and folds were not controlled by basal-slip surface topography but were instead dependent on earth-flow volume and lateral changes in the direction of the earth-flow travel path. The earth-flow travel path was strongly influenced by inactive earth-flow deposits and pre-earth-flow drainages whose positions were determined by tectonic structures. The implications of our results that may be applicable to other earth flows are that structures with strikes normal to the direction of earth-flow motion (e.g., normal faults and thrust faults) can be used as a guide to the geometry of basal-slip surfaces, but that depths to the slip surface (i.e., the thickness of an earth flow) will vary as sediment pulses are transmitted through a flow.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2014.04.039","usgsCitation":"Guerriero, L., Coe, J.A., Revellio, P., Grelle, G., Pinto, F., and Guadagno, F., 2016, Influence of slip-surface geometry on earth-flow deformation, Montaguto earth flow, southern Italy: Geomorphology, v. 219, p. 285-305, https://doi.org/10.1016/j.geomorph.2014.04.039.","productDescription":"21 p. 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2016 - Differential response of carbon fluxes to climate in three peatland ecosystems that vary in the presence and stability of permafrost","interactions":[],"lastModifiedDate":"2016-08-16T15:21:35","indexId":"70175552","displayToPublicDate":"2014-08-14T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Differential response of carbon fluxes to climate in three peatland ecosystems that vary in the presence and stability of permafrost","docAbstract":"Changes in vegetation and soil properties following permafrost degradation and thermokarst development in peatlands may cause changes in net carbon storage. To better understand these dynamics, we established three sites in Alaska that vary in permafrost regime, including a black spruce peat plateau forest with stable permafrost, an internal collapse scar bog formed as a result of thermokarst, and a rich fen without permafrost. Measurements include year-round eddy covariance estimates of carbon dioxide (CO2), water, and energy fluxes, associated environmental variables, and methane (CH4) fluxes at the collapse scar bog. The ecosystems all acted as net sinks of CO2 in 2011 and 2012, when air temperature and precipitation remained near long-term means. In 2013, under a late snowmelt and late leaf out followed by a hot, dry summer, the permafrost forest and collapse scar bog were sources of CO2. In this same year, CO2 uptake in the fen increased, largely because summer inundation from groundwater inputs suppressed ecosystem respiration. CO2 exchange in the permafrost forest and collapse scar bog was sensitive to warm air temperatures, with 0.5 g C m−2 lost each day when maximum air temperature was very warm (≥29°C). The bog lost 4981 ± 300 mg CH4 m−2 between April and September 2013, indicating that this ecosystem acted as a significant source of both CO2 and CH4 to the atmosphere in 2013. These results suggest that boreal peatland responses to warming and drying, both of which are expected to occur in a changing climate, will depend on permafrost regime.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JG002683","usgsCitation":"Euskirchen, E.S., Edgar, C., Turetsky, M., Waldrop, M.P., and Harden, J.W., 2016, Differential response of carbon fluxes to climate in three peatland ecosystems that vary in the presence and stability of permafrost: Journal of Geophysical Research: Biogeosciences, v. 119, no. 8, p. 1576-1595, https://doi.org/10.1002/2014JG002683.","startPage":"1576","endPage":"1595","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056009","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":326591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"119","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-14","publicationStatus":"PW","scienceBaseUri":"57b43942e4b03bcb01039fa7","contributors":{"authors":[{"text":"Euskirchen, Eugenie S. 0000-0002-0848-4295","orcid":"https://orcid.org/0000-0002-0848-4295","contributorId":173730,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugenie","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":645658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edgar, C.W.","contributorId":173731,"corporation":false,"usgs":false,"family":"Edgar","given":"C.W.","email":"","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":645659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":645660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":645657,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":645661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70137535,"text":"70137535 - 2016 - Optimizing surveillance for South American origin influenza A viruses along the United States Gulf Coast through genomic characterization of isolates from blue-winged teal (Anas discors)","interactions":[],"lastModifiedDate":"2018-09-04T16:36:44","indexId":"70137535","displayToPublicDate":"2014-07-23T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing surveillance for South American origin influenza A viruses along the United States Gulf Coast through genomic characterization of isolates from blue-winged teal (Anas discors)","docAbstract":"Relative to research focused on intercontinental viral exchange between Eurasia and North America, less attention has been directed towards understanding the redistribution of influenza A viruses (IAVs) by wild birds between North America and South America. In this study, we genomically characterized 45 viruses isolated from blue-winged teal (Anas discors) along the Texas and Louisiana Gulf Coast during March of 2012 and 2013, coincident with northward migration of this species from Neotropical wintering areas to breeding grounds in the United States and Canada. No evidence of South American lineage genes were detected in IAVs isolated from blue-winged teal supporting restricted viral gene flow between the United States and southern South America. However, it is plausible that blue-winged teal redistribute IAVs between North American breeding grounds and wintering areas throughout the Neotropics, including northern South America, and that viral gene flow is limited by geographical barriers further south (e.g. the Amazon Basin). Surveillance for the introduction of IAVs from Central America and northern South America into the United States may be further optimized through genomic characterization of viruses resulting from coordinated, concurrent sampling efforts targeting blue-winged teal and sympatric species throughout the Neotropics and along the United States Gulf Coast.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Berlin, Germany","doi":"10.1111/tbed.12244","usgsCitation":"Ramey, A.M., Walther, P., Link, P.K., Poulson, R.L., Wilcox, B.R., Newsome, G.M., Spackman, E., Brown, J., and Stallknecht, D.E., 2016, Optimizing surveillance for South American origin influenza A viruses along the United States Gulf Coast through genomic characterization of isolates from blue-winged teal (Anas discors): Transboundary and Emerging Diseases, v. 63, no. 2, p. 194-202, https://doi.org/10.1111/tbed.12244.","productDescription":"9 p.","startPage":"194","endPage":"202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054903","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471477,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1111/tbed.12244","text":"Publisher Index Page"},{"id":298640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-24","publicationStatus":"PW","scienceBaseUri":"55095031e4b02e76d757e62d","chorus":{"doi":"10.1111/tbed.12244","url":"http://dx.doi.org/10.1111/tbed.12244","publisher":"Wiley-Blackwell","authors":"Ramey A. 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A total of 27 individuals of N. boops were collected during five sampling efforts from 1999 to 2005. These specimens represent an addition to the state fauna, a distributional record for the Little Kanawha River, and an eastern range extension for this species on the Appalachian Plateau, West Virginia. Notropis boops in the South Fork Hughes River drainage likely represents a native population.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-172.2.372","usgsCitation":"Welsh, S., Cincotta, D.A., and Raesly, R.L., 2016, First record of the bigeye shiner (Notropis boops) from West Virginia: American Midland Naturalist, v. 172, no. 2, p. 373-375, https://doi.org/10.1674/0003-0031-172.2.372.","productDescription":"3 p.","startPage":"373","endPage":"375","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053142","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Little Kanawha River, South Fork Hughes River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.5570068359375,\n 38.76693348394693\n ],\n [\n -81.5570068359375,\n 39.296048244024085\n ],\n [\n -80.870361328125,\n 39.296048244024085\n ],\n [\n -80.870361328125,\n 38.76693348394693\n ],\n [\n -81.5570068359375,\n 38.76693348394693\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"172","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576913bae4b07657d19ff059","contributors":{"authors":[{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cincotta, Daniel A.","contributorId":172052,"corporation":false,"usgs":false,"family":"Cincotta","given":"Daniel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raesly, Richard L.","contributorId":172208,"corporation":false,"usgs":false,"family":"Raesly","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":13481,"text":"Department of Biology, Frostburg State University, 101 Braddock Road, Frostburg, MD","active":true,"usgs":false}],"preferred":false,"id":639925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170509,"text":"70170509 - 2016 - High-precision relocation of long-period events beneath the summit region of Kı̄lauea Volcano, Hawai‘i, from 1986 to 2009","interactions":[],"lastModifiedDate":"2016-04-25T09:50:52","indexId":"70170509","displayToPublicDate":"2014-05-30T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"High-precision relocation of long-period events beneath the summit region of Kı̄lauea Volcano, Hawai‘i, from 1986 to 2009","docAbstract":"Long-period (0.5–5 Hz, LP) seismicity has been recorded for decades in the summit region of Kı̄lauea Volcano, Hawai‘i, and is postulated as linked with the magma transport and shallow hydrothermal systems. To better characterize its spatiotemporal occurrence, we perform a systematic analysis of 49,030 seismic events occurring in the Kı̄lauea summit region from January 1986 to March 2009 recorded by the ∼50-station Hawaiian Volcano Observatory permanent network. We estimate 215,437 P wave spectra, considering all events on all stations, and use a station-averaged spectral metric to consistently classify LP and non-LP seismicity. We compute high-precision relative relocations for 5327 LP events (43% of all classified LP events) using waveform cross correlation and cluster analysis with 6.4 million event pairs, combined with the source-specific station term method. The majority of intermediate-depth (5–15 km) LPs collapse to a compact volume, with remarkable source location stability over 23 years indicating a source process controlled by geological or conduit structure.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, DC","doi":"10.1002/2014GL059819","collaboration":"Robin Matoza; Peter Shearer","usgsCitation":"Matoza, R.S., Shearer, P., and Okubo, P.G., 2016, High-precision relocation of long-period events beneath the summit region of Kı̄lauea Volcano, Hawai‘i, from 1986 to 2009: Geophysical Research Letters, v. 41, no. 10, p. 3413-3421, https://doi.org/10.1002/2014GL059819.","productDescription":"9 p.","startPage":"3413","endPage":"3421","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057155","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471478,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014gl059819","text":"Publisher Index Page"},{"id":320502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","county":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.35354614257812,\n 19.33090654245574\n ],\n [\n -155.35354614257812,\n 19.46141299683289\n ],\n [\n -155.12832641601562,\n 19.46141299683289\n ],\n [\n -155.12832641601562,\n 19.33090654245574\n ],\n [\n -155.35354614257812,\n 19.33090654245574\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-20","publicationStatus":"PW","scienceBaseUri":"571f3fbbe4b071321fe56a38","contributors":{"authors":[{"text":"Matoza, Robin S.","contributorId":54873,"corporation":false,"usgs":true,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":627501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shearer, Peter M.","contributorId":78946,"corporation":false,"usgs":true,"family":"Shearer","given":"Peter M.","affiliations":[],"preferred":false,"id":627502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Okubo, Paul G. 0000-0002-0381-6051 pokubo@usgs.gov","orcid":"https://orcid.org/0000-0002-0381-6051","contributorId":2730,"corporation":false,"usgs":true,"family":"Okubo","given":"Paul","email":"pokubo@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":627500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159352,"text":"70159352 - 2016 - Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities","interactions":[],"lastModifiedDate":"2023-03-28T13:13:32.849685","indexId":"70159352","displayToPublicDate":"2014-05-28T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":857,"text":"Aquaculture Research","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities","docAbstract":"Effects of eugenol (AQUI-S®20E, 10% active eugenol) sedation on cool water, yellow perch Perca flavescens (Mitchill), and warm water, Nile tilapia Oreochromis niloticus L. fish metabolic rates were assessed. Both species were exposed to 0, 10, 20 and 30 mg L−1 eugenol using static respirometry. In 17°C water and loading densities of 60, 120 and 240 g L−1, yellow perch controls (0 mg L−1 eugenol) had metabolic rates of 329.6–400.0 mg O2 kg−1 h−1, while yellow perch exposed to 20 and 30 mg L−1 eugenol had significantly reduced metabolic rates of 258.4–325.6 and 189.1–271.0 mg O2 kg−1 h−1 respectively. Nile tilapia exposed to 30 mg L−1 eugenol had a significantly reduced metabolic rate (424.5 ± 42.3 mg O2 kg−1 h−1) relative to the 0 mg L−1 eugenol control (546.6 ± 53.5 mg O2 kg−1 h−1) at a loading density of 120 g L−1 in 22°C water. No significant differences in metabolic rates for Nile tilapia were found at 240 or 360 g L−1 loading densities when exposed to eugenol. Results suggest that eugenol sedation may benefit yellow perch welfare at high densities (e.g. live transport) due to a reduction in metabolic rates, while further research is needed to assess the benefits of eugenol sedation on Nile tilapia at high loading densities.
","language":"English","publisher":"Wiley","doi":"10.1111/are.12485","usgsCitation":"Cupp, A.R., Fredricks, K., Hartleb, C.F., and Gaikowski, M., 2016, Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities: Aquaculture Research, v. 47, no. 1, p. 234-242, https://doi.org/10.1111/are.12485.","productDescription":"9 p.","startPage":"234","endPage":"242","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055053","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471479,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/are.12485","text":"Publisher Index Page"},{"id":310614,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"562b5a2de4b00162522207ca","contributors":{"authors":[{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":578127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":5163,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim T.","email":"kfredricks@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":578128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartleb, Christopher F.","contributorId":149356,"corporation":false,"usgs":false,"family":"Hartleb","given":"Christopher","email":"","middleInitial":"F.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":578131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":578132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70101962,"text":"70101962 - 2016 - Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities","interactions":[],"lastModifiedDate":"2015-12-14T13:43:02","indexId":"70101962","displayToPublicDate":"2014-05-01T11:49:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":857,"text":"Aquaculture Research","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities","docAbstract":"Effects of eugenol (AQUI-S®20E, 10% active eugenol) sedation on cool water, yellow perch Perca flavescens (Mitchill), and warm water, Nile tilapia Oreochromis niloticus L. fish metabolic rates were assessed. Both species were exposed to 0, 10, 20 and 30 mg L−1 eugenol using static respirometry. In 17°C water and loading densities of 60, 120 and 240 g L−1, yellow perch controls (0 mg L−1 eugenol) had metabolic rates of 329.6–400.0 mg O2 kg−1 h−1, while yellow perch exposed to 20 and 30 mg L−1 eugenol had significantly reduced metabolic rates of 258.4–325.6 and 189.1–271.0 mg O2 kg−1 h−1 respectively. Nile tilapia exposed to 30 mg L−1 eugenol had a significantly reduced metabolic rate (424.5 ± 42.3 mg O2 kg−1 h−1) relative to the 0 mg L−1 eugenol control (546.6 ± 53.5 mg O2 kg−1 h−1) at a loading density of 120 g L−1 in 22°C water. No significant differences in metabolic rates for Nile tilapia were found at 240 or 360 g L−1 loading densities when exposed to eugenol. Results suggest that eugenol sedation may benefit yellow perch welfare at high densities (e.g. live transport) due to a reduction in metabolic rates, while further research is needed to assess the benefits of eugenol sedation on Nile tilapia at high loading densities.
","language":"English","publisher":"Wiley","doi":"10.1111/are.12485","usgsCitation":"Cupp, A.R., Hartleb, C.F., Fredricks, K., and Gaikowski, M.P., 2016, Effectiveness of eugenol sedation to reduce the metabolic rates of cool and warm water fish at high loading densities: Aquaculture Research, v. 47, no. 1, p. 234-242, https://doi.org/10.1111/are.12485.","productDescription":"9 p.","startPage":"234","endPage":"242","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053888","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/are.12485","text":"Publisher Index Page"},{"id":287958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287957,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/are.12485"}],"volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"53ae7696e4b0abf75cf2bfb6","contributors":{"authors":[{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":492814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartleb, Christopher F.","contributorId":75855,"corporation":false,"usgs":true,"family":"Hartleb","given":"Christopher","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":492816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":5163,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim T.","email":"kfredricks@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":492815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":492813,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173898,"text":"70173898 - 2016 - Reproductive success and habitat characteristics of Golden-winged Warblers in high-elevation pasturelands","interactions":[],"lastModifiedDate":"2016-06-15T12:42:05","indexId":"70173898","displayToPublicDate":"2014-01-30T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive success and habitat characteristics of Golden-winged Warblers in high-elevation pasturelands","docAbstract":"The Golden-winged Warbler (Vermivora chrysoptera) is one of the most rapidly declining vertebrate species in the Appalachian Mountains. It is the subject of extensive range-wide research and conservation action. However, little is known about this species' breeding ecology in high-elevation pasturelands, a breeding habitat with conservation potential considering the U.S. Natural Resource Conservation Service's Working Lands for Wildlife program targeting private lands in the Appalachian Mountains. We located 100 nests of Golden-winged Warblers in pastures in and around the Monongahela National Forest in West Virginia during 2008–2012. Daily nest survival rate (mean ± SE = 0.962 ± 0.006), clutch size (4.5 ± 0.1), and number of young fledged per nest attempt (2.0 ± 0.2) and successful nest (4.0 ± 0.1) fell within the range of values reported in other parts of the species' range and were not significantly affected by year or the presence/absence of cattle grazing. Classification tree analysis revealed that nests were in denser vegetation (≥52%) and closer to forest edges (<36.0 m) and shrubs (<7.0 cm) than random locations within the male's territory. Successful nests had significantly more woody cover (≥9%) within 1 m than failed nests. Our results suggest that cattle grazing at 1.2–2.4 ha of forage/animal unit with periodic mowing can create and maintain these characteristics without interfering with the nesting of Golden-winged Warblers. High-elevation pasturelands may provide a refuge for remaining populations of Golden-winged Warblers in this region.
","language":"English","publisher":"BioOne","publisherLocation":"Washington, D.C.","doi":"10.1676/13-114.1","usgsCitation":"Wood, P., and Aldinger, K.R., 2016, Reproductive success and habitat characteristics of Golden-winged Warblers in high-elevation pasturelands: Wilson Journal of Ornithology, v. 126, no. 2, p. 279-287, https://doi.org/10.1676/13-114.1.","productDescription":"9 p.","startPage":"279","endPage":"287","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028560","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57627c37e4b07657d19a6a0f","contributors":{"authors":[{"text":"Wood, Petra pbwood@usgs.gov","contributorId":169812,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":638946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":639022,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047189,"text":"70047189 - 2016 - Manganese nodules","interactions":[],"lastModifiedDate":"2017-06-27T13:43:00","indexId":"70047189","displayToPublicDate":"2014-01-01T11:49:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Manganese nodules","docAbstract":"The existence of manganese (Mn) nodules (Figure 1) has been known since the late 1800s when they were collected during the Challenger expedition of 1873–1876. However, it was not until after WWII that nodules were further studied in detail for their ability to adsorb metals from seawater. Many of the early studies did not distinguish Mn nodules from Mn crusts. Economic interest in Mn nodules began in the late 1950s and early 1960s when John Mero finished his Ph.D. thesis on this subject, which was published in the journal Economic Geology (Mero, 1962) and later as a book (Mero, 1965). By the mid-1970s, large consortia had formed to search for and mine Mn nodules that occur between the Clarion and Clipperton fracture zones (CCZ) in the NE Pacific (Figure 2). This is still the area considered of greatest economic potential in the global ocean because of high nickel (Ni), copper (Cu), and Mn contents and the dense distribution of nodules in the area. While the mining of nodules was fully expected to begin in the late 1970s or early 1980s, this never occurred due to a downturn in the price of metals on the global market. Since then, many research cruises have been undertaken to study the CCZ nodules, and now 15 contracts for exploration sites have been given or are pending by the International Seabed Authority (ISA). Many books and science journal articles have been published summarizing the early work (e.g., Baturin, 1988; Halbach et al., 1988), and research has continued to the present day (e.g., ISA, 1999; ISA, 2010). Although the initial attraction for nodules was their high Ni, Cu, and Mn contents, subsequent work has shown that nodules host large quantities of other critical metals needed for high-tech, green-tech, and energy applications (Hein et al., 2013; Hein and Koschinsky, 2014).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of marine geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Hein, J.R., 2016, Manganese nodules, chap. of Encyclopedia of marine geosciences, p. 408-412.","productDescription":"5 p.","startPage":"408","endPage":"412","ipdsId":"IP-049388","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":329475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342851,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/referenceworkentry/10.1007/978-94-007-6238-1_26"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe679fe4b0824b2d143719","contributors":{"editors":[{"text":"Harff, Jan","contributorId":63957,"corporation":false,"usgs":false,"family":"Harff","given":"Jan","email":"","affiliations":[],"preferred":false,"id":519981,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Petersen, Sven","contributorId":76586,"corporation":false,"usgs":false,"family":"Petersen","given":"Sven","email":"","affiliations":[],"preferred":false,"id":519982,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Thiede, Jorn","contributorId":88085,"corporation":false,"usgs":false,"family":"Thiede","given":"Jorn","email":"","affiliations":[],"preferred":false,"id":519983,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":2828,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":518092,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048986,"text":"ofr20121266 - 2016 - Bathymetric terrain model of the Atlantic margin for marine geological investigations","interactions":[],"lastModifiedDate":"2025-04-10T15:47:38.104628","indexId":"ofr20121266","displayToPublicDate":"2013-12-03T14:03:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1266","title":"Bathymetric terrain model of the Atlantic margin for marine geological investigations","docAbstract":"A bathymetric terrain model of the Atlantic margin covering almost 725,000 square kilometers of seafloor from the New England Seamounts in the north to the Blake Basin in the south is compiled from existing multibeam bathymetric data for marine geological investigations. Although other terrain models of the same area are extant, they are produced from either satellite-derived bathymetry at coarse resolution (ETOPO1), or use older bathymetric data collected by using a combination of single beam and multibeam sonars (Coastal Relief Model). The new multibeam data used to produce this terrain model have been edited by using hydrographic data processing software to maximize the quality, usability, and cartographic presentation of the combined 100-meter resolution grid. The final grid provides the largest high-resolution, seamless terrain model of the Atlantic margin..
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121266","collaboration":"Prepared in cooperation with the U.S. Nuclear Regulatory Commission and the National Oceanic and Atmospheric Administration","usgsCitation":"Andrews, B., Chaytor, J., ten Brink, U., Brothers, D., Gardner, J.V., Lobecker, E.A., and Calder, B.R., 2016, Bathymetric terrain model of the Atlantic margin for marine geological investigations (Originally posted December 3, 2013; Version 2.0: May 25, 2016): U.S. Geological Survey Open-File Report 2012-1266, Report: vi, 12 p.; 1 Plate: 34 x 44 inches, https://doi.org/10.3133/ofr20121266.","productDescription":"Report: vi, 12 p.; 1 Plate: 34 x 44 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042694","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321436,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1266/ofr20121266_plate1.pdf","size":"224 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1266"},{"id":280161,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2012/1266/title_page.html","text":"Title Page","linkFileType":{"id":5,"text":"html"},"description":"OFR 2012-1266"},{"id":280162,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121266.GIF"},{"id":280159,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1266/"},{"id":280160,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1266/pdf/ofr20121266_v2.pdf","text":"Report","size":"3.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1266"},{"id":321437,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2012/1266/versionHist.txt","size":"2 MB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2012-1266"}],"projection":"Mercator Projection","country":"United States","geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"Polygon\", \"coordinates\": [[[-73.990880318804216, 33.01264651249938], [-76.177520201754476, 33.091051926629071], [-75.698376004295199, 34.511061093644571], [-74.875119155933476, 35.45555931929227], [-74.779290316441632, 37.146980850626349], [-74.522294792349953, 37.547719633955907], [-73.847137059566478, 38.309994493550107], [-73.193758608485723, 38.681660632687567], [-71.600531692308323, 40.026021055247213], [-69.508342808469592, 39.982462491841702], [-69.199077008291354, 40.056512049630946], [-69.107604025140176, 40.296084148360578], [-68.645883253042939, 40.161052601803874], [-68.144959773881169, 40.49209768368479], [-67.535139886205798, 40.422403982236055], [-66.942743423892523, 40.614061661219928], [-65.912845523979058, 41.517915052123776], [-65.276890498260514, 41.160734832199637], [-65.795237402784551, 40.616252789632284], [-65.69505270695214, 40.516068093799888], [-63.020011669307671, 40.487826667598029], [-62.954087379549208, 40.38069969674067], [-64.339510213776634, 39.77339458773816], [-64.213190379900993, 39.564313483392247], [-66.837158239441294, 38.363839475939926], [-67.22047359740867, 37.950033123588796], [-67.758421855465201, 37.826326803517404], [-67.706151579378741, 37.530128572360809], [-70.217302759699066, 37.434299732869007], [-72.491909742100063, 35.603103845332321], [-72.936207088835033, 34.334403118951634], [-73.053815210029597, 34.360538256994865], [-73.990880318804216, 33.01264651249938]]]}, \"properties\": {\"extentType\": \"Custom\", \"code\": \"\", \"name\": \"\", \"notes\": \"\", \"promotedForReuse\": false, \"abbreviation\": \"\", \"shortName\": \"\", \"description\": \"\"}, \"bbox\": [-76.177520201754476, 33.01264651249938, -62.954087379549208, 41.517915052123776], \"type\": \"Feature\", \"id\": \"3091982\"}","edition":"Originally posted December 3, 2013; Version 2.0: May 25, 2016","contact":"Director, Woods Hole Coastal and Marine Science Center
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543-1598
http://woodshole.er.usgs.gov/
Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2013.799466","usgsCitation":"Wagner, T., Irwin, B.J., Bence, J.R., and Daniel B. Hayes, 2016, Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives: Fisheries, v. 38, no. 7, p. 309-319, https://doi.org/10.1080/03632415.2013.799466.","productDescription":"11 p.","startPage":"309","endPage":"319","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038862","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-11","publicationStatus":"PW","scienceBaseUri":"5757f032e4b04f417c24da47","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":637158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bence, James R.","contributorId":171360,"corporation":false,"usgs":false,"family":"Bence","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":26875,"text":"Michigan State University, East Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":637161,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Daniel B. Hayes","contributorId":171359,"corporation":false,"usgs":false,"family":"Daniel B. Hayes","affiliations":[{"id":26875,"text":"Michigan State University, East Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":637160,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70045254,"text":"ds760 - 2016 - Geophysical log database for the Floridan aquifer system and southeastern Coastal Plain aquifer system in Florida and parts of Georgia, Alabama, and South Carolina","interactions":[],"lastModifiedDate":"2024-10-22T23:06:15.14091","indexId":"ds760","displayToPublicDate":"2013-04-04T00:00:00","publicationYear":"2016","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":"760","title":"Geophysical log database for the Floridan aquifer system and southeastern Coastal Plain aquifer system in Florida and parts of Georgia, Alabama, and South Carolina","docAbstract":"A database of borehole geophysical logs and other types of data files were compiled as part of ongoing studies of water availability and assessment of brackish- and saline-water resources. The database contains 4,883 logs from 1,248 wells in Florida, Georgia, Alabama, South Carolina, and from a limited number of offshore wells of the eastern Gulf of Mexico and the Atlantic Ocean. The logs can be accessed through a download directory organized by state and county for onshore wells and in a single directory for the offshore wells. A flat file database is provided that lists the wells, their coordinates, and the file listings.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds760","collaboration":"Groundwater Resources Program","usgsCitation":"Williams, L.J., Raines, J.E., and Lanning, A.E., 2016, Geophysical log database for the Floridan aquifer system and southeastern Coastal Plain aquifer system in Florida and parts of Georgia, Alabama, \nand South Carolina (ver. 1.1, December 2016): U.S. Geological Survey Data Series 760, 12 p., https://doi.org/10.3133/ds760.","productDescription":"Report: v, 12 p.; Geophysical Log Database; List of Wells in Database; List of Files in Database; Downloads Directory","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":270569,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/760/"},{"id":270573,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/760/Downloads/FILES/LogDB_WellListRevision1.xls","text":"List of Wells (Excel)","size":"475 KB"},{"id":270570,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/760/pdf/ds760.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 760"},{"id":270574,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/760/Downloads","text":"State Data Files"},{"id":270575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/760/images/coverthb3.jpg"},{"id":331292,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/760/versionHist.txt","size":"3.96 MB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":331324,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/760/Downloads/FILES/LogDB_WellListRevision1.csv","text":"List of Wells (CSV)","size":"189 KB"},{"id":331302,"rank":10,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/760/Downloads/Readme.txt","linkFileType":{"id":2,"text":"txt"}},{"id":270572,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/760/Downloads/FILES/LogDB_FileListRevision1.xls","text":"List of Files (Excel)","size":"1.69 MB"},{"id":331323,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/760/Downloads/FILES/LogDB_FileListRevision1.csv","text":"List of Files (CSV)","size":"882 MB"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.0,24.0 ], [ -89.0,34.0 ], [ -79.0,34.0 ], [ -79.0,24.0 ], [ -89.0,24.0 ] ] ] } } ] }","edition":"Version 1.0: Originally posted April 4, 2013; Version 1.1: December 30, 2016","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Production and management variables such as carbon dioxide (CO2) level, water velocity, and feeding frequency influence the growth and fillet attributes of rainbow trout (Oncorhynchus mykiss), as well as cost of production. More information is needed to determine the contributions of these variables to growth and fillet attributes to find the right balance between input costs and fish performance. Two studies, of 84 and 90 days duration, were conducted to determine the effects of CO2 level, water velocity, and feed frequency on rainbow trout growth, fillet yield, and fillet quality. In the first study, two CO2levels (30 and 49 mg/L) and two velocity levels (0.5 and 2.0 body lengths/s) were tested. In the second study two CO2 levels (30 and 49 mg/L) and two feeding regimens (fed once daily to satiation or three times daily to satiation) were tested. In the first study, after 84 days, fillet weight from high CO2 tanks was 13.5% lower than the fillet weights of fish from low CO2 tanks. Percent fat of fillets was higher in low CO2 fish (P = 0.05) after 84 days and, fish from the low CO2 treatment were larger (P < 0.01). Both studies had similar results in regards to fat content and weight of fillets in response to elevated CO2levels. Velocity had little affect on either whole wet weight or fillet attributes of rainbow trout in this study. Muscle tissue contained more (P < 0.01) fat when fish were fed three times daily (7.3%; day 90) compared to once daily (5.4%; day 90). Also, fish were larger (P < 0.05) when fed 3 times per day (1079 g; day 90) in comparison to only one daily feeding (792 g; day 90). Fish in high feed/high CO2 tanks were larger and had more fillet fat than fish from low feed/low CO2 tanks. To maximize rainbow trout growth at aquaculture facilities, management strategies should attempt to keep CO2 levels below 30 mg/L when cost efficient. However, feeding 2–3 times daily should reduce production losses if CO2 cannot be minimized. The effect of strain and velocity were minimal over the range we tested in comparison to the effects of CO2 and feeding regimen.
A goal of the U.S. Geological Survey Groundwater Resources Program is to assess the availability of fresh water within each of the principal aquifers in the United States with the greatest groundwater withdrawals. The Floridan aquifer system (FAS), which covers an area of approximately 100,000 square miles in Florida and parts of Georgia, Alabama, Mississippi, and South Carolina, is one such principal aquifer, having the fifth largest groundwater withdrawals in the Nation, totaling 3.64 billion gallons per day in 2000. Compilation of FAS hydraulic properties is critical to the development and calibration of groundwater flow models that can be used to develop water budgets spatially and temporally, as well as to evaluate resource changes over time. Wells with aquifer test data were identified as Upper Floridan aquifer (UFA), Lower Floridan aquifer (LFA), Floridan aquifer system (FAS, Upper Floridan with some middle and/or Lower Floridan), or middle Floridan confining unit (MCU), based on the identification from the original database or report description, or comparison of the open interval of the well with previously published maps.
This report consolidates aquifer hydraulic property data obtained from multiple databases and reports of the U.S. Geological Survey, various State agencies, and the Water Management Districts of Florida, that are compiled into tables to provide a single information source for transmissivity and storage properties of the FAS as of October 2011. Transmissivity calculated from aquifer pumping tests and specific-capacity data are included. Values for transmissivity and storage coefficients are intended for use in regional or sub regional groundwater flow models; thus, any tests (aquifer pumping tests and specific capacity data) that were conducted with packers or for open intervals less than 30 feet in length are excluded from the summary statistics and tables of this report, but are included in the database.
The transmissivity distribution from the aquifer pumping tests is highly variable. The transmissivity based on aquifer pumping tests (from 1,045 values for the UFA and FAS) ranges from 8 to about 9,300,000 square feet per day (ft2/d) and values of storage coefficient (646 reported) range from 3x10-9 to 0.41. The 64 transmissivity values for the LFA range from about 130 to 4,500,000 ft2/d, and the 17 storage coefficient values range from 7x10-8 to 0.03. The 14 transmissivity values for the MCU range from 1 to about 600,000 ft2/d and the 10 storage coefficient values range from 8x10-8 to 0.03. Transmissivity estimates for the UFA and FAS for 442 specific capacity tests range from approximately 200 to 1,000,000 ft2/d.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds669","collaboration":"Product of the U.S. Geological Survey Groundwater Resources Program","usgsCitation":"Kuniansky, E.L., and Bellino, J.C., 2016, Tabulated transmissivity and storage properties of the Floridan aquifer system in Florida and parts of Georgia, South Carolina, and Alabama (ver. 1.1, May 2016): U.S. Geological Survey Data Series 669, 37 p., https://pubs.usgs.gov/ds/669.","productDescription":"Report: v, 16 p.; 2 Tables; Database","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":254564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/669/images/coverthb.jpg"},{"id":254562,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/669/","linkFileType":{"id":5,"text":"html"},"description":"DS 669"},{"id":321205,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/669/versionHist.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"DS 669"},{"id":321208,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/669/tables/ds669_table2-v1.1.pdf","text":"Table 2 -Transmissivity estimates from specific capacity data","size":"157 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 669"},{"id":321207,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/669/tables/ds669_table1-v1.1.xls","text":"Table 1 - Excel","size":"355 KB xls","description":"DS 669"},{"id":321206,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/669/tables/ds669_table1-v1.1.pdf","text":"Table 1 - Transmissivity and storage coefficients from aquifer pumping tests","size":"321 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 669"},{"id":504105,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_96739.htm","linkFileType":{"id":5,"text":"html"}},{"id":321211,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/669/DS669_v1.1FAS_AQT_DATA_04192016.zip","text":"Aquifer Data","size":"1 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 669"},{"id":321209,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/669/tables/ds669_table2-v1.1.xls","text":"Table 2 - Excel","size":"132 KB xls","description":"DS 669"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90,25 ], [ -90,34 ], [ -79.5,34 ], [ -79.5,25 ], [ -90,25 ] ] ] } } ] }","edition":"Version 1.1 May 13, 2016","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Surveyr
4446 Pet Lane, Suite 108r
Lutz, FL 33559r
Telephone: (813) 498–5000r
http://fl.water.usgs.gov/
Dilution of aluminum discharged to reservoirs in filter-backwash effluents at water-treatment facilities in Massachusetts was investigated by a field study and computer simulation. Determination of dilution is needed so that permits for discharge ensure compliance with water-quality standards for aquatic life. The U.S. Environmental Protection Agency chronic standard for aluminum, 87 micrograms per liter (μg/L), rather than the acute standard, 750 μg/L, was used in this investigation because the time scales of chronic exposure (days) more nearly match rates of change in reservoir concentrations than do the time scales of acute exposure (hours).
Whereas dilution factors are routinely computed for effluents discharged to streams solely on the basis of flow of the effluent and flow of the receiving stream, dilution determination for effluents discharged to reservoirs is more complex because (1), compared to streams, additional water is available for dilution in reservoirs during low flows as a result of reservoir flushing and storage during higher flows, and (2) aluminum removal in reservoirs occurs by aluminum sedimentation during the residence time of water in the reservoir. Possible resuspension of settled aluminum was not considered in this investigation. An additional concern for setting discharge standards is the substantial concentration of aluminum that can be naturally present in ambient surface waters, usually in association with dissolved organic carbon (DOC), which can bind aluminum and keep it in solution.
A method for dilution determination was developed using a mass-balance equation for aluminum and considering sources of aluminum from groundwater, surface water, and filter-backwash effluents and losses caused by sedimentation, water withdrawal, and spill discharge from the reservoir. The method was applied to 13 reservoirs. Data on aluminum and DOC concentrations in reservoirs and influent water were collected during the fall of 2009. Complete reservoir volume was determined to be available for mixing on the basis of vertical and horizontal aluminum-concentration profiling. Losses caused by settling of aluminum were assumed to be proportional to aluminum concentration and reservoir area. The constant of proportionality, as a function of DOC concentration, was established by simulations in each of five reservoirs that differed in DOC concentration.
In addition to computing dilution factors, the project determined dilution factors that would be protective with the same statistical basis (frequency of exceedance of the chronic standard) as dilutions computed for streams at the 7-day-average 10-year-recurrence annual low flow (the 7Q10). Low-flow dilutions are used for permitting so that receiving waters are protected even at the worst-case flow levels. The low-flow dilution factors that give the same statistical protection are the lowest annual 7-day-average dilution factors with a recurrence of 10 years, termed 7DF10s. Determination of 7DF10 values for reservoirs required that long periods of record be simulated so that dilution statistics could be determined. Dilution statistics were simulated for 13 reservoirs from 1960 to 2004 using U.S. Geological Survey Firm-Yield Estimator software to model reservoir inputs and outputs and present-day values of filter-effluent discharge and aluminum concentration.
Computed settling velocities ranged from 0 centimeters per day (cm/d) at DOC concentrations of 15.5 milligrams per liter (mg/L) to 21.5 cm/d at DOC concentrations of 2.7 mg/L. The 7DF10 values were a function of aluminum effluent discharged. At current (2009) effluent discharge rates, the 7DF10 values varied from 1.8 to 115 among the 13 reservoirs. In most cases, the present-day (2009) discharge resulted in receiving water concentrations that did not exceed the standard at the 7DF10. Exceptions were one reservoir with a very small area and three reservoirs with high concentrations of DOC. Maximum permissible discharges were determined for water-treatment plants by adjusting discharges upward in simulations until the 7DF10 resulted in reservoir concentrations that just met the standard. In terms of aluminum flux, these discharges ranged from 0 to 28 kilograms of aluminum per day.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115136","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Colman, J.A., Massey, A.J., and Levin, S.B., 2016, Determination of dilution factors for discharge of aluminum-containing wastes by public water-supply treatment facilities into lakes and reservoirs in Massachusetts (ver. 1.1, December 2016): U.S. Geological Survey Scientific Investigations Report 2011–5136, 36 p., https://pubs.usgs.gov/sir/2011/5136.","productDescription":"vi, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":116564,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5136/images/coverthb.jpg"},{"id":94131,"rank":100,"type":{"id":15,"text":"Index 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\"}}]}","edition":"Version 1.0: Originally posted September 16, 2011; Version 1.1: December 30, 2016","contact":"Director, Massachusetts-Rhode Island Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
(508) 490-5000
http://ma.water.usgs.gov
Presentation. No abstract available.
","conferenceTitle":"Encontro Nacional de Engenharia de Sedimentos, 8th","conferenceDate":"November 2-8, 2008","conferenceLocation":"Campo Grande, Brazil","language":"English","usgsCitation":"Meade, R.H., and Moody, J.A., 2016, Changes in the discharge of sediment through the Missouri-Mississippi River system, 1940-2007, Encontro Nacional de Engenharia de Sedimentos, 8th, Campo Grande, Brazil, November 2-8, 2008, CD.","productDescription":"CD","ipdsId":"IP-009209","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":340142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea0e4b006455f2d61d0","contributors":{"authors":[{"text":"Meade, Robert H. 0000-0002-4965-3040 rhmeade@usgs.gov","orcid":"https://orcid.org/0000-0002-4965-3040","contributorId":2744,"corporation":false,"usgs":true,"family":"Meade","given":"Robert","email":"rhmeade@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":623169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":623168,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179395,"text":"70179395 - 2016 - Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems","interactions":[],"lastModifiedDate":"2017-05-25T12:32:52","indexId":"70179395","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems","docAbstract":"Iconic sagebrush ecosystems of the American West are threatened by larger and more frequent wildfires that can kill sagebrush and facilitate invasion by annual grasses, creating a cycle that alters sagebrush ecosystem recovery post disturbance. Thwarting this accelerated grass–fire cycle is at the forefront of current national conservation efforts, yet its impacts on wildlife populations inhabiting these ecosystems have not been quantified rigorously. Within a Bayesian framework, we modeled 30 y of wildfire and climatic effects on population rates of change of a sagebrush-obligate species, the greater sage-grouse, across the Great Basin of western North America. Importantly, our modeling also accounted for variation in sagebrush recovery time post fire as determined by underlying soil properties that influence ecosystem resilience to disturbance and resistance to invasion. Our results demonstrate that the cumulative loss of sagebrush to direct and indirect effects of wildfire has contributed strongly to declining sage-grouse populations over the past 30 y at large spatial scales. Moreover, long-lasting effects from wildfire nullified pulses of sage-grouse population growth that typically follow years of higher precipitation. If wildfire trends continue unabated, model projections indicate sage-grouse populations will be reduced to 43% of their current numbers over the next three decades. Our results provide a timely example of how altered fire regimes are disrupting recovery of sagebrush ecosystems and leading to substantial declines of a widespread indicator species. Accordingly, we present scenario-based stochastic projections to inform conservation actions that may help offset the adverse effects of wildfire on sage-grouse and other wildlife populations.","language":"English","publisher":"HighWire Press","doi":"10.1073/pnas.1606898113","usgsCitation":"Coates, P.S., Ricca, M.A., Prochazka, B.G., Brooks, M.L., Doherty, K., Kroger, T., Blomberg, E.J., Hagen, C.A., and Casazza, M.L., 2016, Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems: PNAS, v. 113, no. 45, p. 12745-12750, https://doi.org/10.1073/pnas.1606898113.","productDescription":"6 p.","startPage":"12745","endPage":"12750","ipdsId":"IP-078711","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1606898113","text":"Publisher Index Page"},{"id":332700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"45","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-25","publicationStatus":"PW","scienceBaseUri":"586781f9e4b0cd2dabe7c71f","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":657072,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroger, Travis 0000-0002-4168-6323 tkroger@usgs.gov","orcid":"https://orcid.org/0000-0002-4168-6323","contributorId":177794,"corporation":false,"usgs":true,"family":"Kroger","given":"Travis","email":"tkroger@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657073,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":657074,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":657075,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657076,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":75513,"text":"sir20055289 - 2016 - Development and evaluation of clear-water pier and contraction scour envelope curves in the Coastal Plain and Piedmont Provinces of South Carolina","interactions":[],"lastModifiedDate":"2017-06-01T08:57:09","indexId":"sir20055289","displayToPublicDate":"2006-03-13T00:00:00","publicationYear":"2016","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":"2005-5289","title":"Development and evaluation of clear-water pier and contraction scour envelope curves in the Coastal Plain and Piedmont Provinces of South Carolina","docAbstract":"The U.S. Geological Survey in cooperation with the South Carolina Department of Transportation collected clear-water pier- and contraction-scour data at 116 bridges in the Coastal Plain and Piedmont Physiographic Provinces of South Carolina. Pier-scour depths collected in both provinces ranged from 0 to 8.0 feet. Contraction-scour depths collected in the Coastal Plain ranged from 0 to 3.9 feet. Using hydraulic data estimated with a one-dimensional flow model, predicted clear-water scour depths were computed with scour equations from the Federal Highway Administration Hydraulic Engineering Circular 18 and compared with measured scour. This comparison indicated that predicted clear-water scour depths, in general, exceeded measured scour depths and at times were excessive. Predicted clear-water contraction scour, however, was underpredicted approximately 30 percent of the time by as much as 7.1 feet.
The investigation focused on clear-water pier scour, comparing trends in the laboratory and field data. This comparison indicated that the range of dimensionless variables (relative depth, flow intensity, relative grain size) used in laboratory investigations of pier scour, were similar to the range for field data in South Carolina, further indicating that laboratory relations may have some applicability to field conditions in South Carolina. Variables determined to be important in developing pier scour in laboratory studies were investigated to understand their influence on the South Carolina field data, and many of these variables appeared to be insignificant under field conditions in South Carolina. The strongest explanatory variables were pier width and approach velocity. Envelope curves developed from the field data are useful tools for evaluating reasonable ranges of clear-water pier and contraction scour in South Carolina. A modified version of the Hydraulic Engineering Circular 18 pier-scour equation also was developed as a tool for evaluating clearwater pier scour. The envelope curves and modified equation offer an improvement over the current methods for predicting clear-water scour in South Carolina.
Data from this study were compiled into a database that includes photographs, measured scour depths, predicted scour depths, limited basin characteristics, limited soil data, and modeled hydraulic data. The South Carolina database can be used to compare studied sites with unstudied sites to evaluate the potential for scour at the unstudied sites. In addition, the database can be used to evaluate the performance of various methods for predicting clear-water pier and contraction scour.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20055289","collaboration":"Prepared in cooperation with the South Carolina Department of Transportaton","usgsCitation":"Benedict, S., and Caldwell, A.W., 2016, Development and evaluation of clear-water pier and contraction scour envelope curves in the Coastal Plain and Piedmont Provinces of South Carolina (Version 1.0: Originally posted 2006; Version 1.1: August 31, 2016): U.S. Geological Survey Scientific Investigations Report 2005-5289, Report: x, 98 p.; Database, https://doi.org/10.3133/sir20055289.","productDescription":"Report: x, 98 p.; Database","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":7316,"rank":100,"type":{"id":25,"text":"Version 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Carolina\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: Originally posted 2006; Version 1.1: August 31, 2016","contact":"South Carolina Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://sc.water.usgs.gov/
This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644327,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":50958,"text":"wri034064 - 2016 - Clear-water abutment and contraction scour in the Coastal Plain and Piedmont Provinces of South Carolina, 1996-99","interactions":[],"lastModifiedDate":"2017-01-20T09:25:23","indexId":"wri034064","displayToPublicDate":"2003-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4064","title":"Clear-water abutment and contraction scour in the Coastal Plain and Piedmont Provinces of South Carolina, 1996-99","docAbstract":"The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, collected observations of clear-water aburment and contraction scour at 146 bridges in the Coastal Plain and Piedmont of South Carolina. Scour depths ranged from 0 to 23.6 feet. Theoretical scour depths were computed at each bridge and compared with observed scour. This comparison showed that theoretical scour depths, in general, exceeded the observed scour depths and often were excessive. A comparison of field data with dimensionless relations for laboratory data showed that the range of dimensionless variables used in laboratory investigations was outside of the range for field data in South Carolina, suggesting laboratory relations may not be applicable to field conditions in South Carolina. Variables determined to be important in developing scour within laboratory studies were investigated to understand their influence within the South Carolina field data, and many of these variables appeared to be insignificant under field conditions found in South Carolina. The strongest explanatory variables were embankment length, geometric-contraction ratio, approach velocity, and soil cohesion. Envelope curves developed with the field data are useful tools for assessing reasonable ranges of scour depth in South Carolina. These tools are simple to apply and are an improvement over the current methods for predicting theoretical scour.
\nData from this study have been compiled into a database that includes photographs, figures, observed scour depths, theoretical scour depths, limited basin characteristics, limited soil data, and theoretical hydraulic data. The database can be used to compare studied sites with unstudied sites to assess the potential for scour at the unstudied sites. In addition, the database can be used to assess the performance of various theoretical methods for predicting clear-water abutment and contraction scour.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/wri034064","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation","usgsCitation":"Benedict, S., 2016, Clear-water abutment and contraction scour in the Coastal Plain and Piedmont Provinces of South Carolina, 1996-99 (Version 1.0: Originally posted in 2003; Version 1.1: August 31, 2016): U.S. Geological Survey Water-Resources Investigations Report 2003-4064, Report: x, 137 p.; Appendix A; Database, https://doi.org/10.3133/wri034064.","productDescription":"Report: x, 137 p.; Appendix A; Database","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://sc.water.usgs.gov/
The Cenozoic volcanic rocks of Saudi Arabia cover about 90,000 km2, one of the largest areas of alkali olivine basalt in the world. These volcanic rocks are in 13 separate fields near the eastern coast of the Red Sea and in the western Arabian Peninsula highlands from Syria southward to the Yemen Arab Republic.
\nThe initial phase of rifting of the Arabian Plate from the African Plate began as a wide zone of continental-crust extension manifested by basin and range topography. Freshwater lakes, northwest-trending marine gulfs, and alkali olivine basalt flows occupied these basins. Extensive dike swarms intruded parallel to the proto-Red Sea and marked the first phase of new mafic crust formed by volcanic processes. After a hiatus in volcanic activity, counterclockwise rotation of the Arabian Plate during middle Miocene time changed the stress pattern in the plate and a second phase of extrusion of alkali olivine basalt commenced along north-trending fractures. This stress pattern continues to influence Holocene volcanism.
\nThe earliest (pre-uplift) basalts to erupt on the Arabian Plate were predominantly undersaturated picrite and ankaramite, whereas those to erupt near the axis of the proto-Red Sea rift zone were tholeiite. The within-plate volcanic rocks evolved from picrite-ankaramite to alkali olivine basalt with minor volumes of fractionated, undersaturated felsic rocks. Continued crustal thinning and dike intrusion along the proto-Red Sea were accompanied by melting of the continental crust to produce silicic magma as part of a bimodal volcanic suite (tholeiite-rhyolite). These magmas were emplaced as dikes, sills, layered bodies, and flows that mark the early construction of the Red Sea crust. Second-phase lavas are predominantly fractionated hawaiites and alkali olivine basalts. Because undersaturated and oversaturated silicic magmas represent the second phase of activity, both fractional crystallization of the basaltic magma and melting of the crust are believed to have occurred.
\nThe historical record of volcanic activity in Saudi Arabia suggests that volcanism is dormant. The harrats should be evaluated for their potential as volcanic hazards and as sources of geothermal energy. The volcanic rocks are natural traps for groundwater; thus water resources for agriculture may be significant and should be investigated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr83788","usgsCitation":"Coleman, R.G., Gregory, R.T., and Brown, G.F., 2016, Cenozoic volcanic rocks of Saudi Arabia: U.S. Geological Survey Open-File Report 83-788, iii, 86 p., https://doi.org/10.3133/ofr83788.","productDescription":"iii, 86 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":35955,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1983/0788/plate-1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":35956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1983/0788/report.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":141274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1983/0788/report-thumb.jpg"},{"id":324557,"rank":4,"type":{"id":12,"text":"Errata"},"url":"https://pubs.usgs.gov/of/1983/0788/ofr83788_erratum-june282016.txt","text":"Erratum","linkFileType":{"id":2,"text":"txt"}}],"tableOfContents":"This study, covering the Bureau of Land Management (BLM) Central Yukon Planning Area (CYPA), Alaska, was prepared to aid BLM mineral resource management planning. Estimated mineral resource potential and certainty are mapped for six selected mineral deposit groups: (1) rare earth element (REE) deposits associated with peralkaline to carbonatitic intrusive igneous rocks, (2) placer and paleoplacer gold, (3) platinum group element (PGE) deposits associated with mafic and ultramafic intrusive igneous rocks, (4) carbonate-hosted copper deposits, (5) sandstone uranium deposits, and (6) tin-tungsten-molybdenum-fluorspar deposits associated with specialized granites. These six deposit groups include most of the strategic and critical elements of greatest interest in current exploration.
\nThis study has used a data-driven, geographic information system (GIS)-based method for evaluating the mineral resource potential across the large region of the CYPA. This method systematically and simultaneously analyzes geoscience data from multiple geospatially referenced datasets and uses individual subwatersheds (12-digit hydrologic unit codes or HUCs) as the spatial unit of classification. The final map output indicates an estimated potential (high, medium, low) for a given mineral deposit group and indicates the certainty (high, medium, low) of that estimate for any given subwatershed (HUC). Accompanying tables describe the data layers used in each analysis, the values assigned for specific analysis parameters, and the relative weighting of each data layer that contributes to the estimated potential and certainty determinations. Core datasets used include the U.S. Geological Survey (USGS) Alaska Geochemical Database (AGDB2), the Alaska Division of Geologic and Geophysical Surveys Web-based geochemical database, data from an anticipated USGS geologic map of Alaska, and the USGS Alaska Resource Data File. Map plates accompanying this report illustrate the mineral prospectivity for the six deposit groups across the CYPA and estimates of mineral resource potential. There are numerous areas, some of them large, rated with high potential for one or more of the selected deposit groups within the CYPA.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151021","collaboration":"Prepared in cooperation with the Alaska Division of Geological and Geophysical Surveys","usgsCitation":"Jones, J.V., III, Karl, S.M., Labay, K.A., Shew, N.B., Granitto, M., Hayes, T.S., Mauk, J.L., Schmidt, J.M., Todd, E., Wang, B., Werdon, M.B., and Yager, D.B., 2015, GIS-based identification of areas with mineral resource potential for six selected deposit groups, Bureau of Land Management Central Yukon Planning Area, Alaska: U.S. Geological Survey Open-File Report 2015–1021, 78 p., 5 appendixes, 12 pls., https://dx.doi.org/10.3133/ofr20151021.","productDescription":"Report: vii, 78 p.; 12 Plates: 11 inches x 16.3 inches; Metadata; 5 Appendices","numberOfPages":"86","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056688","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":371212,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_appxD.xlsx","text":"Appendix D","size":"17.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":" - Lithology keyword search terms for an anticipated U.S. Geological Survey geologic map of Alaska."},{"id":371213,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_appxE.zip","text":"Appendix E","size":"411 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Scoring results for HUC analysis of selected deposit groups (folder containing Excel spreadsheet and geospatial data files)"},{"id":371214,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021.zip","text":"Complete data package","size":"451 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - A single ZIP file that contains the report, appendixes, metadata and plates."},{"id":371215,"rank":10,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_meta.txt","size":"83.3 KB","linkFileType":{"id":2,"text":"txt"}},{"id":371211,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_appxC.xlsx","text":"Appendix C","size":"38.6 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":" - Alaska Resource Data File (ARDF) mineral deposit keyword and scoring templates."},{"id":371191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1021/coverthb3.jpg"},{"id":371192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021.pdf","text":"Report","size":"2.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1021"},{"id":371210,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_appxB.pdf","text":"Appendix B","size":"138 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":" - Igneous rock geochemistry peer-reviewed literature sources."},{"id":371208,"rank":11,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_metadatafaq.pdf","text":"Metadata FAQ","size":"243 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":371209,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_appxE.zip","text":"Appendix A","size":"28.4 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":" - Stream-sediment geochemistry summary statistics and percentile cutoffs."},{"id":371207,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1021/ofr20151021_plates.pdf","text":"Plates 1-12","size":"39.0 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":" - A single PDF file that contains the 12 plates not included in the report."}],"country":"United States","state":"Alaska","otherGeospatial":"Central Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.05859375,\n 62.431074232920906\n ],\n [\n -165.05859375,\n 71.1877539181316\n ],\n [\n -141.328125,\n 71.1877539181316\n ],\n [\n -141.328125,\n 62.431074232920906\n ],\n [\n -165.05859375,\n 62.431074232920906\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center staff
U.S. Geological Survey
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Anchorage, AK 99508
Alaska Science Center