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\nTo achieve this benefit, the Ministry of Petroleum, Energy, and Mines implemented a second Projet de Renforcement Institutionnel du Secteur Minier (PRISM-II) in 2006 to consolidate, synthesize, and interpret all of the existing data, create a new 1:1,000,000 scale geologic map, and define the mineral resource potential of the country. A consortium in which the USGS was the lead scientific agency carried out the majority of the PRISM-II work. In 2008, the USGS Mauritania Minerals Project was interrupted due to political changes in Mauritania. PRISM-II work resumed in 2011, and was completed in 2013 with the delivery of over 40 separate written reports and plates, an access file containing the Mauritanian National Mineral Deposits Database, and an interactive GIS containing all of the multi-disciplinary data and interpretive areas of mineral resource potential in Mauritania.
\nThis report contains the USGS results of the PRISM-II Mauritania Minerals Project and is presented in cooperation with the Ministry of Petroleum, Energy, and Mines of the Islamic Republic of Mauritania. The Report is composed of separate chapters consisting of multidisciplinary interpretive reports with accompanying plates on the geology, structure, geochronology, geophysics, hydrogeology, geochemistry, remote sensing (Landsat TM and ASTER), and SRTM and ASTER digital elevation models of Mauritania. The syntheses of these multidisciplinary data formed the basis for additional chapters containing interpretive reports on 12 different commodities and deposit types known to occur in Mauritania, accompanied by countrywide mineral resource potential maps of each commodity/deposit type. The commodities and deposit types represented include: (1) Ni, Cu, PGE, and Cr deposits hosted in ultramafic rocks; (2) orogenic, Carlin-like, and epithermal gold deposits; (3) polymetallic Pb-Zn-Cu vein deposits; (4) sediment-hosted Pb-Zn-Ag deposits of the SEDEX and Mississippi Valley-type; (5) sediment-hosted copper deposits; ( 6) volcanogenic massive sulfide deposits; (7) iron oxide copper-gold deposits; (8) uranium deposits; (9) Algoma-, Superior-, and oolitic-type iron deposits; (10) shoreline Ti-Zr placer deposits; (11) incompatible element deposits hosted in pegmatites, alkaline rocks, and carbonatites, and; (12) industrial mineral deposits. Additional chapters include the Mauritanian National Mineral Deposits Database are accompanied by an explanatory text and the Mauritania Minerals Project GIS that contains all of the interpretive layers created by USGS scientists. Raw data not in the public domain may be obtained from the Ministry of Petroleum, Energy, and Mines in Nouakchott, Mauritania.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II) (Open File Report 2013-1280)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131280Q1","collaboration":"Prepared in cooperation with the Ministry of Petroleum, Energy, and Mines of the Islamic Republic of Mauritania","usgsCitation":"Taylor, C.D., and Horton, J.D., 2012, Permissive tracts for incompatible element deposits hosted in pegmatities, alkaline rocks, and carbonatities in Mauritania (phase V, deliverable 86), Chapter Q1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II): U.S. Geological Survey Open-File Report 2013-1280, Plate: 54.0 x 60.0 inches; Data; Metadata, https://doi.org/10.3133/ofr20131280Q1.","productDescription":"Plate: 54.0 x 60.0 inches; Data; Metadata","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056916","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":319135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131280Q1.PNG"},{"id":319134,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1280/GIS_and_Maps/Chapter_Q1_deliverable_86-Incompatible_element_deposits_hosted_in_pegmatities_alkaline%20rocks_and_carbonatities/","text":"Map, Data, and Metadata"},{"id":318737,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/publication/ofr20131280"}],"country":"Mauritania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-12.17075,14.61683],[-12.83066,15.30369],[-13.43574,16.03938],[-14.09952,16.3043],[-14.57735,16.59826],[-15.13574,16.58728],[-15.62367,16.36934],[-16.12069,16.45566],[-16.4631,16.13504],[-16.54971,16.67389],[-16.27055,17.16696],[-16.14635,18.10848],[-16.25688,19.09672],[-16.37765,19.59382],[-16.27784,20.09252],[-16.53632,20.56787],[-17.06342,20.99975],[-16.84519,21.33332],[-12.9291,21.32707],[-13.11875,22.77122],[-12.87422,23.28483],[-11.93722,23.37459],[-11.96942,25.93335],[-8.68729,25.88106],[-8.6844,27.39574],[-4.92334,24.97457],[-6.45379,24.95659],[-5.97113,20.64083],[-5.48852,16.3251],[-5.31528,16.20185],[-5.53774,15.50169],[-9.55024,15.4865],[-9.70026,15.26411],[-10.08685,15.33049],[-10.65079,15.13275],[-11.3491,15.41126],[-11.66608,15.38821],[-11.83421,14.7991],[-12.17075,14.61683]]]},\"properties\":{\"name\":\"Mauritania\"}}]}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f11b65e4b0f59b85ddc4a0","contributors":{"authors":[{"text":"Taylor, Cliff D. 0000-0001-6376-6298 ctaylor@usgs.gov","orcid":"https://orcid.org/0000-0001-6376-6298","contributorId":1283,"corporation":false,"usgs":true,"family":"Taylor","given":"Cliff","email":"ctaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, John D. 0000-0003-2969-9073 jhorton@usgs.gov","orcid":"https://orcid.org/0000-0003-2969-9073","contributorId":1227,"corporation":false,"usgs":true,"family":"Horton","given":"John","email":"jhorton@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622261,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159521,"text":"ofr20131280N1 - 2012 - Permissive tracts for uranium deposits in Mauritania (phase V, deliverable 80): Chapter N1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II)","interactions":[{"subject":{"id":70159521,"text":"ofr20131280N1 - 2012 - Permissive tracts for uranium deposits in Mauritania (phase V, deliverable 80): Chapter N1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II)","indexId":"ofr20131280N1","publicationYear":"2012","noYear":false,"chapter":"N1","title":"Permissive tracts for uranium deposits in Mauritania (phase V, deliverable 80): Chapter N1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II)"},"predicate":"IS_PART_OF","object":{"id":70160523,"text":"ofr20131280 - 2015 - Second Projet de Renforcement Institutionnel du Secteur Minier de la République Islamique de Mauritanie (PRISM-II) Phase V","indexId":"ofr20131280","publicationYear":"2015","noYear":false,"title":"Second Projet de Renforcement Institutionnel du Secteur Minier de la République Islamique de Mauritanie (PRISM-II) Phase V"},"id":1}],"isPartOf":{"id":70160523,"text":"ofr20131280 - 2015 - Second Projet de Renforcement Institutionnel du Secteur Minier de la République Islamique de Mauritanie (PRISM-II) Phase V","indexId":"ofr20131280","publicationYear":"2015","noYear":false,"title":"Second Projet de Renforcement Institutionnel du Secteur Minier de la République Islamique de Mauritanie (PRISM-II) Phase V"},"lastModifiedDate":"2016-03-22T08:55:36","indexId":"ofr20131280N1","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1280","chapter":"N1","title":"Permissive tracts for uranium deposits in Mauritania (phase V, deliverable 80): Chapter N1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II)","docAbstract":"In 1996, at the request of the Government of the Islamic Republic of Mauritania, a team of U.S. Geological Survey (USGS) scientists produced a strategic plan for the acquisition, improvement and modernization of multidisciplinary sets of data to support the growth of the Mauritanian minerals sector and to highlight the geological and mineral exploration potential of the country. In 1999, the Ministry of Petroleum, Energy, and Mines of the Islamic Republic of Mauritania implemented a program for the acquisition of the recommended basic geoscientific information, termed the first Projet de Renforcement Institutionnel du Secteur Minier (Project for Institutional Capacity Building in the Mining Sector, PRISM-I). As a result of the PRISM-I efforts, a great deal of new geological, geophysical, geochemical, remote sensing, and hydrological data became available for evaluation and synthesis. However, the Ministry of Petroleum, Energy, and Mines recognized that additional work was required to extract the full benefit of the data before it could be of greatest use to the international community and of benefit to the Mauritanian minerals and development sector.
\nTo achieve this benefit, the Ministry of Petroleum, Energy, and Mines implemented a second Projet de Renforcement Institutionnel du Secteur Minier (PRISM-II) in 2006 to consolidate, synthesize, and interpret all of the existing data, create a new 1:1,000,000 scale geologic map, and define the mineral resource potential of the country. A consortium in which the USGS was the lead scientific agency carried out the majority of the PRISM-II work. In 2008, the USGS Mauritania Minerals Project was interrupted due to political changes in Mauritania. PRISM-II work resumed in 2011, and was completed in 2013 with the delivery of over 40 separate written reports and plates, an access file containing the Mauritanian National Mineral Deposits Database, and an interactive GIS containing all of the multi-disciplinary data and interpretive areas of mineral resource potential in Mauritania.
\nThis report contains the USGS results of the PRISM-II Mauritania Minerals Project and is presented in cooperation with the Ministry of Petroleum, Energy, and Mines of the Islamic Republic of Mauritania. The Report is composed of separate chapters consisting of multidisciplinary interpretive reports with accompanying plates on the geology, structure, geochronology, geophysics, hydrogeology, geochemistry, remote sensing (Landsat TM and ASTER), and SRTM and ASTER digital elevation models of Mauritania. The syntheses of these multidisciplinary data formed the basis for additional chapters containing interpretive reports on 12 different commodities and deposit types known to occur in Mauritania, accompanied by countrywide mineral resource potential maps of each commodity/deposit type. The commodities and deposit types represented include: (1) Ni, Cu, PGE, and Cr deposits hosted in ultramafic rocks; (2) orogenic, Carlin-like, and epithermal gold deposits; (3) polymetallic Pb-Zn-Cu vein deposits; (4) sediment-hosted Pb-Zn-Ag deposits of the SEDEX and Mississippi Valley-type; (5) sediment-hosted copper deposits; ( 6) volcanogenic massive sulfide deposits; (7) iron oxide copper-gold deposits; (8) uranium deposits; (9) Algoma-, Superior-, and oolitic-type iron deposits; (10) shoreline Ti-Zr placer deposits; (11) incompatible element deposits hosted in pegmatites, alkaline rocks, and carbonatites, and; (12) industrial mineral deposits. Additional chapters include the Mauritanian National Mineral Deposits Database are accompanied by an explanatory text and the Mauritania Minerals Project GIS that contains all of the interpretive layers created by USGS scientists. Raw data not in the public domain may be obtained from the Ministry of Petroleum, Energy, and Mines in Nouakchott, Mauritania.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II) (Open File Report 2013-1280)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131280N1","collaboration":"Prepared in cooperation with the Ministry of Petroleum, Energy, and Mines of the Islamic Republic of Mauritania","usgsCitation":"Fernette, G., and Horton, J.D., 2012, Permissive tracts for uranium deposits in Mauritania (phase V, deliverable 80): Chapter N1 in Second projet de renforcement institutionnel du secteur minier de la République Islamique de Mauritanie (PRISM-II): U.S. Geological Survey Open-File Report 2013-1280, Plate: 54.0 x 60.0 inches; Data; Metadata, https://doi.org/10.3133/ofr20131280N1.","productDescription":"Plate: 54.0 x 60.0 inches; Data; Metadata","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056908","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":319068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131280N1.PNG"},{"id":318742,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/publication/ofr20131280"},{"id":319067,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1280/GIS_and_Maps/Chapter_N1_deliverable_80-Uranium_deposits/","text":"Map, Data, and Metadata"}],"country":"Mauritania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-12.17075,14.61683],[-12.83066,15.30369],[-13.43574,16.03938],[-14.09952,16.3043],[-14.57735,16.59826],[-15.13574,16.58728],[-15.62367,16.36934],[-16.12069,16.45566],[-16.4631,16.13504],[-16.54971,16.67389],[-16.27055,17.16696],[-16.14635,18.10848],[-16.25688,19.09672],[-16.37765,19.59382],[-16.27784,20.09252],[-16.53632,20.56787],[-17.06342,20.99975],[-16.84519,21.33332],[-12.9291,21.32707],[-13.11875,22.77122],[-12.87422,23.28483],[-11.93722,23.37459],[-11.96942,25.93335],[-8.68729,25.88106],[-8.6844,27.39574],[-4.92334,24.97457],[-6.45379,24.95659],[-5.97113,20.64083],[-5.48852,16.3251],[-5.31528,16.20185],[-5.53774,15.50169],[-9.55024,15.4865],[-9.70026,15.26411],[-10.08685,15.33049],[-10.65079,15.13275],[-11.3491,15.41126],[-11.66608,15.38821],[-11.83421,14.7991],[-12.17075,14.61683]]]},\"properties\":{\"name\":\"Mauritania\"}}]}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f11b66e4b0f59b85ddc4c4","contributors":{"authors":[{"text":"Fernette, Gregory gfernette@usgs.gov","contributorId":149751,"corporation":false,"usgs":true,"family":"Fernette","given":"Gregory","email":"gfernette@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, John D. 0000-0003-2969-9073 jhorton@usgs.gov","orcid":"https://orcid.org/0000-0003-2969-9073","contributorId":1227,"corporation":false,"usgs":true,"family":"Horton","given":"John","email":"jhorton@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622278,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042632,"text":"70042632 - 2012 - Near-bed turbulence and sediment flux measurements in tidal channels","interactions":[],"lastModifiedDate":"2016-06-29T10:49:34","indexId":"70042632","displayToPublicDate":"2014-09-16T13:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Near-bed turbulence and sediment flux measurements in tidal channels","docAbstract":"Understanding the hydrodynamics and sediment transport dynamics in tidal channels is important for studies of estuary geomorphology, sediment supply to tidal wetlands, aquatic ecology and fish habitat, and dredging and navigation. Hydrodynamic and sediment transport data are essential for calibration and testing of numerical models that may be used to address management questions related to these topics. Herein we report preliminary analyses of near-bed turbulence and sediment flux measurements in the Sacramento-San Joaquin Delta, a large network of tidal channels and wetlands located at the confluence of the Sacramento and San Joaquin Rivers, California, USA (Figure 1). Measurements were made in 6 channels spanning a wide range of size and tidal conditions, from small channels that are primarily fluvial to large channels that are tidally dominated. The results of these measurements are summarized herein and the hydrodynamic and sediment transport characteristics of the channels are compared across this range of size and conditions.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the Hydraulic Measurement and Experimental Methods Conference, Snowbird, Utah, August 12-15, 2012","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"Hydraulic Measurement and Experimental Methods Conference","conferenceDate":"August 12, 2012","conferenceLocation":"Snowbird, Utah","language":"English","publisherLocation":"Reston, VA","usgsCitation":"Wright, S., and Whealdon-Haught, D., 2012, Near-bed turbulence and sediment flux measurements in tidal channels, in Proceedings of the Hydraulic Measurement and Experimental Methods Conference, Snowbird, Utah, August 12-15, 2012, Snowbird, Utah, August 12, 2012, 6 p.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038033","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324597,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ca.water.usgs.gov/projects/baydelta/publications.html"},{"id":324598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.86035156249999,\n 38.098901948321256\n ],\n [\n -121.85760498046875,\n 38.01239425385966\n ],\n [\n -121.55273437499999,\n 37.95827503526034\n ],\n [\n -121.46347045898438,\n 37.966936792535144\n ],\n [\n -121.47720336914062,\n 38.25974980039479\n ],\n [\n -121.8878173828125,\n 38.23386541556983\n ],\n [\n -121.86035156249999,\n 38.098901948321256\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774f2a1e4b07dd077c6a780","contributors":{"authors":[{"text":"Wright, S.A.","contributorId":90080,"corporation":false,"usgs":true,"family":"Wright","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":640594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whealdon-Haught, D.R.","contributorId":172409,"corporation":false,"usgs":false,"family":"Whealdon-Haught","given":"D.R.","affiliations":[],"preferred":false,"id":640595,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70073502,"text":"70073502 - 2012 - Testing the effect of water in crevasses on a physically based calving model","interactions":[],"lastModifiedDate":"2018-07-07T18:08:12","indexId":"70073502","displayToPublicDate":"2014-01-01T09:20:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":794,"text":"Annals of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Testing the effect of water in crevasses on a physically based calving model","docAbstract":"A new implementation of a calving model, using the finite-element code Elmer, is presented and used to investigate the effects of surface water within crevasses on calving rate. For this work, we use a two-dimensional flowline model of Columbia Glacier, Alaska. Using the glacier's 1993 geometry as a starting point, we apply a crevasse-depth calving criterion, which predicts calving at the location where surface crevasses cross the waterline. Crevasse depth is calculated using the Nye formulation. We find that calving rate in such a regime is highly dependent on the depth of water in surface crevasses, with a change of just a few meters in water depth causing the glacier to change from advancing at a rate of 3.5 km a-1 to retreating at a rate of 1.9 km a-1. These results highlight the potential for atmospheric warming and surface meltwater to trigger glacier retreat, but also the difficulty of modeling calving rates, as crevasse water depth is difficult to determine either by measurement in situ or surface mass-balance modelling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Annals of Glaciology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"International Glaciological Society","doi":"10.3189/2012AoG60A107","usgsCitation":"Cook, S., Zwinger, T., Rutt, I., O’Neel, S., and Murray, T., 2012, Testing the effect of water in crevasses on a physically based calving model: Annals of Glaciology, v. 53, no. 60, p. 90-96, https://doi.org/10.3189/2012AoG60A107.","productDescription":"7 p.","startPage":"90","endPage":"96","ipdsId":"IP-033017","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3189/2012aog60a107","text":"Publisher Index Page"},{"id":281498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281496,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3189/2012AoG60A107"}],"country":"United States","state":"Alaska","otherGeospatial":"Columbia Glacier","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -147.30,60.30 ], [ -147.30,61.30 ], [ -146.30,61.30 ], [ -146.30,60.30 ], [ -147.30,60.30 ] ] ] } } ] }","volume":"53","issue":"60","noUsgsAuthors":false,"publicationDate":"2017-09-14","publicationStatus":"PW","scienceBaseUri":"53cd76a3e4b0b2908510b090","contributors":{"authors":[{"text":"Cook, S.","contributorId":26225,"corporation":false,"usgs":true,"family":"Cook","given":"S.","affiliations":[],"preferred":false,"id":488836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwinger, T.","contributorId":82612,"corporation":false,"usgs":true,"family":"Zwinger","given":"T.","email":"","affiliations":[],"preferred":false,"id":488839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rutt, I.C.","contributorId":82613,"corporation":false,"usgs":true,"family":"Rutt","given":"I.C.","email":"","affiliations":[],"preferred":false,"id":488840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":488837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, T.","contributorId":59304,"corporation":false,"usgs":true,"family":"Murray","given":"T.","email":"","affiliations":[],"preferred":false,"id":488838,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205864,"text":"70205864 - 2012 - Physical Climate Forces","interactions":[{"subject":{"id":70205864,"text":"70205864 - 2012 - Physical Climate Forces","indexId":"70205864","publicationYear":"2012","noYear":false,"chapter":"2","title":"Physical Climate Forces"},"predicate":"IS_PART_OF","object":{"id":70048737,"text":"70048737 - 2012 - Coastal impacts, adaptation, and vulnerabilities: a technical input to the 2013 National Climate Assessment","indexId":"70048737","publicationYear":"2012","noYear":false,"title":"Coastal impacts, adaptation, and vulnerabilities: a technical input to the 2013 National Climate Assessment"},"id":1}],"isPartOf":{"id":70048737,"text":"70048737 - 2012 - Coastal impacts, adaptation, and vulnerabilities: a technical input to the 2013 National Climate Assessment","indexId":"70048737","publicationYear":"2012","noYear":false,"title":"Coastal impacts, adaptation, and vulnerabilities: a technical input to the 2013 National Climate Assessment"},"lastModifiedDate":"2019-10-08T16:24:10","indexId":"70205864","displayToPublicDate":"2013-10-08T16:02:11","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"2","title":"Physical Climate Forces","docAbstract":"Key Findings
The coasts of the U.S. are home to many large urban centers and important infrastructure such seaports, airports, transportation routes, oil import and refining facilities, power plants, and military bases. All are vulnerable to varying degrees to impacts of global warming such as sea-level rise, storms, and flooding. High Confidence.
Physical observations collected over the past several decades from the land, coasts, oceans, and the atmosphere, as well as environmental indicators, show that warming and some related environmental changes are occurring globally at rates greater than can be expected due to natural processes. These climate-related changes are highly varied, but some are likely due in large part to anthropogenically increased atmospheric concentrations of greenhouse gases and altered land surface properties. High Confidence.
Findings from many independent scientific studies conclude that these changes are consistent with global warming. The primary changes observed are rising sea level and average global air, land, and ocean temperatures; heightening temperature and precipitation extremes in some regions; and increasing levels of oceans acidification and rates of glacier and ice sheet melt. High Confidence.
Most coastal landforms, such as barrier islands, deltas, bays, estuaries, wetlands, coral reefs, are highly dynamic and sensitive to even small changes in physical
forces and feedbacks such as warming, storms, ocean circulation, waves and currents, flooding, sediment budgets, and sea-level rise. High Confidence.
The effects of sea-level rise on coasts vary considerably from region-to-region and over a range of spatial and temporal scales. Land subsidence in certain locations causes relative sea-level rise to exceed global mean sea-level rise. Land uplift such as that found in Alaska and the Northwestern Pacific coast can reduce effects of global mean rise. The effects will be greatest and most immediate on low-relief, low-elevation parts of the U.S. coast along the Gulf of Mexico, mid-Atlantic states, northern Alaska, Hawaii, and island territories and especially on coasts containing deltas, coastal plains, tidal wetlands, bays, estuaries, and coral reefs. Beaches and wetlands on steep cliff coasts and shores backed with seawalls may be unable to move landward or maintain their landform with sea-level rise. Many areas of the coast are especially vulnerable because of the often detrimental effects of development on natural processes. High Confidence.
The gradual inundation from recent sea-level rise is evident in many regions such as the mid-Atlantic and Louisiana where high tides regularly flood roads and areas that were previously dry, and in stands of “ghost forests,” in which trees are killed by intrusion of brackish water. High Confidence.
Sea level change and storms are dominant driving forces of coastal change as observed in the geologic record of coastal landforms. Increasingly, sea-level rise will become a hazard for coastal regions because of continued global mean sea-level rise, including possibly accelerated rates of rise that increase risk to coastal regions. As the global climate continues to warm and ice sheets melt, coasts will become more dynamic and coastal cities and low-lying areas will be increasingly exposed to erosion, inundation, and flooding. High Confidence.
No coordinated, interagency process exists in the U.S. for identifying agreed upon global mean sea-level rise projections for the purpose of coastal planning, policy, or management, even though this is a critical first step in assessing coastal impacts and vulnerabilities. High Confidence.
Global sea level rose at a rate of 1.7 millimeters/year during the 20th century. The rate has increased to over 3 millimeters/year in the past 20 years and scientific studies suggest high confidence (>9 in 10 chance) that global mean sea level will rise 0.2 to 2 meters by the end of this century. Some regions such as Louisiana and the Chesapeake Bay will experience greater relative rise due to factors such as land subsidence, gravitational redistribution of ice-sheet meltwater, ocean circulation changes, and regional ocean thermostatic effects. Other regions undergoing land uplift, such as Alaska, will experience lesser sea-level rise. High Confidence.
Variability in the location and time-of-year of storm genesis can influence landfalling storm characteristics, and even small changes can lead to large changes in landfalling location and impact. Although scientists have only low confidence in the sign of projected changes to the coast of storm-related hazards that depend on a combination of factors such as frequency, track, intensity, and storm size, any sea-level rise is virtually certain to exacerbate storm-related hazards. High Confidence.
Although sea-level rise and climate change have occurred in the past, the increasing human presence in the coastal zone will make the impacts different
for the future. Land use and other human activities often inhibit the natural response of physical processes and adaptation by plants and animals. In some
areas, erosion and wetland loss are common because sediment budgets have been reduced, while, in other regions, excess sediment is in-filling harbors, channels, and bays. High Confidence.
Observations continue to indicate an ongoing, warming-induced intensification of the hydrologic cycle that will likely result in heavier precipitation events and, combined with sea-level rise and storm surge, an increased flooding severity in some coastal areas, particularly the northeast U.S. Moderate Confidence.
Temperature is primarily driving environmental change in the Alaskan coastal zone. Sea ice and permafrost make northern regions particularly susceptible to temperature change. For example, an increase of two degrees Celsius could basically transform much of Alaska from frozen to unfrozen, with extensive implications. Portions of the north and west coast of Alaska are seeing dramatic increases in the rate of coastal erosion and flooding due to sea ice loss and permafrost melting. As a consequence, several coastal communities are planning to relocate to safer locations. Relocation is a difficult decision that is likely to become more common in the future for many coastal regions. High Confidence.
Methane is a primary greenhouse gas. Large reserves of methane are bound-up in Alaska’s frozen permafrost. These are susceptible to disturbance and methane
release if the Arctic continues to warm. The additional methane released may result in even greater greenhouse warming of the atmosphere. High Confidence.
Volcanogenic massive sulfide (VMS) Zn-Pb-Cu-Ag-Au deposits of the Bonnifield mining district formed during Late Devonian-Early Mississippian magmatism along the western edge of Laurentia. The largest deposits, Dry Creek and WTF, have a combined resource of 5.7 million tonnes at 10% Zn, 4% Pb, 0.3% Cu, 300 grams per tonne (g/t) Ag, and 1.6 g/t Au. These polymetallic deposits are hosted in high field strength element (HFSE)- and rare-earth element (REE)-rich peralkaline (pantelleritic) metarhyolite, and interlayered pyritic argillite and mudstone of the Mystic Creek Member of the Totatlanika Schist Formation. Mystic Creek metarhyolite and alkali basalt (Chute Creek Member) constitute a bimodal pair that formed in an extensional environment. A synvolcanic peralkaline quartz porphyry containing veins of fluorite, sphalerite, pyrite, and quartz intrudes the central footwall at Dry Creek. The Anderson Mountain deposit, located ~32 km to the southwest, occurs within calc-alkaline felsic to intermediate-composition metavolcanic rocks and associated graphitic argillite of the Wood River assemblage. Felsic metavolcanic rocks there have only slightly elevated HFSEs and REEs. The association of abundant graphitic and siliceous argillite with the felsic volcanic rocks together with low Cu contents in the Bonnifield deposits suggests classification as a siliciclastic-felsic type of VMS deposit.
Bonnifield massive sulfides and host rocks were metamorphosed and deformed under greenschist-facies conditions in the Mesozoic. Primary depositional textures, generally uncommon, consist of framboids, framboidal aggregates, and spongy masses of pyrite. Sphalerite, the predominant base metal sulfide, encloses early pyrite framboids. Galena and chalcopyrite accompanied early pyrite formation but primarily formed late in the paragenetic sequence. Silver-rich tetrahedrite is a minor late phase at the Dry Creek deposit. Gold and Ag are present in low to moderate amounts in pyrite from all of the deposits; electrum inclusions occur in Dry Creek sphalerite. Contents and ratios of trace elements in graphitic argillite that serve as proxies for the redox state of the bottom waters in the basin indicate that Dry Creek mineralization took place in suboxic to periodically anoxic bottom waters. Trace element data show higher contents of Tl-Mn-As in pyrite from the Anderson Mountain deposit compared to the Dry Creek or WTF deposits and thus suggest that Anderson Mountain may have formed at lower temperatures or under slightly more oxidizing conditions.
No exact modern analogue for the tectonic setting of the Bonnifield VMS deposits is known, although the back-arc regions of the Okinawa Trough and Woodlark Basin satisfy the requirement for a submarine, extensional setting adjacent to a continental margin. Limited occurrences of peralkaline volcanic rocks occur in these two potential analogues, but the peralkalinity of those rocks is much less than that of the Mystic Creek Member metarhyolites in the Bonnifield district. The highly elevated trace element (e.g., Zr, Nb) contents of Mystic Creek metarhyolites suggest that a better analogue may be a submarine rifted continental margin. The calc-alkaline composition of the host rocks to the Anderson Mountain deposit suggests that mineralization there formed in a continental margin arc, outboard of the extended continental margin setting of the peralkaline-hosted Dry Creek and WTF deposits.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.107.7.1403","usgsCitation":"Dusel-Bacon, C., Foley, N.K., Slack, J.E., Koenig, A.E., and Oscarson, R.L., 2012, Peralkaline- and calc-alkaline-hosted volcanogenic massive sulfide deposits of the Bonnifield District, East-Central Alaska: Economic Geology, v. 107, no. 7, p. 1403-1432, https://doi.org/10.2113/econgeo.107.7.1403.","productDescription":"30 p.","startPage":"1403","endPage":"1432","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":291192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291191,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/econgeo.107.7.1403"}],"country":"United States","state":"Alaska","otherGeospatial":"Bonnifield District","volume":"107","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-10-12","publicationStatus":"PW","scienceBaseUri":"57f7f3c1e4b0bc0bec0a0b77","contributors":{"authors":[{"text":"Dusel-Bacon, Cynthia 0000-0001-8481-739X cdusel@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-739X","contributorId":2797,"corporation":false,"usgs":true,"family":"Dusel-Bacon","given":"Cynthia","email":"cdusel@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":496798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":496800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slack, John E.","contributorId":65774,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":496801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koenig, Alan E. 0000-0002-5230-0924 akoenig@usgs.gov","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":1564,"corporation":false,"usgs":true,"family":"Koenig","given":"Alan","email":"akoenig@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":496797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oscarson, Robert L. roscarson@usgs.gov","contributorId":3390,"corporation":false,"usgs":true,"family":"Oscarson","given":"Robert","email":"roscarson@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":496799,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118335,"text":"70118335 - 2012 - Distribution of arsenic, selenium, and other trace elements in high pyrite Appalachian coals: evidence for multiple episodes of pyrite formation","interactions":[],"lastModifiedDate":"2014-07-28T14:13:12","indexId":"70118335","displayToPublicDate":"2013-07-28T14:04:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of arsenic, selenium, and other trace elements in high pyrite Appalachian coals: evidence for multiple episodes of pyrite formation","docAbstract":"Pennsylvanian coals in the Appalachian Basin host pyrite that is locally enriched in potentially toxic trace elements such as As, Se, Hg, Pb, and Ni. A comparison of pyrite-rich coals from northwestern Alabama, eastern Kentucky, and West Virginia reveals differences in concentrations and mode of occurrence of trace elements in pyrite. Pyrite occurs as framboids, dendrites, or in massive crystalline form in cell lumens or crosscutting veins. Metal concentrations in pyrite vary over all scales, from microscopic to mine to regional, because trace elements are inhomogeneously distributed in the different morphological forms of pyrite, and in the multiple generations of sulfide mineral precipitates.
\nEarly diagenetic framboidal pyrite is usually depleted in As, Se, and Hg, and enriched in Pb and Ni, compared to other pyrite forms. In dendritic pyrite, maps of As distribution show a chemical gradient from As-rich centers to As-poor distal branches, whereas Se concentrations are highest at the distal edges of the branches. Massive crystalline pyrite that fills veins is composed of several generations of sulfide minerals. Pyrite in late-stage veins commonly exhibits As-rich growth zones, indicating a probable epigenetic hydrothermal origin. Selenium is concentrated at the distal edges of veins. A positive correlation of As and Se in pyrite veins from Kentucky coals, and of As and Hg in pyrite-filled veins from Alabama coals, suggests coprecipitation of these elements from the same fluid.
\nIn the Kentucky coal samples (n = 18), As and Se contents in pyrite-filled veins average 4200 ppm and 200 ppm, respectively. In Alabama coal samples, As in pyrite-filled veins averages 2700 ppm (n = 34), whereas As in pyrite-filled cellular structures averages 6470 ppm (n = 35). In these same Alabama samples, Se averages 80 ppm in pyrite-filled veins, but was below the detection limit in cell structures. In samples of West Virginia massive pyrite, As averages 1700 ppm, and Se averages 270 ppm (n = 24). The highest concentration of Hg (≤ 102 ppm) is in Alabama pyrite veins.
\nImproved detailed descriptions of sulfide morphology, sulfide mineral paragenesis, and trace-element concentration and distribution allow more informed predictions of: (1) the relative rate of release of trace elements during weathering of pyrite in coals, and (2) the relative effectiveness of various coal-cleaning procedures of removing pyrite. For example, trace element-rich pyrite has been shown to be more soluble than stoichiometric pyrite, and fragile fine-grained pyrite forms such as dendrites and framboids are more susceptible to dissolution and disaggregation but less amenable to removal during coal cleaning.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Coal Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2012.01.015","usgsCitation":"Diehl, S.F., Goldhaber, M., Koenig, A., Lowers, H., and Ruppert, L., 2012, Distribution of arsenic, selenium, and other trace elements in high pyrite Appalachian coals: evidence for multiple episodes of pyrite formation: International Journal of Coal Geology, v. 94, p. 238-249, https://doi.org/10.1016/j.coal.2012.01.015.","productDescription":"12 p.","startPage":"238","endPage":"249","costCenters":[],"links":[{"id":291189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291188,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2012.01.015"}],"country":"United States","state":"Alabama;Kentucky;West Virginia","otherGeospatial":"Appalachian Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,33.21 ], [ -88.25,39.43 ], [ -79.66,39.43 ], [ -79.66,33.21 ], [ -88.25,33.21 ] ] ] } } ] }","volume":"94","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f3c1e4b0bc0bec0a0b79","contributors":{"authors":[{"text":"Diehl, S. F.","contributorId":84780,"corporation":false,"usgs":true,"family":"Diehl","given":"S.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":496788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldhaber, M. B. 0000-0002-1785-4243","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":103280,"corporation":false,"usgs":true,"family":"Goldhaber","given":"M. B.","affiliations":[],"preferred":false,"id":496789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koenig, A.E. 0000-0002-5230-0924","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":23679,"corporation":false,"usgs":true,"family":"Koenig","given":"A.E.","affiliations":[],"preferred":false,"id":496785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowers, H.A. 0000-0001-5360-9264","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":31843,"corporation":false,"usgs":true,"family":"Lowers","given":"H.A.","affiliations":[],"preferred":false,"id":496786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ruppert, L.F. 0000-0003-4990-0539","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":59043,"corporation":false,"usgs":true,"family":"Ruppert","given":"L.F.","affiliations":[],"preferred":false,"id":496787,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118264,"text":"70118264 - 2012 - The first direct evidence of pre-columbian sources of palygorskite for Maya Blue","interactions":[],"lastModifiedDate":"2014-07-28T10:36:52","indexId":"70118264","displayToPublicDate":"2013-07-28T10:34:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2182,"text":"Journal of Archaeological Science","active":true,"publicationSubtype":{"id":10}},"title":"The first direct evidence of pre-columbian sources of palygorskite for Maya Blue","docAbstract":"Maya Blue, a nano-structured clay–organic complex of palygorskite and indigo, was used predominantly before the Spanish Conquest. It has fascinated chemists, material scientists, archaeologists and art historians for decades because it is resistant to the effect of acids, alkalis, and other reagents, and its rich color has persisted for centuries in the harsh tropical climate of southern Mesoamerica. One of its components, palygorskite, is part of modern Maya indigenous knowledge, and ethnohistoric and archaeological data suggest that its modern sources were probably utilized in Prehispanic times. Yet no direct evidence verifies that palygorskite was actually mined from these sources to make Maya Blue. Here we characterize these sources compositionally, and compare our analyses to those of Maya Blue from Chichén Itzá and Palenque. We demonstrate that the palygorskite in most of these samples came from modern mines, providing the first direct evidence for the use of these sources for making Maya Blue. These findings reveal that modern Maya indigenous knowledge about palygorskite, its mining, and its source locations, is at least seven centuries old.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Archaeological Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jas.2012.02.036","usgsCitation":"Arnold, D., Bohor, B., Neff, H., Feinman, G.M., Williams, P.R., Dussubieux, L., and Bishop, R., 2012, The first direct evidence of pre-columbian sources of palygorskite for Maya Blue: Journal of Archaeological Science, v. 39, no. 7, p. 2252-2260, https://doi.org/10.1016/j.jas.2012.02.036.","productDescription":"9 p.","startPage":"2252","endPage":"2260","costCenters":[],"links":[{"id":291121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291120,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jas.2012.02.036"}],"volume":"39","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f3c1e4b0bc0bec0a0b89","contributors":{"authors":[{"text":"Arnold, Dean E.","contributorId":73117,"corporation":false,"usgs":true,"family":"Arnold","given":"Dean E.","affiliations":[],"preferred":false,"id":496641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohor, Bruce F.","contributorId":104823,"corporation":false,"usgs":true,"family":"Bohor","given":"Bruce F.","affiliations":[],"preferred":false,"id":496643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neff, Hector","contributorId":102400,"corporation":false,"usgs":true,"family":"Neff","given":"Hector","email":"","affiliations":[],"preferred":false,"id":496642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinman, Gary M.","contributorId":11959,"corporation":false,"usgs":true,"family":"Feinman","given":"Gary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":496637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Patrick Ryan","contributorId":14746,"corporation":false,"usgs":true,"family":"Williams","given":"Patrick","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":496638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dussubieux, Laure","contributorId":58577,"corporation":false,"usgs":true,"family":"Dussubieux","given":"Laure","email":"","affiliations":[],"preferred":false,"id":496639,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bishop, Ronald","contributorId":67809,"corporation":false,"usgs":true,"family":"Bishop","given":"Ronald","email":"","affiliations":[],"preferred":false,"id":496640,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70118138,"text":"70118138 - 2012 - Structure and mechanism of diet specialisation: testing models of individual variation in resource use with sea otters","interactions":[],"lastModifiedDate":"2015-04-09T15:58:00","indexId":"70118138","displayToPublicDate":"2013-07-25T16:21:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Structure and mechanism of diet specialisation: testing models of individual variation in resource use with sea otters","docAbstract":"Studies of consumer-resource interactions suggest that individual diet specialisation is empirically widespread and theoretically important to the organisation and dynamics of populations and communities. We used weighted networks to analyze the resource use by sea otters, testing three alternative models for how individual diet specialisation may arise. As expected, individual specialisation was absent when otter density was low, but increased at high-otter density. A high-density emergence of nested resource-use networks was consistent with the model assuming individuals share preference ranks. However, a density-dependent emergence of a non-nested modular network for ‘core’ resources was more consistent with the ‘competitive refuge’ model. Individuals from different diet modules showed predictable variation in rank-order prey preferences and handling times of core resources, further supporting the competitive refuge model. Our findings support a hierarchical organisation of diet specialisation and suggest individual use of core and marginal resources may be driven by different selective pressures.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1461-0248.2012.01760.x","usgsCitation":"Tinker, M., Guimaraes, P.R., Novak, M., Marquitti, F.M., Bodkin, J.L., Staedler, M., Bentall, G.B., and Estes, J.A., 2012, Structure and mechanism of diet specialisation: testing models of individual variation in resource use with sea otters: Ecology Letters, v. 15, no. 5, p. 475-483, https://doi.org/10.1111/j.1461-0248.2012.01760.x.","productDescription":"9 p.","startPage":"475","endPage":"483","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":291067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291066,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1461-0248.2012.01760.x"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9482421875,\n 36.482036438803604\n ],\n [\n -121.92626953124999,\n 36.54494944148322\n ],\n [\n -121.95098876953125,\n 36.56811502180857\n ],\n [\n -121.981201171875,\n 36.57473248336113\n ],\n [\n -121.94274902343749,\n 36.63867203824882\n ],\n [\n -121.92764282226564,\n 36.641977814705946\n ],\n [\n -121.87820434570311,\n 36.60229913579042\n ],\n [\n -121.84661865234374,\n 36.63757008123925\n ],\n [\n -121.81228637695312,\n 36.71136634281923\n ],\n [\n -121.86584472656251,\n 36.756490329505155\n ],\n [\n -121.94412231445314,\n 36.7586908210984\n ],\n [\n -121.99493408203125,\n 36.6959520787169\n ],\n [\n -122.02926635742188,\n 36.58686302344181\n ],\n [\n -122.01553344726561,\n 36.49970139181239\n ],\n [\n -122.00454711914061,\n 36.45111307831851\n ],\n [\n -121.98394775390625,\n 36.423492513472326\n ],\n [\n -121.96060180664062,\n 36.405810193726765\n ],\n [\n -121.9317626953125,\n 36.416862115300304\n ],\n [\n -121.915283203125,\n 36.43896124085945\n ],\n [\n -121.9482421875,\n 36.482036438803604\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.35086059570314,\n 35.631628173298424\n ],\n [\n -121.27670288085938,\n 35.68407153314097\n ],\n [\n -121.18606567382812,\n 35.65841206428204\n ],\n [\n -121.09405517578125,\n 35.56686337967425\n ],\n [\n -121.04324340820312,\n 35.51098961071258\n ],\n [\n -120.95535278320311,\n 35.461788508399174\n ],\n [\n -120.9320068359375,\n 35.44165210456756\n ],\n [\n -120.99380493164062,\n 35.4159149234562\n ],\n [\n -121.18606567382812,\n 35.553457224935244\n ],\n [\n -121.35086059570314,\n 35.631628173298424\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.608154296875,\n 33.31790588151775\n ],\n [\n -119.47357177734375,\n 33.333970395573864\n ],\n [\n -119.38980102539062,\n 33.26624989076273\n ],\n [\n -119.39666748046874,\n 33.19732768648872\n ],\n [\n -119.50103759765625,\n 33.169743600216165\n ],\n [\n -119.59991455078124,\n 33.206520451760596\n ],\n [\n -119.63562011718751,\n 33.265101632548216\n ],\n [\n -119.608154296875,\n 33.31790588151775\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-03-14","publicationStatus":"PW","scienceBaseUri":"5527a2b8e4b026915857c85d","contributors":{"authors":[{"text":"Tinker, M. 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Ambient vibration data recorded are analyzed to identify modes and associated frequencies and damping. The low-amplitude dynamic characteristics are considerably different than those computed from design analyses, but serve as a baseline against which to compare with future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the added features to the building and help improve designs in the future.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SMIP12 seminar on utilization of strong-motion data","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SMIP12 Seminar on Utilization of Strong-Motion Data","conferenceDate":"October 2, 2012","conferenceLocation":"Sacramento, California, United States","language":"English","publisher":"Wiley","usgsCitation":"Çelebi, M., Huang, M., Shakal, A., Hooper, J., and Klemencic, R., 2012, Ambient response of a unique performance-based design building with dynamic response modification features, in Proceedings of SMIP12 seminar on utilization of strong-motion data, Sacramento, California, United States, October 2, 2012, p. 97-110.","productDescription":"14 p.","startPage":"97","endPage":"110","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041033","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":307388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.39573130364712,\n 37.78639392372942\n ],\n [\n -122.3940046115253,\n 37.785126778990545\n ],\n [\n -122.39441161752544,\n 37.78493183171767\n ],\n [\n -122.3928699281308,\n 37.78370407492284\n ],\n [\n -122.39154221813193,\n 37.784678399494354\n ],\n [\n -122.39086387479841,\n 37.785380209676305\n ],\n [\n -122.38974152491902,\n 37.78622822142104\n ],\n [\n -122.38874251019155,\n 37.78695925821883\n ],\n [\n -122.38845883934303,\n 37.78709571762036\n ],\n [\n -122.38801483279752,\n 37.78709571762036\n ],\n [\n -122.38799016576692,\n 37.78780725184491\n ],\n [\n -122.39095020940425,\n 37.79009776069822\n ],\n [\n -122.39573130364712,\n 37.78639392372942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f3c2e4b0bc0bec0a0b9b","contributors":{"authors":[{"text":"Çelebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":3205,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":569689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Moh","contributorId":146970,"corporation":false,"usgs":false,"family":"Huang","given":"Moh","email":"","affiliations":[],"preferred":false,"id":569690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shakal, Antony","contributorId":146971,"corporation":false,"usgs":false,"family":"Shakal","given":"Antony","email":"","affiliations":[],"preferred":false,"id":569691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hooper, John","contributorId":146972,"corporation":false,"usgs":false,"family":"Hooper","given":"John","affiliations":[],"preferred":false,"id":569692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klemencic, Ron","contributorId":146973,"corporation":false,"usgs":false,"family":"Klemencic","given":"Ron","email":"","affiliations":[],"preferred":false,"id":569693,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045501,"text":"70045501 - 2012 - Strategies for soil quality assessment using VNIR gyperspectral spectroscopy in a western Kenya Chronosequence","interactions":[],"lastModifiedDate":"2013-05-07T14:17:23","indexId":"70045501","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Strategies for soil quality assessment using VNIR gyperspectral spectroscopy in a western Kenya Chronosequence","docAbstract":"Visible and near-infrared reflectance spectroscopy (VNIRS) is a rapid and nondestructive method that can predict multiple soil properties simultaneously, but its application in multidimensional soil quality (SQ) assessment in the tropics still needs to be further assessed. In this study, VNIRS (350–2500 nm) was employed to analyze 227 air-dried soil samples of Ultisols from a soil chronosequence in western Kenya and assess 16 SQ indicators. Partial least squares regression (PLSR) was validated using the full-site cross-validation method by grouping samples from each farm or forest site. Most suitable models successfully predicted SQ indicators (R2 ≥ 0.80; ratio of performance to deviation [RPD] ≥ 2.00) including soil organic matter (OMLOI), active C, Ca, cation exchange capacity (CEC), and clay. Moderately-well predicted indicators (0.50 ≤ R2 < 0.80; 1.40 ≤ RPD < 2.00) were water stable aggregation (WSA), Cu, silt, Mg, pH, sand, water content at permanent wilting point (Θpwp), and field capacity (Θfc). Poorly predicted indicators (R2 < 0.50; RPD < 1.40) were EC, S, P, available water capacity (AWC), K, Zn, and penetration resistance. Combining VNIRS with selected field- and laboratory-measured SQ indicator values increased predictability. Furthermore, VNIRS showed moderate to substantial agreement in predicting interpretive SQ scores and a composite soil quality index (CSQI) especially when combined with directly measured SQ indicator values. In conclusion, VNIRS has good potential for low cost, rapid assessment of physical and biological SQ indicators but conventional soil chemical tests may need to be retained to provide comprehensive SQ assessments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2011.0307","usgsCitation":"Kinoshita, R., Moebius-Clune, B.N., van Es, H.M., Hively, W., and Bilgilis, A.V., 2012, Strategies for soil quality assessment using VNIR gyperspectral spectroscopy in a western Kenya Chronosequence: Soil Science Society of America Journal, v. 76, no. 5, p. 1776-1788, https://doi.org/10.2136/sssaj2011.0307.","productDescription":"13 p.","startPage":"1776","endPage":"1788","numberOfPages":"13","ipdsId":"IP-033379","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":474097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/sssaj2011.0307","text":"Publisher Index Page"},{"id":272032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272030,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2011.0307"}],"country":"Kenya","otherGeospatial":"Western Kenya","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.91,-4.68 ], [ 33.91,5.05 ], [ 37.51,5.05 ], [ 37.51,-4.68 ], [ 33.91,-4.68 ] ] ] } } ] }","volume":"76","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-09-12","publicationStatus":"PW","scienceBaseUri":"518a1460e4b061e1bd53335b","contributors":{"authors":[{"text":"Kinoshita, Rintaro","contributorId":34800,"corporation":false,"usgs":true,"family":"Kinoshita","given":"Rintaro","email":"","affiliations":[],"preferred":false,"id":477644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moebius-Clune, Bianca N.","contributorId":62104,"corporation":false,"usgs":true,"family":"Moebius-Clune","given":"Bianca","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":477645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Es, Harold M.","contributorId":97800,"corporation":false,"usgs":true,"family":"van Es","given":"Harold","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hively, W. 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Under transformations that stabilize data and model-parameter variances, the most likely Poisson-event occurrence rate, $k/\\tau$, applies for frequentist inference and, also, for Bayesian inference with a Jeffreys prior that ensures posterior invariance under changes of variables. Frequentist confidence intervals and Bayesian (Jeffreys) credibility intervals are approximately the same and easy to calculate: $(1/\\tau)[(\\sqrt{k} - z/2)^{2},(\\sqrt{k} + z/2)^{2}]$, where $z$ is a parameter that specifies the width, $z=1$ ($z=2$) corresponding to $1\\sigma$, $68.3\\%$ ($2\\sigma$, $95.4\\%$). If only a few events have been observed, as is usually the case for extreme events, then these \"error-bar\" intervals might be considered to be relatively wide. From historical records, we estimate most likely long-term occurrence rates, 10-yr occurrence probabilities, and intervals of frequentist confidence and Bayesian credibility for large earthquakes, explosive volcanic eruptions, and magnetic storms.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GL051431","usgsCitation":"Love, J.J., 2012, Credible occurrence probabilities for extreme geophysical events: earthquakes, volcanic eruptions, magnetic storms: Geophysical Research Letters, v. 39, no. 10, L10301, https://doi.org/10.1029/2012GL051431.","productDescription":"L10301","ipdsId":"IP-037733","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012gl051431","text":"Publisher Index Page"},{"id":271365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271364,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GL051431"}],"volume":"39","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-05-18","publicationStatus":"PW","scienceBaseUri":"51764ddbe4b0f989f99e008e","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476944,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045472,"text":"ofr20121263 - 2012 - Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012","interactions":[],"lastModifiedDate":"2017-02-03T12:14:22","indexId":"ofr20121263","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1263","title":"Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012","docAbstract":"The U.S. Geological Survey (USGS) deployed a temporary monitoring network of water-level and barometric pressure sensors at 127 locations along the gulf coast from Alabama to Louisiana to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Isaac. This deployment was undertaken as part of a coordinated federal emergency response as outlined by the Stafford Act under a directed mission assignment by the Federal Emergency Management Agency. Storm tide, as defined by National Oceanic and Atmospheric Administration (NOAA; National Oceanic and Atmospheric Administration, 2008), is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm. Hurricane Isaac initially made landfall on the coast of Louisiana in Plaquemines Parish on August 28, 2012, as a Category 1 hurricane on the Saffir–Simpson Hurricane Wind Scale (National Weather Service, 1974) and then stalled over southern Louisiana for several days, causing prolonged storm-tide impacts. A total of 188 water-level and wave-height sensors were deployed at 127 locations during August 27–28 prior to landfall. More than 90 percent of the sensors and all high-water marks (HWMs) were recovered and surveyed to North American Vertical Datum of 1988 (NAVD 88) within 7 days of the Isaac landfall. Only a handful of sensors in the Plaquemines Parish area of Louisiana could not be retrieved until weeks later due to prolonged flooding in the area. Data collected from this event can be used to evaluate the performance of storm-tide models for maximum and incremental water level and flood extent and the site-specific effects of storm tide on natural and anthropogenic features of the environment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121263","collaboration":"Prepared under a mission assignment with the Federal Emergency Management Agency","usgsCitation":"McCallum, B.E., McGee, B.D., Kimbrow, D.R., Runner, M.S., Painter, J.A., Frantz, E.R., and Gotvald, A.J., 2012, Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012: U.S. Geological Survey Open-File Report 2012-1263, Report: ii, 26 p.; 6 Tables, https://doi.org/10.3133/ofr20121263.","productDescription":"Report: ii, 26 p.; 6 Tables","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-042625","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121263.JPG"},{"id":271126,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1263/"},{"id":271129,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1263/pdf/ofr2012-1263.pdf","text":"Report"},{"id":271131,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table1-Isaac.xlsx","text":"Table 1 - Number of monitoring sites, by state"},{"id":271133,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table2-Isaac.xlsx","text":"Table 2 - GNSS/NGS elevation differences"},{"id":271134,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table3-Isaac.xlsx","text":"Table 3 - Storm tides-temporary sites"},{"id":271136,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table5-Isaac.xlsx","text":"Table 5 - Storm tides-NOAA sites"},{"id":271137,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table6-Isaac.xlsx","text":"Table 6 - High-water marks"},{"id":271135,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table4-Isaac.xlsx","text":"Table 4 - Storm tides-USGS sites"}],"country":"United States","state":"Alabama, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.28515625,\n 28.719496107557465\n ],\n [\n -92.28515625,\n 30.883369321692268\n ],\n [\n -87.286376953125,\n 30.883369321692268\n ],\n [\n -87.286376953125,\n 28.719496107557465\n ],\n [\n -92.28515625,\n 28.719496107557465\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ce4b0c173799e78ea","contributors":{"authors":[{"text":"McCallum, Brian E. 0000-0002-8935-0343 bemccall@usgs.gov","orcid":"https://orcid.org/0000-0002-8935-0343","contributorId":1591,"corporation":false,"usgs":true,"family":"McCallum","given":"Brian","email":"bemccall@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGee, Benton D. bdmcgee@usgs.gov","contributorId":2899,"corporation":false,"usgs":true,"family":"McGee","given":"Benton","email":"bdmcgee@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runner, Michael S. msrunner@usgs.gov","contributorId":3497,"corporation":false,"usgs":true,"family":"Runner","given":"Michael","email":"msrunner@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":477584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frantz, Eric R. 0000-0002-1867-886X efrantz@usgs.gov","orcid":"https://orcid.org/0000-0002-1867-886X","contributorId":41573,"corporation":false,"usgs":true,"family":"Frantz","given":"Eric","email":"efrantz@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":477586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477582,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}