{"pageNumber":"1433","pageRowStart":"35800","pageSize":"25","recordCount":184723,"records":[{"id":70059199,"text":"70059199 - 2014 - Routine screening of harmful microorganisms in beach sands: implications to public health","interactions":[],"lastModifiedDate":"2013-12-20T09:44:10","indexId":"70059199","displayToPublicDate":"2013-12-20T09:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Routine screening of harmful microorganisms in beach sands: implications to public health","docAbstract":"Beaches worldwide provide recreational opportunities to hundreds of millions of people and serve as important components of coastal economies. Beach water is often monitored for microbiological quality to detect the presence of indicators of human sewage contamination so as to prevent public health outbreaks associated with water contact. However, growing evidence suggests that beach sand can harbor microbes harmful to human health, often in concentrations greater than the beach water. Currently, there are no standards for monitoring, sampling, analyzing, or managing beach sand quality. In addition to indicator microbes, growing evidence has identified pathogenic bacteria, viruses, and fungi in a variety of beach sands worldwide. The public health threat associated with these populations through direct and indirect contact is unknown because so little research has been conducted relating to health outcomes associated with sand quality. In this manuscript, we present the consensus findings of a workshop of experts convened in Lisbon, Portugal to discuss the current state of knowledge on beach sand microbiological quality and to develop suggestions for standardizing the evaluation of sand at coastal beaches. The expert group at the “Microareias 2012” workshop recommends that 1) beach sand should be screened for a variety of pathogens harmful to human health, and sand monitoring should then be initiated alongside regular water monitoring; 2) sampling and analysis protocols should be standardized to allow proper comparisons among beach locations; and 3) further studies are needed to estimate human health risk with exposure to contaminated beach sand. Much of the manuscript is focused on research specific to Portugal, but similar results have been found elsewhere, and the findings have worldwide implications.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2013.11.091","usgsCitation":"Sabino, R., Rodrigues, R., Costa, I., Carneiro, C., Cunha, M., Duarte, A., Faria, N., Ferriera, F., Gargate, M., Julio, C., Martins, M., Nevers, M., Oleastro, M., Solo-Gabriele, H., Verissimo, C., Viegas, C., Whitman, R.L., and Brandao, J., 2014, Routine screening of harmful microorganisms in beach sands: implications to public health: Science of the Total Environment, v. 472, p. 1062-1069, https://doi.org/10.1016/j.scitotenv.2013.11.091.","productDescription":"8 p.","startPage":"1062","endPage":"1069","numberOfPages":"8","ipdsId":"IP-050645","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488150,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10400.21/3027","text":"External Repository"},{"id":280451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280435,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.11.091"}],"volume":"472","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7129e4b0b29085107834","contributors":{"authors":[{"text":"Sabino, Raquel","contributorId":28157,"corporation":false,"usgs":true,"family":"Sabino","given":"Raquel","email":"","affiliations":[],"preferred":false,"id":487523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodrigues, R.","contributorId":23834,"corporation":false,"usgs":true,"family":"Rodrigues","given":"R.","email":"","affiliations":[],"preferred":false,"id":487522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costa, I.","contributorId":45617,"corporation":false,"usgs":true,"family":"Costa","given":"I.","email":"","affiliations":[],"preferred":false,"id":487526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carneiro, Carlos","contributorId":108014,"corporation":false,"usgs":true,"family":"Carneiro","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":487536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cunha, M.","contributorId":83437,"corporation":false,"usgs":true,"family":"Cunha","given":"M.","email":"","affiliations":[],"preferred":false,"id":487532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duarte, A.","contributorId":46405,"corporation":false,"usgs":true,"family":"Duarte","given":"A.","email":"","affiliations":[],"preferred":false,"id":487527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Faria, N.","contributorId":105213,"corporation":false,"usgs":true,"family":"Faria","given":"N.","email":"","affiliations":[],"preferred":false,"id":487535,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ferriera, F.C.","contributorId":38463,"corporation":false,"usgs":true,"family":"Ferriera","given":"F.C.","email":"","affiliations":[],"preferred":false,"id":487524,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gargate, M.J.","contributorId":100729,"corporation":false,"usgs":true,"family":"Gargate","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":487534,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Julio, C.","contributorId":39685,"corporation":false,"usgs":true,"family":"Julio","given":"C.","email":"","affiliations":[],"preferred":false,"id":487525,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Martins, M.L.","contributorId":72289,"corporation":false,"usgs":true,"family":"Martins","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":487530,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":487521,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oleastro, M.","contributorId":108015,"corporation":false,"usgs":true,"family":"Oleastro","given":"M.","email":"","affiliations":[],"preferred":false,"id":487537,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Solo-Gabriele, H.","contributorId":70275,"corporation":false,"usgs":true,"family":"Solo-Gabriele","given":"H.","affiliations":[],"preferred":false,"id":487528,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Verissimo, C.","contributorId":77450,"corporation":false,"usgs":true,"family":"Verissimo","given":"C.","email":"","affiliations":[],"preferred":false,"id":487531,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Viegas, C.","contributorId":94962,"corporation":false,"usgs":true,"family":"Viegas","given":"C.","email":"","affiliations":[],"preferred":false,"id":487533,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":487520,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Brandao, J.","contributorId":71870,"corporation":false,"usgs":true,"family":"Brandao","given":"J.","affiliations":[],"preferred":false,"id":487529,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70059129,"text":"70059129 - 2014 - Unique characteristics of the trachea of the juvenile leatherback turtle facilitate feeding, diving and endothermy","interactions":[],"lastModifiedDate":"2022-11-02T16:24:33.741251","indexId":"70059129","displayToPublicDate":"2013-12-18T09:47:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Unique characteristics of the trachea of the juvenile leatherback turtle facilitate feeding, diving and endothermy","docAbstract":"<p>The adult leatherback turtle <i>Dermochelys coriacea</i> overlaps in body size (300&ndash;500 kg) with many marine mammals, yet develops from a 50 g hatchling. Adults can dive deeper than 1200 m and have core body temperatures of 25 &deg;C; hatchlings are near-surface dwellers. Juvenile leatherbacks have rarely been studied; here we present anatomical information for the upper respiratory tract of 3 turtles (66.7&ndash;83.0 cm straight carapace length; 33.2&ndash;53.4 kg body mass) incidentally captured by long-line fisheries. Combined with existing information from adults and hatchlings, our data show that there is an ontogenic shift in tracheal structure, with cartilaginous rings becoming broader and eventually fusing anteriorly. This ontogenic shift during independent existence is unique among extant deep-diving air breathing vertebrates. Tract wall thickness is graded, becoming progressively thinner from larynx to bronchi. In addition, cross-sectional shape becomes increasingly dorsoventrally flattened (more elliptical) from anterior to posterior. These characteristics ensure that the tract will collapse from posterior to anterior during dives. This study contains the first report of a double (= internally bifurcated) posterior section of the trachea; it is suggested that this allows continuous food movement along the esophagus without tracheal collapse. The whole upper respiratory tract (from larynx to lungs) has a vascular lining (thicker anteriorly than posteriorly) that appears to be a simple analog of the complex turbinates of birds and mammals. Our study confirmed that the leatherback tracheal structure represents a distinctive way of dealing with the challenges of diving in deep, cold sea water.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2013.10.013","usgsCitation":"Davenport, J., Jones, T., Work, T.M., and Balazs, G.H., 2014, Unique characteristics of the trachea of the juvenile leatherback turtle facilitate feeding, diving and endothermy: Journal of Experimental Marine Biology and Ecology, v. 450, p. 40-46, https://doi.org/10.1016/j.jembe.2013.10.013.","productDescription":"7 p.","startPage":"40","endPage":"46","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049401","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":280396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Equatorial Pacific Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              166.77294853142018,\n              14.78558056021572\n            ],\n            [\n              166.77294853142018,\n              14.32788557818715\n            ],\n            [\n              167.43150821435654,\n              14.32788557818715\n            ],\n            [\n              167.43150821435654,\n              14.78558056021572\n            ],\n            [\n              166.77294853142018,\n              14.78558056021572\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              169.499920820532,\n              11.546374884556585\n            ],\n            [\n              169.499920820532,\n              11.127206568923143\n            ],\n            [\n              169.93721295290305,\n              11.127206568923143\n            ],\n            [\n              169.93721295290305,\n              11.546374884556585\n            ],\n            [\n              169.499920820532,\n              11.546374884556585\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              163.24369271990167,\n              5.106657114971725\n            ],\n            [\n              163.24369271990167,\n              4.40233629638837\n            ],\n            [\n              164.18797836826207,\n              4.40233629638837\n            ],\n            [\n              164.18797836826207,\n              5.106657114971725\n            ],\n            [\n              163.24369271990167,\n              5.106657114971725\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"450","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b2c406e4b08e3289f1571f","contributors":{"authors":[{"text":"Davenport, John","contributorId":68643,"corporation":false,"usgs":true,"family":"Davenport","given":"John","email":"","affiliations":[],"preferred":false,"id":487480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, T. Todd","contributorId":61334,"corporation":false,"usgs":true,"family":"Jones","given":"T. Todd","affiliations":[],"preferred":false,"id":487479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":487478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balazs, George H.","contributorId":88195,"corporation":false,"usgs":true,"family":"Balazs","given":"George","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":487481,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70059128,"text":"70059128 - 2014 - Impact of climate variability on runoff in the north-central United States","interactions":[],"lastModifiedDate":"2017-10-12T20:15:37","indexId":"70059128","displayToPublicDate":"2013-12-17T12:03:53","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Impact of climate variability on runoff in the north-central United States","docAbstract":"Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrologic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HE.1943-5584.0000775","usgsCitation":"Ryberg, K.R., Lin, W., and Vecchia, A.V., 2014, Impact of climate variability on runoff in the north-central United States: Journal of Hydrologic Engineering, v. 19, no. 1, p. 148-158, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000775.","productDescription":"11 p.","startPage":"148","endPage":"158","ipdsId":"IP-036799","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":280403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd620be4b0b290850fdec0","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Wei","contributorId":93805,"corporation":false,"usgs":true,"family":"Lin","given":"Wei","email":"","affiliations":[],"preferred":false,"id":487477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":487476,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70058881,"text":"70058881 - 2014 - The relation between invertebrate drift and two primary controls, discharge and benthic densities, in a large regulated river","interactions":[],"lastModifiedDate":"2014-01-24T09:32:06","indexId":"70058881","displayToPublicDate":"2013-12-17T10:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"The relation between invertebrate drift and two primary controls, discharge and benthic densities, in a large regulated river","docAbstract":"1. Invertebrate drift is a fundamental process in streams and rivers. Studies from laboratory experiments and small streams have identified numerous extrinsic (e.g. discharge, light intensity, water quality) and intrinsic factors (invertebrate life stage, benthic density, behaviour) that govern invertebrate drift concentrations (# m−3), but the factors that govern invertebrate drift in larger rivers remain poorly understood. For example, while large increases or decreases in discharge can lead to large increases in invertebrate drift, the role of smaller, incremental changes in discharge is poorly described. In addition, while we might expect invertebrate drift concentrations to be proportional to benthic densities (# m−2), the benthic–drift relation has not been rigorously evaluated.\n<br>\n2. Here, we develop a framework for modelling invertebrate drift that is derived from sediment transport studies. We use this framework to guide the analysis of high-resolution data sets of benthic density and drift concentration for four important invertebrate taxa from the Colorado River downstream of Glen Canyon Dam (mean daily discharge 325 m3 s−1) that were collected over 18 months and include multiple observations within days. Ramping of regulated flows on this river segment provides an experimental treatment that is repeated daily and allowed us to describe the functional relations between invertebrate drift and two primary controls, discharge and benthic densities.\n<br>\n3. Twofold daily variation in discharge resulted in a >10-fold increase in drift concentrations of benthic invertebrates associated with pools and detritus (i.e. Gammarus lacustris and Potamopyrgus antipodarum). In contrast, drift concentrations of sessile blackfly larvae (Simuliium arcticum), which are associated with high-velocity cobble microhabitats, decreased by over 80% as discharge doubled. Drift concentrations of Chironomidae increased proportional to discharge.\n<br>\n4. Drift of all four taxa was positively related to benthic density. Drift concentrations of Gammarus, Potamopyrgus and Chironomidae were proportional to benthic density. Drift concentrations of Simulium were positively related to benthic density, but the benthic–drift relation was less than proportional (i.e. a doubling of benthic density only led to a 40% increase in drift concentrations).\n<br>\n5. Our study demonstrates that invertebrate drift concentrations in the Colorado River are jointly controlled by discharge and benthic densities, but these controls operate at different timescales. Twofold daily variation in discharge associated with hydropeaking was the primary control on within-day variation in invertebrate drift concentrations. In contrast, benthic density, which varied 10- to 1000-fold among sampling dates, depending on the taxa, was the primary control on invertebrate drift concentrations over longer timescales (weeks to months).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12285","usgsCitation":"Kennedy, T., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M., and Copp, A.J., 2014, The relation between invertebrate drift and two primary controls, discharge and benthic densities, in a large regulated river: Freshwater Biology, v. 59, no. 3, p. 557-572, https://doi.org/10.1111/fwb.12285.","productDescription":"16 p.","startPage":"557","endPage":"572","numberOfPages":"16","ipdsId":"IP-045496","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":280362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280361,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12285"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.666667,36.833333 ], [ -111.666667,36.966667 ], [ -111.416667,36.966667 ], [ -111.416667,36.833333 ], [ -111.666667,36.833333 ] ] ] } } ] }","volume":"59","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-12-11","publicationStatus":"PW","scienceBaseUri":"52b172c1e4b0d9b325224604","contributors":{"authors":[{"text":"Kennedy, Theodore A. 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":50227,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":487413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":487410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Wyatt F.","contributorId":70881,"corporation":false,"usgs":true,"family":"Cross","given":"Wyatt","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":487414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":487409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yard, Michael D. 0000-0002-6580-6027","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":8577,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","affiliations":[],"preferred":false,"id":487412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Copp, Adam J. 0000-0001-7385-0055 acopp@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-0055","contributorId":5194,"corporation":false,"usgs":true,"family":"Copp","given":"Adam","email":"acopp@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":487411,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70058854,"text":"70058854 - 2014 - Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study","interactions":[],"lastModifiedDate":"2014-05-02T16:37:09","indexId":"70058854","displayToPublicDate":"2013-12-17T09:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study","docAbstract":"Toxic compounds such as organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ether flame retardants (PBDEs) have been detected in fish, birds, and aquatic mammals that live in the Columbia River or use food resources from within the river. We developed a custom microarray for largescale suckers (Catostomus macrocheilus) and used it to investigate the molecular effects of contaminant exposure on wild fish in the Columbia River. Using Significance Analysis of Microarrays (SAM) we identified 72 probes representing 69 unique genes with expression patterns that correlated with hepatic tissue levels of OCs, PCBs, or PBDEs. These genes were involved in many biological processes previously shown to respond to contaminant exposure, including drug and lipid metabolism, apoptosis, cellular transport, oxidative stress, and cellular chaperone function. The relation between gene expression and contaminant concentration suggests that these genes may respond to environmental contaminant exposure and are promising candidates for further field and laboratory studies to develop biomarkers for monitoring exposure of wild fish to contaminant mixtures found in the Columbia River Basin. The array developed in this study could also be a useful tool for studies involving endangered sucker species and other sucker species used in contaminant research.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2013.08.034","usgsCitation":"Christiansen, H.E., Mehinto, A.C., Yu, F., Perry, R.W., Denslow, N., Maule, A.G., and Mesa, M.G., 2014, Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study: Science of the Total Environment, v. 484, p. 379-389, https://doi.org/10.1016/j.scitotenv.2013.08.034.","productDescription":"11 p.","startPage":"379","endPage":"389","numberOfPages":"11","ipdsId":"IP-045118","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":280356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280327,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.08.034"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.2178,45.4972 ], [ -123.2178,46.2173 ], [ -121.9101,46.2173 ], [ -121.9101,45.4972 ], [ -123.2178,45.4972 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52b172bde4b0d9b3252245d9","contributors":{"authors":[{"text":"Christiansen, Helena E. hchristiansen@usgs.gov","contributorId":4530,"corporation":false,"usgs":true,"family":"Christiansen","given":"Helena","email":"hchristiansen@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":487402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mehinto, Alvine C.","contributorId":104387,"corporation":false,"usgs":true,"family":"Mehinto","given":"Alvine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":487404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yu, Fahong","contributorId":107180,"corporation":false,"usgs":true,"family":"Yu","given":"Fahong","email":"","affiliations":[],"preferred":false,"id":487405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Denslow, Nancy D.","contributorId":72831,"corporation":false,"usgs":true,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":487403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maule, Alec G. amaule@usgs.gov","contributorId":2606,"corporation":false,"usgs":true,"family":"Maule","given":"Alec","email":"amaule@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mesa, Matthew G. mmesa@usgs.gov","contributorId":3423,"corporation":false,"usgs":true,"family":"Mesa","given":"Matthew","email":"mmesa@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487401,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70058744,"text":"70058744 - 2014 - Climatic variation and tortoise survival: has a desert species met its match?","interactions":[],"lastModifiedDate":"2013-12-13T12:06:21","indexId":"70058744","displayToPublicDate":"2013-12-13T11:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Climatic variation and tortoise survival: has a desert species met its match?","docAbstract":"While demographic changes in short-lived species may be observed relatively quickly in response to climate changes, measuring population responses of long-lived species requires long-term studies that are not always available. We analyzed data from a population of threatened Agassiz’s desert tortoises (Gopherus agassizii) at a 2.59 km<sup>2</sup> study plot in the Sonoran Desert ecosystem of Joshua Tree National Park, California, USA from 1978 to 2012 to examine variation in apparent survival and demography in this long-lived species. Transect-based, mark-recapture surveys were conducted in 10 of those years to locate living and dead tortoises. Previous modeling suggested that this area would become unsuitable as tortoise habitat under a warming and drying climate scenario. Estimated adult population size declined greatly from 1996 to 2012. The population appeared to have high apparent survival from 1978 to 1996 but apparent survival decreased from 1997 to 2002, concurrent with persistent drought. The best model relating apparent survivorship of tortoises &ge;18 cm over time was based on a three year moving average of estimated winter precipitation. The postures and positions of a majority of dead tortoises found in 2012 were consistent with death by dehydration and starvation. Some live and many dead tortoises found in 2012 showed signs of predation or scavenging by mammalian carnivores. Coyote (Canis latrans) scats and other evidence from the site confirmed their role as tortoise predators and scavengers. Predation rates may be exacerbated by drought if carnivores switch from preferred mammalian prey to tortoises during dry years. Climate modeling suggests that the region will be subjected to even longer duration droughts in the future and that the plot may become unsuitable for continued tortoise survival. Our results showing wide fluctuations in apparent survival and decreasing tortoise density over time may be early signals of that possible outcome.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biological Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2013.09.027","usgsCitation":"Lovich, J.E., Yackulic, C.B., Freilich, J., Agha, M., Austin, M., Meyer, K.P., Arundel, T., Hansen, J., Vamstad, M., and Root, S., 2014, Climatic variation and tortoise survival: has a desert species met its match?: Biological Conservation, v. 169, p. 214-224, https://doi.org/10.1016/j.biocon.2013.09.027.","productDescription":"11 p.","startPage":"214","endPage":"224","numberOfPages":"11","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2013.09.027","text":"Publisher Index Page"},{"id":280295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280294,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.biocon.2013.09.027"}],"country":"United States","state":"California","otherGeospatial":"Joshua Tree National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.458031,33.670186 ], [ -116.458031,34.129343 ], [ -115.262191,34.129343 ], [ -115.262191,33.670186 ], [ -116.458031,33.670186 ] ] ] } } ] }","volume":"169","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ac2c62e4b004a77d23c4c9","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":487334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":487335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freilich, Jerry","contributorId":42518,"corporation":false,"usgs":true,"family":"Freilich","given":"Jerry","email":"","affiliations":[],"preferred":false,"id":487340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":487337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Austin, Meaghan","contributorId":37244,"corporation":false,"usgs":true,"family":"Austin","given":"Meaghan","affiliations":[],"preferred":false,"id":487339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyer, Katherine P.","contributorId":95789,"corporation":false,"usgs":true,"family":"Meyer","given":"Katherine","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arundel, Terence R.","contributorId":11080,"corporation":false,"usgs":true,"family":"Arundel","given":"Terence R.","affiliations":[],"preferred":false,"id":487336,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hansen, Jered","contributorId":34034,"corporation":false,"usgs":true,"family":"Hansen","given":"Jered","affiliations":[],"preferred":false,"id":487338,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vamstad, Michael S.","contributorId":66590,"corporation":false,"usgs":true,"family":"Vamstad","given":"Michael S.","affiliations":[],"preferred":false,"id":487341,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Root, Stephanie A.","contributorId":87449,"corporation":false,"usgs":true,"family":"Root","given":"Stephanie A.","affiliations":[],"preferred":false,"id":487342,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70058543,"text":"70058543 - 2014 - Ecological limit functions relating fish community response to hydrologic departures of the ecological flow regime in the Tennessee River basin, United States","interactions":[],"lastModifiedDate":"2016-12-14T11:37:49","indexId":"70058543","displayToPublicDate":"2013-12-09T11:20:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological limit functions relating fish community response to hydrologic departures of the ecological flow regime in the Tennessee River basin, United States","docAbstract":"<div class=\"para\"><p>Ecological limit functions relating streamflow and aquatic ecosystems remain elusive despite decades of research. We investigated functional relationships between species richness and changes in streamflow characteristics at 662 fish sampling sites in the Tennessee River basin. Our approach included the following: (1) a brief summary of relevant literature on functional relations between fish and streamflow, (2) the development of ecological limit functions that describe the strongest discernible relationships between fish species richness and streamflow characteristics, (3) the evaluation of proposed definitions of hydrologic reference conditions, and (4) an investigation of the internal structures of wedge-shaped distributions underlying ecological limit functions.</p><p>Twenty-one ecological limit functions were developed across three ecoregions that relate the species richness of 11 fish groups and departures from hydrologic reference conditions using multivariate and quantile regression methods. Each negatively sloped function is described using up to four streamflow characteristics expressed in terms of cumulative departure from hydrologic reference conditions. Negative slopes indicate increased departure results in decreased species richness.</p><p>Sites with the highest measured fish species richness generally had near-reference hydrologic conditions for a given ecoregion. Hydrology did not generally differ between sites with the highest and lowest fish species richness, indicating that other environmental factors likely limit species richness at sites with reference hydrology.</p><p>Use of ecological limit functions to make decisions regarding proposed hydrologic regime changes, although commonly presented as a management tool, is not as straightforward or informative as often assumed. We contend that statistical evaluation of the internal wedge structure below limit functions may provide a probabilistic understanding of how aquatic ecology is influenced by altered hydrology and may serve as the basis for evaluating the potential effect of proposed hydrologic changes.</p></div>","language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1002/eco.1460","usgsCitation":"Knight, R., Murphy, J.C., Wolfe, W., Saylor, C.F., and Wales, A.K., 2014, Ecological limit functions relating fish community response to hydrologic departures of the ecological flow regime in the Tennessee River basin, United States: Ecohydrology, v. 7, no. 5, p. 1262-1280, https://doi.org/10.1002/eco.1460.","productDescription":"19 p.","startPage":"1262","endPage":"1280","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044901","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":473325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.1460","text":"Publisher Index Page"},{"id":280230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280223,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/eco.1460"}],"country":"United States","otherGeospatial":"Tennessee River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.59374999999999,\n              33.925129700072\n            ],\n            [\n              -88.59374999999999,\n              37.3002752813443\n            ],\n            [\n              -81.23291015625,\n              37.3002752813443\n            ],\n            [\n              -81.23291015625,\n              33.925129700072\n            ],\n            [\n              -88.59374999999999,\n              33.925129700072\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-12-20","publicationStatus":"PW","scienceBaseUri":"52a717f2e4b0de1a6d2d96f3","contributors":{"authors":[{"text":"Knight, Rodney R. rrknight@usgs.gov","contributorId":2272,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney R.","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolfe, William J. wjwolfe@usgs.gov","contributorId":1888,"corporation":false,"usgs":true,"family":"Wolfe","given":"William J.","email":"wjwolfe@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":false,"id":487160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saylor, Charles F.","contributorId":29731,"corporation":false,"usgs":true,"family":"Saylor","given":"Charles","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":487163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wales, Amy K.","contributorId":108021,"corporation":false,"usgs":true,"family":"Wales","given":"Amy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":487164,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70058014,"text":"70058014 - 2014 - Integration of stable carbon isotope, microbial community, dissolved hydrogen gas, and <sup>2</sup>H<sub>H<sub>2</sub>O</sub> tracer data to assess bioaugmentation for chlorinated ethene degradation in fractured rocks","interactions":[],"lastModifiedDate":"2018-09-18T16:15:49","indexId":"70058014","displayToPublicDate":"2013-12-05T09:56:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Integration of stable carbon isotope, microbial community, dissolved hydrogen gas, and <sup>2</sup>H<sub>H<sub>2</sub>O</sub> tracer data to assess bioaugmentation for chlorinated ethene degradation in fractured rocks","docAbstract":"An in situ bioaugmentation (BA) experiment was conducted to understand processes controlling microbial dechlorination of trichloroethene (TCE) in groundwater at the Naval Air Warfare Center (NAWC), West Trenton, NJ. In the BA experiment, an electron donor (emulsified vegetable oil and sodium lactate) and a chloro-respiring microbial consortium were injected into a well in fractured mudstone of Triassic age. Water enriched in <sup>2</sup>H was also injected as a tracer of the BA solution, to monitor advective transport processes. The changes in concentration and the δ<sup>13</sup>C of TCE, cis-dichloroethene (cis-DCE), and vinyl chloride (VC); the δ<sup>2</sup>H of water; changes in the abundance of the microbial communities; and the concentration of dissolved H2 gas compared to pre- test conditions, provided multiple lines of evidence that enhanced biodegradation occurred in the injection well and in two downgradient wells. For those wells where the biodegradation was stimulated intensively, the sum of the molar chlorinated ethene (CE) concentrations in post-BA water was higher than that of the sum of the pre-BA background molar CE concentrations. The concentration ratios of TCE/(cis-DCE + VC) indicated that the increase in molar CE concentration may result from additional TCE mobilized from the rock matrix in response to the oil injection or due to desorption/diffusion. The stable carbon isotope mass-balance calculations show that the weighted average <sup>13</sup>C isotope of the CEs was enriched for around a year compared to the background value in a two year monitoring period, an effective indication that dechlorination of VC was occurring. Insights gained from this study can be applied to efforts to use BA in other fractured rock systems. The study demonstrates that a BA approach can substantially enhance in situ bioremediation not only in fractures connected to the injection well, but also in the rock matrix around the well due to processes such as diffusion and desorption. Because the effect of the BA was intensive only in wells where an amendment was distributed during injection, it is necessary to adequately distribute the amendments throughout the fractured rock to achieve substantial bioremediation. The slowdown in BA effect after a year is due to some extend to the decrease abundant of appropriate microbes, but more likely the decreased concentration of electron donor.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2013.10.004","usgsCitation":"Revesz, K.M., Lollar, B.S., Kirshtein, J.D., Tiedeman, C.R., Imbrigiotta, T., Goode, D., Shapiro, A.M., Voytek, M.A., Lancombe, P.J., and Busenberg, E., 2014, Integration of stable carbon isotope, microbial community, dissolved hydrogen gas, and <sup>2</sup>H<sub>H<sub>2</sub>O</sub> tracer data to assess bioaugmentation for chlorinated ethene degradation in fractured rocks: Journal of Contaminant Hydrology, v. 156, p. 62-77, https://doi.org/10.1016/j.jconhyd.2013.10.004.","productDescription":"16 p.","startPage":"62","endPage":"77","numberOfPages":"16","ipdsId":"IP-044573","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":280190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280189,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2013.10.004"}],"country":"United States","state":"New Jersey","city":"Ewing Township","otherGeospatial":"Naval Air Warfare Center, West Trenton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.838496,40.209396 ], [ -74.838496,40.283997 ], [ -74.725712,40.283997 ], [ -74.725712,40.209396 ], [ -74.838496,40.209396 ] ] ] } } ] }","volume":"156","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a1a089e4b02938ec05883c","contributors":{"authors":[{"text":"Revesz, Kinga M.","contributorId":18258,"corporation":false,"usgs":true,"family":"Revesz","given":"Kinga","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":486998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lollar, Barbara Sherwood","contributorId":18668,"corporation":false,"usgs":false,"family":"Lollar","given":"Barbara","email":"","middleInitial":"Sherwood","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":486999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kirshtein, Julie D.","contributorId":26033,"corporation":false,"usgs":true,"family":"Kirshtein","given":"Julie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":487000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":487002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":2466,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas E.","email":"timbrig@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":486997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":2433,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel J.","email":"djgoode@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":486996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":486994,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487003,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lancombe, Pierre J.","contributorId":33614,"corporation":false,"usgs":true,"family":"Lancombe","given":"Pierre","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":487001,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":486995,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70058428,"text":"70058428 - 2014 - Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation","interactions":[],"lastModifiedDate":"2013-12-05T09:39:16","indexId":"70058428","displayToPublicDate":"2013-12-05T09:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3475,"text":"Statistical Methodology","active":true,"publicationSubtype":{"id":10}},"title":"Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation","docAbstract":"Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Statistical Methodology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.stamet.2012.10.002","usgsCitation":"Zipkin, E., Leirness, J.B., Kinlan, B.P., O’Connell, A.F., and Silverman, E.D., 2014, Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation: Statistical Methodology, v. 17, p. 67-81, https://doi.org/10.1016/j.stamet.2012.10.002.","productDescription":"15 p.","startPage":"67","endPage":"81","numberOfPages":"15","ipdsId":"IP-041848","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":280187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280186,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.stamet.2012.10.002"}],"volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a1a089e4b02938ec058835","contributors":{"authors":[{"text":"Zipkin, Elise F.","contributorId":70528,"corporation":false,"usgs":true,"family":"Zipkin","given":"Elise F.","affiliations":[],"preferred":false,"id":487035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leirness, Jeffery B.","contributorId":24678,"corporation":false,"usgs":true,"family":"Leirness","given":"Jeffery","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":487033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinlan, Brian P.","contributorId":24679,"corporation":false,"usgs":true,"family":"Kinlan","given":"Brian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":487032,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silverman, Emily D.","contributorId":79220,"corporation":false,"usgs":true,"family":"Silverman","given":"Emily","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":487036,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70156236,"text":"70156236 - 2014 - Band reporting probablilities of mallards, American black ducks, and wood ducks in eastern North America","interactions":[],"lastModifiedDate":"2022-11-10T17:17:14.126777","indexId":"70156236","displayToPublicDate":"2013-12-05T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Band reporting probablilities of mallards, American black ducks, and wood ducks in eastern North America","docAbstract":"<p><span>Estimates of band reporting probabilities are used for managing North American waterfowl to convert band recovery probabilities into harvest probabilities, which are used to set harvest regulations. Band reporting probability is the probability that someone who has shot and retrieved a banded bird will report the band. This probability can vary relative to a number of factors, particularly the inscription on the band and the ease with which it can be reported. Other factors, such as geographic reporting region, and species and sex of the bird may also play a role. We tested whether reporting probabilities of wood ducks (</span><i>Aix sponsa</i><span>) and American black ducks (black ducks; </span><i>Anas rubripes</i><span>) differed from those of mallards (</span><i>Anas platyrhynchos</i><span>) and whether band reporting varied geographically or by the sex of the banded bird. In the analysis of spatially comparable wood duck and mallard data, a band reporting probability of 0.73 (95% CI = 0.67–0.78) was appropriate for use across species, sex, and reporting region within the United States. In the black duck–mallard comparison, the band reporting probability of black ducks in Eastern Canada (0.50, 95% CI = 0.44–0.57) was lower than in the Eastern United States (0.73, 95% CI = 0.62–0.83). These estimates reflected an increase in overall band reporting probability following the addition of a toll-free telephone number to band inscriptions. Lower reporting in Eastern Canada may be because of cultural, linguistic, or logistical barriers.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.647","usgsCitation":"Garrettson, P., Raftovich, R.V., Hines, J.E., and Zimmerman, G.S., 2014, Band reporting probablilities of mallards, American black ducks, and wood ducks in eastern North America: Journal of Wildlife Management, v. 78, no. 1, p. 50-57, https://doi.org/10.1002/jwmg.647.","productDescription":"7 p.","startPage":"50","endPage":"57","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052406","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":306826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": 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System","active":true,"usgs":false}],"preferred":false,"id":568122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":568120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":568123,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70058431,"text":"70058431 - 2014 - Precise determination of δ<sup>88</sup>Sr in rocks, minerals, and waters by double-spike TIMS: A powerful tool in the study of chemical, geologic, hydrologic and biologic processes","interactions":[],"lastModifiedDate":"2013-12-05T10:25:37","indexId":"70058431","displayToPublicDate":"2013-12-04T10:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2155,"text":"Journal of Analytical Atomic Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"Precise determination of δ<sup>88</sup>Sr in rocks, minerals, and waters by double-spike TIMS: A powerful tool in the study of chemical, geologic, hydrologic and biologic processes","docAbstract":"We present strontium isotopic (<sup>88</sup>Sr/<sup>86</sup>Sr and <sup>87</sup>Sr/<sup>86</sup>Sr) results obtained by <sup>87</sup>Sr–<sup>84</sup>Sr double spike thermal ionization mass-spectrometry (DS-TIMS) for several standards as well as natural water samples and mineral samples of abiogenic and biogenic origin. The detailed data reduction algorithm and a user-friendly Sr-specific stand-alone computer program used for the spike calibration and the data reduction are also presented. Accuracy and precision of our δ<sup>88</sup>Sr measurements, calculated as permil (‰) deviations from the NIST SRM-987 standard, were evaluated by analyzing the NASS-6 seawater standard, which yielded δ<sup>88</sup>Sr = 0.378 ± 0.009‰. The first DS-TIMS data for the NIST SRM-607 potassium feldspar standard and for several US Geological Survey carbonate, phosphate, and silicate standards (EN-1, MAPS-4, MAPS-5, G-3, BCR-2, and BHVO-2) are also reported. Data obtained during this work for Sr-bearing solids and natural waters show a range of δ<sup>88</sup>Sr values of about 2.4‰, the widest observed so far in terrestrial materials. This range is easily resolvable analytically because the demonstrated external error (±SD, standard deviation) for measured δ<sup>88</sup>Sr values is typically ≤0.02‰. It is shown that the “true” <sup>87</sup>Sr/<sup>86</sup>Sr value obtained by the DS-TIMS or any other external normalization method combines radiogenic and mass-dependent mass-fractionation effects, which cannot be separated. Therefore, the “true” <sup>87</sup>Sr/<sup>86</sup>Sr and the δ<sup>87</sup>Sr parameter derived from it are not useful isotope tracers. Data presented in this paper for a wide range of naturally occurring sample types demonstrate the potential of the δ<sup>88</sup>Sr isotope tracer in combination with the traditional radiogenic <sup>87</sup>Sr/<sup>86</sup>Sr tracer for studying a variety of biological, hydrological, and geological processes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Analytical Atomic Spectrometry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C3JA50310K","usgsCitation":"Neymark, L.A., Premo, W.R., Mel’nikov, N.N., and Emsbo, P., 2014, Precise determination of δ<sup>88</sup>Sr in rocks, minerals, and waters by double-spike TIMS: A powerful tool in the study of chemical, geologic, hydrologic and biologic processes: Journal of Analytical Atomic Spectrometry, v. 29, p. 65-75, https://doi.org/10.1039/C3JA50310K.","productDescription":"11 p.","startPage":"65","endPage":"75","numberOfPages":"11","ipdsId":"IP-050748","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":280192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280191,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1039/C3JA50310K"}],"volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a1aea5e4b02938ec05c900","contributors":{"authors":[{"text":"Neymark, Leonid A. lneymark@usgs.gov","contributorId":532,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid","email":"lneymark@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":487037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Premo, Wayne R. 0000-0001-9904-4801 wpremo@usgs.gov","orcid":"https://orcid.org/0000-0001-9904-4801","contributorId":1697,"corporation":false,"usgs":true,"family":"Premo","given":"Wayne","email":"wpremo@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":487039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mel’nikov, Nikolay N.","contributorId":37246,"corporation":false,"usgs":true,"family":"Mel’nikov","given":"Nikolay","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":487040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":487038,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70094738,"text":"70094738 - 2014 - Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt","interactions":[],"lastModifiedDate":"2014-02-24T15:54:43","indexId":"70094738","displayToPublicDate":"2013-12-01T15:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1866,"text":"Groundwater Monitoring & Remediation","active":true,"publicationSubtype":{"id":10}},"title":"Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt","docAbstract":"Starting in 2008, a 4-year tracer study was conducted to evaluate ambient changes in groundwater concentrations of a 1,3,6-naphthalene trisulfonate tracer that was added to drill water. Samples were collected under open borehole conditions and after installing a multilevel groundwater monitoring system completed with 11 discrete monitoring zones within dense and fractured basalt and sediment layers in the eastern Snake River aquifer. The study was done in cooperation with the U.S. Department of Energy to test whether ambient fracture flow conditions were sufficient to remove the effects of injected drill water prior to sample collection. Results from thief samples indicated that the tracer was present in minor concentrations 28 days after coring, but was not present 6 months after coring or 7 days after reaming the borehole. Results from sampling the multilevel monitoring system indicated that small concentrations of the tracer remained in 5 of 10 zones during some period after installation. All concentrations were several orders of magnitude lower than the initial concentrations in the drill water. The ports that had remnant concentrations of the tracer were either located near sediment layers or were located in dense basalt, which suggests limited groundwater flow near these ports. The ports completed in well-fractured and vesicular basalt had no detectable concentrations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Groundwater Monitoring & Remediation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gwmr.12038","usgsCitation":"Bartholomay, R.C., Twining, B.V., and Rose, P.E., 2014, Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt: Groundwater Monitoring & Remediation, v. 34, no. 1, p. 79-88, https://doi.org/10.1111/gwmr.12038.","productDescription":"10 p.","startPage":"79","endPage":"88","numberOfPages":"10","ipdsId":"IP-042016","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":473327,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwmr.12038","text":"Publisher Index Page"},{"id":282712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282680,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwmr.12038"}],"scale":"100000","projection":"Universal Transverse Mercator Projection","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.5,43.25 ], [ -113.5,44.25 ], [ -112.25,44.25 ], [ -112.25,43.25 ], [ -113.5,43.25 ] ] ] } } ] }","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-06","publicationStatus":"PW","scienceBaseUri":"53cd4c3ee4b0b290850f0ddb","contributors":{"authors":[{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Peter E.","contributorId":103574,"corporation":false,"usgs":true,"family":"Rose","given":"Peter","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490845,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048865,"text":"70048865 - 2014 - Hysteresis and uncertainty in soil water-retention curve parameters","interactions":[],"lastModifiedDate":"2018-03-08T15:54:54","indexId":"70048865","displayToPublicDate":"2013-12-01T14:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2327,"text":"Journal of Geotechnical and Geoenvironmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Hysteresis and uncertainty in soil water-retention curve parameters","docAbstract":"Accurate estimates of soil hydraulic parameters representing wetting and drying paths are required for predicting hydraulic and mechanical responses in a large number of applications. A comprehensive suite of laboratory experiments was conducted to measure hysteretic soil-water characteristic curves (SWCCs) representing a wide range of soil types. Results were used to quantitatively assess differences and uncertainty in three simplifications frequently adopted to estimate wetting-path SWCC parameters from more easily measured drying curves. They are the following: (1) α<sup>w</sup>=2α<sup>d</sup>, (2) n<sup>w</sup>=n<sup>d</sup>, and (3) θ<sup>w</sup><sub>s</sub>=θ<sup>d</sup><sub>s</sub>, where α, n, and θ<sub>s</sub> are fitting parameters entering van Genuchten’s commonly adopted SWCC model, and the superscripts w and d indicate wetting and drying paths, respectively. The average ratio αw/αd for the data set was 2.24±1.25. Nominally cohesive soils had a lower α<sup>w</sup>/α<sup>d</sup> ratio (1.73±0.94) than nominally cohesionless soils (3.14±1.27). The average n<sup>w</sup>/n<sup>d</sup> ratio was 1.01±0.11 with no significant dependency on soil type, thus confirming the n<sup>w</sup>=n<sup>d</sup> simplification for a wider range of soil types than previously available. Water content at zero suction during wetting (θ<sup>w</sup><sub>s</sub>) was consistently less than during drying (θ<sup>d</sup><sub>s</sub>) owing to air entrapment. The θ<sup>w</sup><sub>s</sub>/θ<sup>d</sup>s</sup> ratio averaged 0.85±0.10 and was comparable for nominally cohesive (0.87±0.11) and cohesionless (0.81±0.08) soils. Regression statistics are provided to quantitatively account for uncertainty in estimating hysteretic retention curves. Practical consequences are demonstrated for two case studies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geotechnical and Geoenvironmental Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)GT.1943-5606.0001071","usgsCitation":"Likos, W.J., Lu, N., and Godt, J.W., 2014, Hysteresis and uncertainty in soil water-retention curve parameters: Journal of Geotechnical and Geoenvironmental Engineering, v. 140, no. 4, 11 p., https://doi.org/10.1061/(ASCE)GT.1943-5606.0001071.","productDescription":"11 p.","numberOfPages":"11","ipdsId":"IP-052321","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":280761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280760,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)GT.1943-5606.0001071"}],"volume":"140","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd61dee4b0b290850fdcdf","contributors":{"authors":[{"text":"Likos, William J.","contributorId":14725,"corporation":false,"usgs":true,"family":"Likos","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":485768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":485766,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70098946,"text":"70098946 - 2014 - Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm","interactions":[],"lastModifiedDate":"2017-04-06T16:13:58","indexId":"70098946","displayToPublicDate":"2013-12-01T14:31:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm","docAbstract":"Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer’s accuracy of 93% and a user’s accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of ≥95% for cultivated croplands and ≥76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.","language":"English","publisher":"SPIE","doi":"10.1117/1.JRS.8.083685","usgsCitation":"Wu, Z., Thenkabail, P.S., Mueller, R., Zakzeski, A., Melton, F., Johnson, L., Rosevelt, C., Dwyer, J., Jones, J., and Verdin, J.P., 2014, Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm: Journal of Applied Remote Sensing, v. 8, no. 1, Article 083685; 17 p., https://doi.org/10.1117/1.JRS.8.083685.","productDescription":"Article 083685; 17 p.","numberOfPages":"17","ipdsId":"IP-044862","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1117/1.jrs.8.083685","text":"Publisher Index Page"},{"id":284264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284265,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.JRS.8.083685"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.0,33.0 ], [ -125.0,42.0 ], [ -115.0,42.0 ], [ -115.0,33.0 ], [ -125.0,33.0 ] ] ] } } ] }","volume":"8","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd71abe4b0b29085107d2e","contributors":{"authors":[{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":491771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":491769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Rick","contributorId":101182,"corporation":false,"usgs":false,"family":"Mueller","given":"Rick","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":491778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zakzeski, Audra","contributorId":79796,"corporation":false,"usgs":true,"family":"Zakzeski","given":"Audra","email":"","affiliations":[],"preferred":false,"id":491777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melton, F.","contributorId":34039,"corporation":false,"usgs":true,"family":"Melton","given":"F.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":491774,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Lee","contributorId":60122,"corporation":false,"usgs":true,"family":"Johnson","given":"Lee","email":"","affiliations":[],"preferred":false,"id":491776,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosevelt, Carolyn","contributorId":25455,"corporation":false,"usgs":true,"family":"Rosevelt","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":491773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwyer, John","contributorId":45042,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","affiliations":[],"preferred":false,"id":491775,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jones, Jeanine","contributorId":6758,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanine","email":"","affiliations":[],"preferred":false,"id":491772,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":491770,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70049728,"text":"70049728 - 2014 - Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.","interactions":[],"lastModifiedDate":"2014-01-24T09:47:59","indexId":"70049728","displayToPublicDate":"2013-12-01T11:21:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.","docAbstract":"As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrobiologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10750-013-1774-4","usgsCitation":"Waite, I.R., 2014, Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.: Hydrobiologia, v. 726, no. 1, p. 285-303, https://doi.org/10.1007/s10750-013-1774-4.","productDescription":"19 p.","startPage":"285","endPage":"303","numberOfPages":"19","ipdsId":"IP-038732","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":280866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280865,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10750-013-1774-4"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"726","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-18","publicationStatus":"PW","scienceBaseUri":"53cd4c08e4b0b290850f0b8b","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486107,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70046853,"text":"70046853 - 2014 - Deep-ocean ferromanganese crusts and nodules","interactions":[],"lastModifiedDate":"2017-02-03T12:38:01","indexId":"70046853","displayToPublicDate":"2013-12-01T10:52:50","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Deep-ocean ferromanganese crusts and nodules","docAbstract":"Ferromanganese crusts and nodules may provide a future resource for a large variety of metals, including many that are essential for emerging high- and green-technology applications. A brief review of nodules and crusts provides a setting for a discussion on the latest (past 10 years) research related to the geochemistry of sequestration of metals from seawater. Special attention is given to cobalt, nickel, titanium, rare earth elements and yttrium, bismuth, platinum, tungsten, tantalum, hafnium, tellurium, molybdenum, niobium, zirconium, and lithium. Sequestration from seawater by sorption, surface oxidation, substitution, and precipitation of discrete phases is discussed. Mechanisms of metal enrichment reflect modes of formation of the crusts and nodules, such as hydrogenetic (from seawater), diagenetic (from porewaters), and mixed diagenetic–hydrogenetic processes.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-095975-7.01111-6","usgsCitation":"Hein, J.R., and Koschinsky, A., 2014, Deep-ocean ferromanganese crusts and nodules, chap. <i>of</i> Treatise on geochemistry, v. 13, p. 273-291, https://doi.org/10.1016/B978-0-08-095975-7.01111-6.","productDescription":"19 p.","startPage":"273","endPage":"291","ipdsId":"IP-030576","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":284154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284153,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/B978-0-08-095975-7.01111-6"}],"volume":"13","edition":"Second","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd53f0e4b0b290850f574a","contributors":{"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":480471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koschinsky, Andrea","contributorId":83813,"corporation":false,"usgs":true,"family":"Koschinsky","given":"Andrea","affiliations":[],"preferred":false,"id":480472,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70096238,"text":"70096238 - 2014 - Near-bottom circulation and dispersion of sediment containing <i>Alexandrium fundyense</i> cysts in the Gulf of Maine during 2010-2011","interactions":[],"lastModifiedDate":"2014-05-29T14:45:26","indexId":"70096238","displayToPublicDate":"2013-12-01T10:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Near-bottom circulation and dispersion of sediment containing <i>Alexandrium fundyense</i> cysts in the Gulf of Maine during 2010-2011","docAbstract":"The life cycle of <i>Alexandrium fundyense</i> in the Gulf of Maine includes a dormant cyst stage that spends the winter predominantly in the bottom sediment. Wave-current bottom stress caused by storms and tides induces resuspension of cyst-containing sediment during winter and spring. Resuspended sediment could be transported by water flow to different locations in the Gulf and the redistribution of sediment containing <i>A. fundyense</i> cysts could alter the spatial and temporal manifestation of its spring bloom. The present study evaluates model near-bottom flow during storms, when sediment resuspension and redistribution are most likely to occur, between October and May when <i>A. fundyense</i> cells are predominantly in cyst form. Simulated water column sediment (mud) concentrations from representative locations of the Gulf are used to initialize particle tracking simulations for the period October 2010–May 2011. Particles are tracked in full three-dimensional model solutions including a sinking velocity characteristic of cyst and aggregated mud settling (0.1 mm s<sup>−</sup>1). Although most of the material was redeposited near the source areas, small percentages of total resuspended sediment from some locations in the western (~4%) and eastern (2%) Maine shelf and the Bay of Fundy (1%) traveled distances longer than 100 km before resettling. The redistribution changed seasonally and was sensitive to the prescribed sinking rate. Estimates of the amount of cysts redistributed with the sediment were small compared to the inventory of cysts in the upper few centimeters of sediment but could potentially have more relevance immediately after deposition.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.11.003","usgsCitation":"Aretxabaleta, A., Butman, B., Signell, R.P., Dalyander, P., Sherwood, C.R., Sheremet, V.A., and McGillicuddy, D.J., 2014, Near-bottom circulation and dispersion of sediment containing <i>Alexandrium fundyense</i> cysts in the Gulf of Maine during 2010-2011: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 103, p. 96-111, https://doi.org/10.1016/j.dsr2.2013.11.003.","productDescription":"16 p.","startPage":"96","endPage":"111","numberOfPages":"16","ipdsId":"IP-051764","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473329,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2013.11.003","text":"Publisher Index Page"},{"id":283874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283873,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.11.003"}],"country":"United States","state":"Maine","otherGeospatial":"Bay Of Fundy;Gulf Of Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.0,42.5 ], [ -71.0,45.5 ], [ -65.0,45.5 ], [ -65.0,42.5 ], [ -71.0,42.5 ] ] ] } } ] }","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53885706e4b0318b93124adf","contributors":{"authors":[{"text":"Aretxabaleta, Alfredo L.","contributorId":41311,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo L.","affiliations":[],"preferred":false,"id":491497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":491494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":491499,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":491495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sheremet, Vitalii A.","contributorId":52886,"corporation":false,"usgs":true,"family":"Sheremet","given":"Vitalii","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491498,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGillicuddy, Dennis J. Jr.","contributorId":13541,"corporation":false,"usgs":true,"family":"McGillicuddy","given":"Dennis","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491496,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70068813,"text":"70068813 - 2014 - Compaction and gas loss in welded pyroclastic deposits as revealed by porosity, permeability, and electrical conductivity measurements of the Shevlin Park Tuff","interactions":[],"lastModifiedDate":"2019-03-14T09:28:56","indexId":"70068813","displayToPublicDate":"2013-12-01T10:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Compaction and gas loss in welded pyroclastic deposits as revealed by porosity, permeability, and electrical conductivity measurements of the Shevlin Park Tuff","docAbstract":"Pyroclastic flows produced by large volcanic eruptions commonly densify after emplacement. Processes of gas escape, compaction, and welding in pyroclastic-flow deposits are controlled by the physical and thermal properties of constituent material. Through measurements of matrix porosity, permeability, and electrical conductivity, we provide a framework for understanding the evolution of pore structure during these processes. Using data from the Shevlin Park Tuff in central Oregon, United States, and from the literature, we find that over a porosity range of 0%–70%, matrix permeability varies by almost 10 orders of magnitude (from 10<sup>–20</sup> to 10<sup>–11</sup> m<sup>2</sup>), with over three orders of magnitude variation at any given porosity. Part of the variation at a given porosity is due to permeability anisotropy, where oriented core samples indicate higher permeabilities parallel to foliation (horizontally) than perpendicular to foliation (vertically). This suggests that pore space is flattened during compaction, creating anisotropic crack-like networks, a geometry that is supported by electrical conductivity measurements. We find that the power law equation: <i>k</i><sub>1</sub> = 1.3 × 10<sup>–21</sup> × ϕ<sup>5.2</sup> provides the best approximation of dominant horizontal gas loss, where <i>k</i><sub>1</sub> = permeability, and ϕ = porosity. Application of Kozeny-Carman fluid-flow approximations suggests that permeability in the Shevlin Park Tuff is controlled by crack- or disk-like pore apertures with minimum widths of 0.3 and 7.5 μm. We find that matrix permeability limits compaction over short times, but deformation is then controlled by competition among cooling, compaction, water resorption, and permeable gas escape. These competing processes control the potential for development of overpressure (and secondary explosions) and the degree of welding in the deposit, processes that are applicable to viscous densification of volcanic deposits in general. Further, the general relationships among porosity, permeability, and pore geometry are relevant for flow of any fluid through an ignimbritic host.","language":"English","publisher":"Geological Society of America","doi":"10.1130/B30668.1","usgsCitation":"Wright, H.M., and Cashman, K., 2014, Compaction and gas loss in welded pyroclastic deposits as revealed by porosity, permeability, and electrical conductivity measurements of the Shevlin Park Tuff: GSA Bulletin, v. 126, no. 1-2, p. 234-247, https://doi.org/10.1130/B30668.1.","productDescription":"14 p.","startPage":"234","endPage":"247","numberOfPages":"14","ipdsId":"IP-042666","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":280975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Shevlin Park Tuff","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.7,43.933333 ], [ -121.7,44.3 ], [ -121.3,44.3 ], [ -121.3,43.933333 ], [ -121.7,43.933333 ] ] ] } } ] }","volume":"126","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2013-12-13","publicationStatus":"PW","scienceBaseUri":"53cd51e7e4b0b290850f4342","contributors":{"authors":[{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":488132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Katharine V.","contributorId":40097,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine V.","affiliations":[],"preferred":false,"id":488133,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048647,"text":"70048647 - 2014 - The Mw 5.8 Mineral, Virginia, earthquake of August 2011 and aftershock sequence: constraints on earthquake source parameters and fault geometry","interactions":[],"lastModifiedDate":"2014-02-24T11:04:12","indexId":"70048647","displayToPublicDate":"2013-12-01T10:09:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The Mw 5.8 Mineral, Virginia, earthquake of August 2011 and aftershock sequence: constraints on earthquake source parameters and fault geometry","docAbstract":"<p>The M<sub>w</sub> 5.8 earthquake of 23 August 2011 (17:51:04 UTC) (moment, M0 5.7×10<sup>17</sup>  N·m) occurred near Mineral, Virginia, within the central Virginia seismic zone and was felt by more people than any other earthquake in United States history. The U.S. Geological Survey (USGS) received 148,638 felt reports from 31 states and 4 Canadian provinces. The USGS PAGER system estimates as many as 120,000 people were exposed to shaking intensity levels of IV and greater, with approximately 10,000 exposed to shaking as high as intensity VIII. Both regional and teleseismic moment tensor solutions characterize the earthquake as a northeast‐striking reverse fault that nucleated at a depth of approximately 7±2  km. The distribution of reported macroseismic intensities is roughly ten times the area of a similarly sized earthquake in the western United States (Horton and Williams, 2012). Near‐source and far‐field damage reports, which extend as far away as Washington, D.C., (135 km away) and Baltimore, Maryland, (200 km away) are consistent with an earthquake of this size and depth in the eastern United States (EUS).</p>\n<br/>\n<p>Within the first few days following the earthquake, several government and academic institutions installed 36 portable seismograph stations in the epicentral region, making this among the best‐recorded aftershock sequences in the EUS. Based on modeling of these data, we provide a detailed description of the source parameters of the mainshock and analysis of the subsequent aftershock sequence for defining the fault geometry, area of rupture, and observations of the aftershock sequence magnitude–frequency and temporal distribution. The observed slope of the magnitude–frequency curve or b‐value for the aftershock sequence is consistent with previous EUS studies (b=0.75), suggesting that most of the accumulated strain was released by the mainshock. The aftershocks define a rupture that extends between approximately 2–8 km in depth and 8–10 km along the strike of the fault plane. Best‐fit modeling of the geometry of the aftershock sequence defines a rupture plane that strikes N36°E and dips to the east‐southeast at 49.5°. Moment tensor solutions of the mainshock and larger aftershocks are consistent with the distribution of aftershock locations, both indicating reverse slip along a northeast–southwest striking southeast‐dipping fault plane.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130058","usgsCitation":"McNamara, D.E., Benz, H., Herrmann, R., Bergman, E.A., Earle, P., Meltzer, A., Withers, M., and Chapman, M., 2014, The Mw 5.8 Mineral, Virginia, earthquake of August 2011 and aftershock sequence: constraints on earthquake source parameters and fault geometry: Bulletin of the Seismological Society of America, v. 104, no. 1, p. 40-54, https://doi.org/10.1785/0120130058.","productDescription":"15 p.","startPage":"40","endPage":"54","numberOfPages":"15","ipdsId":"IP-051290","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":280971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280970,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120130058"}],"country":"Canada;United States","state":"Virginia","city":"Mineral","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.86,30.86 ], [ -88.86,46.86 ], [ -66.8,46.86 ], [ -66.8,30.86 ], [ -88.86,30.86 ] ] ] } } ] }","volume":"104","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-24","publicationStatus":"PW","scienceBaseUri":"53cd7714e4b0b2908510b519","contributors":{"authors":[{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":485272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benz, H.M.","contributorId":21594,"corporation":false,"usgs":true,"family":"Benz","given":"H.M.","email":"","affiliations":[],"preferred":false,"id":485274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrmann, Robert B.","contributorId":80255,"corporation":false,"usgs":false,"family":"Herrmann","given":"Robert B.","affiliations":[],"preferred":false,"id":485278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergman, Eric A. 0000-0002-7069-8286","orcid":"https://orcid.org/0000-0002-7069-8286","contributorId":84513,"corporation":false,"usgs":false,"family":"Bergman","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485279,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earle, Paul","contributorId":13536,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","affiliations":[],"preferred":false,"id":485273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meltzer, Anne","contributorId":64559,"corporation":false,"usgs":true,"family":"Meltzer","given":"Anne","affiliations":[],"preferred":false,"id":485277,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Withers, Mitch","contributorId":24684,"corporation":false,"usgs":true,"family":"Withers","given":"Mitch","email":"","affiliations":[],"preferred":false,"id":485275,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chapman, Martin","contributorId":45622,"corporation":false,"usgs":true,"family":"Chapman","given":"Martin","affiliations":[],"preferred":false,"id":485276,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70093432,"text":"70093432 - 2014 - An evaluation of temporal changes in sediment accumulation and impacts on carbon burial in Mobile Bay, Alabama, USA","interactions":[],"lastModifiedDate":"2025-05-13T17:02:45.609004","indexId":"70093432","displayToPublicDate":"2013-12-01T09:56:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of temporal changes in sediment accumulation and impacts on carbon burial in Mobile Bay, Alabama, USA","docAbstract":"The estuarine environment can serve as either a source or sink of carbon relative to the coastal ocean carbon budget. A variety of time-dependent processes such as sedimentation, carbon supply, and productivity dictate how estuarine systems operate, and Mobile Bay is a system that has experienced both natural and anthropogenic perturbations that influenced depositional processes and carbon cycling. Sediments from eight box cores provide a record of change in bulk sediment accumulation and carbon burial over the past 110 years. Accumulation rates in the central part of the basin (0.09 g cm<sup>−2</sup>) were 60–80 % less than those observed at the head (0.361 g cm<sup>−2</sup>) and mouth (0.564 g cm<sup>−2</sup>) of the bay. Sediment accumulation in the central bay decreased during the past 90 years in response to both anthropogenic (causeway construction) and natural (tropical cyclones) perturbations. Sediment accumulation inevitably increased the residence time of organic carbon in the oxic zone, as observed in modeled remineralization rates, and reduced the overall carbon burial. Such observations highlight the critical balance among sediment accumulation, carbon remineralization, and carbon burial in dynamic coastal environments. Time-series analysis based solely on short-term observation would not capture the long-term effects of changes in sedimentation on carbon cycling. Identifying these relationships over longer timescales (multi-annual to decadal) will provide a far better evaluation of coastal ocean carbon budgets.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuaries and Coasts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s12237-013-9731-z","usgsCitation":"Smith, C.G., and Osterman, L.E., 2014, An evaluation of temporal changes in sediment accumulation and impacts on carbon burial in Mobile Bay, Alabama, USA: Estuaries and Coasts, v. 37, no. 5, p. 1092-1106, https://doi.org/10.1007/s12237-013-9731-z.","productDescription":"15 p.","startPage":"1092","endPage":"1106","numberOfPages":"15","ipdsId":"IP-045967","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":282102,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282101,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-013-9731-z"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,30.25 ], [ -88.25,30.833333 ], [ -87.583333,30.833333 ], [ -87.583333,30.25 ], [ -88.25,30.25 ] ] ] } } ] }","volume":"37","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-12-04","publicationStatus":"PW","scienceBaseUri":"53cd4c87e4b0b290850f107a","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":490008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osterman, Lisa E. osterman@usgs.gov","contributorId":3058,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":490007,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70073499,"text":"70073499 - 2014 - Geochronology and paleoenvironment of pluvial Harper Lake, Mojave Desert, California, USA","interactions":[],"lastModifiedDate":"2014-03-28T09:44:27","indexId":"70073499","displayToPublicDate":"2013-12-01T09:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Geochronology and paleoenvironment of pluvial Harper Lake, Mojave Desert, California, USA","docAbstract":"Accurate reconstruction of the paleo-Mojave River and pluvial lake (Harper, Manix, Cronese, and Mojave) system of southern California is critical to understanding paleoclimate and the North American polar jet stream position over the last 500 ka. Previous studies inferred a polar jet stream south of 35°N at 18 ka and at ~ 40°N at 17–14 ka. Highstand sediments of Harper Lake, the upstream-most pluvial lake along the Mojave River, have yielded uncalibrated radiocarbon ages ranging from 24,000 to > 30,000 <sup>14</sup>C yr BP. Based on geologic mapping, radiocarbon and optically stimulated luminescence dating, we infer a ~ 45–40 ka age for the Harper Lake highstand sediments. Combining the Harper Lake highstand with other Great Basin pluvial lake/spring and marine climate records, we infer that the North American polar jet stream was south of 35°N about 45–40 ka, but shifted to 40°N by ~ 35 ka. Ostracodes (<i>Limnocythere ceriotuberosa</i>) from Harper Lake highstand sediments are consistent with an alkaline lake environment that received seasonal inflow from the Mojave River, thus confirming the lake was fed by the Mojave River. The ~ 45–40 ka highstand at Harper Lake coincides with a shallowing interval at downstream Lake Manix.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.yqres.2013.10.008","usgsCitation":"Garcia, A.L., Knott, J.R., Mahan, S., and Bright, J., 2014, Geochronology and paleoenvironment of pluvial Harper Lake, Mojave Desert, California, USA: Quaternary Research, v. 81, no. 2, p. 305-317, https://doi.org/10.1016/j.yqres.2013.10.008.","productDescription":"13 p.","startPage":"305","endPage":"317","numberOfPages":"13","ipdsId":"IP-034989","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":281275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281243,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.yqres.2013.10.008"}],"country":"United States","state":"California","otherGeospatial":"Harper Lake;Mojave Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.9679,34.7902 ], [ -117.9679,35.3657 ], [ -117.038,35.3657 ], [ -117.038,34.7902 ], [ -117.9679,34.7902 ] ] ] } } ] }","volume":"81","issue":"2","noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"5355943be4b0120853e8bf9a","contributors":{"authors":[{"text":"Garcia, Anna L.","contributorId":28163,"corporation":false,"usgs":true,"family":"Garcia","given":"Anna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":488822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knott, Jeffrey R.","contributorId":81408,"corporation":false,"usgs":true,"family":"Knott","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":488823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":1215,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":488821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bright, Jordan","contributorId":106799,"corporation":false,"usgs":true,"family":"Bright","given":"Jordan","affiliations":[],"preferred":false,"id":488824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70059149,"text":"70059149 - 2014 - Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts","interactions":[],"lastModifiedDate":"2013-12-19T09:49:32","indexId":"70059149","displayToPublicDate":"2013-12-01T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts","docAbstract":"Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrologic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HE.1943-5584.0000776","usgsCitation":"Almanaseer, N., Sankarasubramanian, A., and Bales, J., 2014, Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts: Journal of Hydrologic Engineering, v. 19, no. 1, p. 87-98, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000776.","productDescription":"12 p.","startPage":"87","endPage":"98","numberOfPages":"12","ipdsId":"IP-042885","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":280427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280411,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000776"}],"country":"United States","state":"Georgia","otherGeospatial":"Flint River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.0,31.0 ], [ -85.0,33.5 ], [ -83.5,33.5 ], [ -83.5,31.0 ], [ -85.0,31.0 ] ] ] } } ] }","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6230e4b0b290850fe033","contributors":{"authors":[{"text":"Almanaseer, Naser","contributorId":13732,"corporation":false,"usgs":true,"family":"Almanaseer","given":"Naser","email":"","affiliations":[],"preferred":false,"id":487497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankarasubramanian, A.","contributorId":23062,"corporation":false,"usgs":true,"family":"Sankarasubramanian","given":"A.","affiliations":[],"preferred":false,"id":487498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bales, Jerad","contributorId":47390,"corporation":false,"usgs":true,"family":"Bales","given":"Jerad","affiliations":[],"preferred":false,"id":487499,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073409,"text":"70073409 - 2014 - HiRISE observations of new impact craters exposing Martian ground ice","interactions":[],"lastModifiedDate":"2018-11-02T10:56:31","indexId":"70073409","displayToPublicDate":"2013-12-01T09:33:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"HiRISE observations of new impact craters exposing Martian ground ice","docAbstract":"Twenty small new impact craters or clusters have been observed to excavate bright material inferred to be ice at mid and high latitudes on Mars. In the northern hemisphere, the craters are widely distributed geographically and occur at latitudes as low as 39°N. Stability modeling suggests that this ice distribution requires a long-term average atmospheric water vapor content around 25 precipitable microns, more than double the present value, which is consistent with the expected effect of recent orbital variations. Alternatively, near-surface humidity could be higher than expected for current column abundances if water vapor is not well-mixed with atmospheric CO<sub>2</sub>, or the vapor pressure at the ice table could be lower due to salts. Ice in and around the craters remains visibly bright for months to years, indicating that it is clean ice rather than ice-cemented regolith. Although some clean ice may be produced by the impact process, it is likely that the original ground ice was excess ice (exceeding dry soil pore space) in many cases. Observations of the craters suggest small-scale heterogeneities in this excess ice. The origin of such ice is uncertain. Ice lens formation by migration of thin films of liquid is most consistent with local heterogeneity in ice content and common surface boulders, but in some cases nearby thermokarst landforms suggest large amounts of excess ice that may be best explained by a degraded ice sheet.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research E: Planets","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/2013JE004482","usgsCitation":"Dundas, C.M., Byrne, S., McEwen, A.S., Mellon, M.T., Kennedy, M.R., Daubar, I., and Saper, L., 2014, HiRISE observations of new impact craters exposing Martian ground ice: Journal of Geophysical Research E: Planets, v. 119, no. 1, p. 109-127, https://doi.org/10.1002/2013JE004482.","productDescription":"19 p.","startPage":"109","endPage":"127","numberOfPages":"19","ipdsId":"IP-049885","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":281220,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JE004482"},{"id":281230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"119","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-27","publicationStatus":"PW","scienceBaseUri":"53cd6076e4b0b290850fcf0f","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":488709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":488714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":488715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mellon, Michael T.","contributorId":8603,"corporation":false,"usgs":false,"family":"Mellon","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":488710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Megan R.","contributorId":19474,"corporation":false,"usgs":true,"family":"Kennedy","given":"Megan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":488711,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daubar, Ingrid J.","contributorId":34431,"corporation":false,"usgs":true,"family":"Daubar","given":"Ingrid J.","affiliations":[],"preferred":false,"id":488713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Saper, Lee","contributorId":32085,"corporation":false,"usgs":true,"family":"Saper","given":"Lee","email":"","affiliations":[],"preferred":false,"id":488712,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70111687,"text":"70111687 - 2014 - Virtual Beach 3: user's guide","interactions":[],"lastModifiedDate":"2014-07-08T08:27:34","indexId":"70111687","displayToPublicDate":"2013-12-01T08:52:19","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"EPA/600/R-13/311","title":"Virtual Beach 3: user's guide","docAbstract":"<p>Virtual Beach version 3 (VB<sub>3</sub>) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches.  VB<sub>3</sub> is primarily designed for beach managers responsible for making decisions regarding beach closures or the issuance of swimming advisories due to pathogen contamination.  However, researchers, scientists, engineers, and students interested in studying relationships between water quality indicators and ambient environmental conditions will find VB<sub>3</sub> useful.  VB<sub>3</sub> reads input data from a text file or Excel document, assists the user in preparing the data for analysis, enables automated model selection using a wide array of possible model evaluation criteria, and provides predictions using a chosen model parameterized with new data.  With an integrated mapping component to determine the geographic orientation of the beach, the software can automatically decompose wind/current/wave speed and magnitude information into along-shore and onshore/offshore components for use in subsequent analyses.  Data can be examined using simple scatter plots to evaluate relationships between the response and independent variables (IVs).  VB<sub>3</sub> can produce interaction terms between the primary IVs, and it can also test an array of transformations to maximize the linearity of the relationship The software includes search routines for finding the \"best\" models from an array of possible choices.  Automated censoring of statistical models with highly correlated IVs occurs during the selection process.  Models can be constructed either using previously collected data or forecasted environmental information.  VB<sub>3</sub> has residual diagnostics for regression models, including automated outlier identification and removal using DFFITs or Cook's Distances.</p>","language":"English","publisher":"US EPA Office of Research and Development Ecosystems Research Division","publisherLocation":"Athens, GA","usgsCitation":"Cyterski, M., Brooks, W., Galvin, M., Wolfe, K., Carvin, R., Roddick, T., Fienen, M., and Corsi, S., 2014, Virtual Beach 3: user's guide, 86 p.","productDescription":"86 p.","numberOfPages":"88","ipdsId":"IP-053145","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":289444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289501,"type":{"id":15,"text":"Index Page"},"url":"https://www2.epa.gov/exposure-assessment-models/virtual-beach-v-30-user-guide"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53bbc188e4b084059e8bff0c","contributors":{"authors":[{"text":"Cyterski, Mike","contributorId":64161,"corporation":false,"usgs":true,"family":"Cyterski","given":"Mike","affiliations":[],"preferred":false,"id":494434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Wesley","contributorId":29738,"corporation":false,"usgs":true,"family":"Brooks","given":"Wesley","affiliations":[],"preferred":false,"id":494431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galvin, Mike","contributorId":26972,"corporation":false,"usgs":true,"family":"Galvin","given":"Mike","email":"","affiliations":[],"preferred":false,"id":494430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolfe, Kurt","contributorId":50825,"corporation":false,"usgs":true,"family":"Wolfe","given":"Kurt","email":"","affiliations":[],"preferred":false,"id":494433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carvin, Rebecca","contributorId":97820,"corporation":false,"usgs":true,"family":"Carvin","given":"Rebecca","affiliations":[],"preferred":false,"id":494437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roddick, Tonia","contributorId":40129,"corporation":false,"usgs":true,"family":"Roddick","given":"Tonia","email":"","affiliations":[],"preferred":false,"id":494432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fienen, Mike 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":85507,"corporation":false,"usgs":true,"family":"Fienen","given":"Mike","email":"","affiliations":[],"preferred":false,"id":494436,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Corsi, Steve","contributorId":68652,"corporation":false,"usgs":true,"family":"Corsi","given":"Steve","email":"","affiliations":[],"preferred":false,"id":494435,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70132431,"text":"70132431 - 2014 - Actual evapotranspiration (water use) assessment of the Colorado River Basin at the Landsat resolution using the operational simplified surface energy balance model","interactions":[],"lastModifiedDate":"2017-01-18T11:37:09","indexId":"70132431","displayToPublicDate":"2013-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Actual evapotranspiration (water use) assessment of the Colorado River Basin at the Landsat resolution using the operational simplified surface energy balance model","docAbstract":"<p>Accurately estimating consumptive water use in the Colorado River Basin (CRB) is important for assessing and managing limited water resources in the basin. Increasing water demand from various sectors may threaten long-term sustainability of the water supply in the arid southwestern United States. We have developed a first-ever basin-wide actual evapotranspiration (ET<sub>a</sub>) map of the CRB at the Landsat scale for water use assessment at the field level. We used the operational Simplified Surface Energy Balance (SSEBop) model for estimating ET<sub>a</sub> using 328 cloud-free Landsat images acquired during 2010. Our results show that cropland had the highest ET<sub>a</sub> among all land cover classes except for water. Validation using eddy covariance measured ET<sub>a</sub> showed that the SSEBop model nicely captured the variability in annual ET<sub>a</sub> with an overall R<sup>2</sup> of 0.78 and a mean bias error of about 10%. Comparison with water balance-based ETa showed good agreement (R<sup>2 </sup>= 0.85) at the sub-basin level. Though there was good correlation (R<sup>2</sup> = 0.79) between Moderate Resolution Imaging Spectroradiometer (MODIS)-based ETa (1 km spatial resolution) and Landsat-based ET<sub>a</sub> (30 m spatial resolution), the spatial distribution of MODIS-based ET<sub>a</sub> was not suitable for water use assessment at the field level. In contrast, Landsat-based ET<sub>a</sub> has good potential to be used at the field level for water management. With further validation using multiple years and sites, our methodology can be applied for regular production of ET<sub>a</sub> maps of larger areas such as the conterminous United States.</p>","language":"English","publisher":"MDPI","doi":"10.3390/rs6010233","usgsCitation":"Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., Russell L, S., and Verdin, J.P., 2014, Actual evapotranspiration (water use) assessment of the Colorado River Basin at the Landsat resolution using the operational simplified surface energy balance model: Remote Sensing, v. 6, no. 1, p. 233-256, https://doi.org/10.3390/rs6010233.","productDescription":"24 p.","startPage":"233","endPage":"256","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049231","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473330,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6010233","text":"Publisher Index Page"},{"id":296034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.06152343749999,\n              43.54854811091286\n            ],\n            [\n              -106.69921875,\n              42.65012181368025\n            ],\n            [\n              -106.12792968749999,\n              41.44272637767212\n            ],\n            [\n              -105.908203125,\n              40.613952441166596\n            ],\n            [\n              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