{"pageNumber":"94","pageRowStart":"2325","pageSize":"25","recordCount":10951,"records":[{"id":70196963,"text":"70196963 - 2017 - Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","interactions":[],"lastModifiedDate":"2018-05-15T17:03:36","indexId":"70196963","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, <i>Crassostrea virginica</i>: A meta-analysis using 40 years of monitoring data","title":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","docAbstract":"<p><span>Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster (</span><i>Crassostrea virginica</i><span>) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (&lt;25 mm), seed (25–75 mm), and sack (&gt;75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.</span></p>","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.036.0318","collaboration":"National Fish and Wildlife Foundation, Louisiana,Department of Wildlife and Fisheries, Louisiana State University","usgsCitation":"Lowe, M.R., Sehlinger, T., Soniat, T.M., and LaPeyre, M.K., 2017, Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data: Journal of Shellfish Research, v. 36, no. 3, p. 683-697, https://doi.org/10.2983/035.036.0318.","productDescription":"15 p.","startPage":"683","endPage":"697","ipdsId":"IP-088282","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94,\n              29\n            ],\n            [\n              -89,\n              29\n            ],\n            [\n              -89,\n              30.5\n            ],\n            [\n              -94,\n              30.5\n            ],\n            [\n              -94,\n              29\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2fa","contributors":{"authors":[{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":735465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sehlinger, Troy","contributorId":204922,"corporation":false,"usgs":false,"family":"Sehlinger","given":"Troy","email":"","affiliations":[],"preferred":false,"id":735466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soniat, Thomas M.","contributorId":11109,"corporation":false,"usgs":true,"family":"Soniat","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735149,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70191906,"text":"70191906 - 2017 - Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California","interactions":[],"lastModifiedDate":"2019-06-13T10:31:01","indexId":"70191906","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California","docAbstract":"<p>The U.S. Army Fort Irwin National Training Center (NTC), in the Mojave Desert, obtains all of its potable water supply from three groundwater basins (Irwin, Langford, and Bicycle) within the NTC boundaries (fig. 1; California Department of Water Resources, 2003). Because of increasing water demands at the NTC, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army, completed several studies to evaluate water resources in the developed and undeveloped groundwater basins underlying the NTC. In all of the developed basins, groundwater withdrawals exceed natural recharge, resulting in water-level declines. However, artificial recharge of treated wastewater has had some success in offsetting water-level declines in Irwin Basin. Additionally, localized water-quality changes have occurred in some parts of Irwin Basin as a result of human activities (i.e., wastewater disposal practices, landscape irrigation, and/or leaking pipes). As part of the multi-faceted NTC-wide studies, traditional datacollection methods were used and include lithological and geophysical logging at newly drilled boreholes, hydrologic data collection (i.e. water-level, water-quality, aquifer tests, wellbore flow). Because these data cover a small portion of the 1,177 square-mile (mi2 ) NTC, regional mapping, including geologic, gravity, aeromagnetic, and InSAR, also were done. In addition, ground and airborne electromagnetic surveys were completed and analyzed to provide more detailed subsurface information on a regional, base-wide scale. The traditional and regional ground and airborne data are being analyzed and will be used to help develop preliminary hydrogeologic framework and groundwater-flow models in all basins. This report is intended to provide an overview of recent water-resources and land-surface deformation studies at the NTC.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"California State University Desert Studies Center","usgsCitation":"Densmore, J.N., Dishart, J.E., Miller, D., Buesch, D.C., Ball, L.B., Bedrosian, P.A., Woolfenden, L.R., Cromwell, G., Burgess, M.K., Nawikas, J., O’Leary, D., Kjos, A., Sneed, M., and Brandt, J.T., 2017, Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California, <i>in</i> 2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone, p. 290-298.","productDescription":"9 p.","startPage":"290","endPage":"298","ipdsId":"IP-083966","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":350041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346897,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertsymposium.org/About.html"}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.00164794921875,\n              34.896068816229686\n            ],\n            [\n              -116.24633789062499,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":713607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dishart, Justine E.","contributorId":197492,"corporation":false,"usgs":false,"family":"Dishart","given":"Justine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buesch, David C. 0000-0002-4978-5027 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Center","active":true,"usgs":true}],"preferred":true,"id":713617,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kjos, Adam 0000-0002-2722-3306 adamkjos@usgs.gov","orcid":"https://orcid.org/0000-0002-2722-3306","contributorId":4130,"corporation":false,"usgs":true,"family":"Kjos","given":"Adam","email":"adamkjos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713618,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713619,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713620,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70194482,"text":"70194482 - 2017 - Case study - Dynamic pressure-limited capacity and costs of CO2 storage in the Mount Simon sandstone","interactions":[],"lastModifiedDate":"2018-12-20T14:30:03","indexId":"70194482","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"displayTitle":"Case study - Dynamic pressure-limited capacity and costs of CO<sub>2</sub> storage in the Mount Simon sandstone","title":"Case study - Dynamic pressure-limited capacity and costs of CO2 storage in the Mount Simon sandstone","docAbstract":"<p><span>Widespread deployment of carbon capture and storage (CCS) is likely necessary to be able to satisfy baseload electricity demand, to maintain diversity in the energy mix, and to achieve climate and other objectives at the lowest cost. If all of the carbon dioxide (CO<sub>2</sub>) emissions from stationary sources (such as fossil-fuel burning power plants, and other industrial plants) in the United States needed to be captured and stored, it could be possible to store only a small fraction of this CO<sub>2</sub> in oil and natural gas reservoirs, including as a result of CO<sub>2</sub> utilization for enhanced oil recovery. The vast majority would have to be stored in saline-filled reservoirs (Dahowski et al., 2005). Given a lack of long-term commercial-scale CCS projects, there is considerable uncertainty in the risks, dynamic capacity, and their cost implications for geologic storage of CO<sub>2</sub>. Pressure buildup in the storage reservoir is expected to be a primary source of risk associated with CO<sub>2</sub> storage, and could severely limit CO<sub>2</sub> injection rates (dynamic storage capacities). Most cost estimates for commercial-scale deployment of CCS estimate CO<sub>2</sub> storage costs under assumed availability of a theoretical capacity to store tens, hundreds, or even thousands of gigatons of CO<sub>2</sub>, without considering geologic heterogeneities, pressure limitations, or the time dimension. This could lead to underestimation of the costs of CO<sub>2</sub> storage (Anderson, 2017). This paper considers the impacts of pressure limitations and geologic heterogeneity on the dynamic CO<sub>2</sub> storage capacity and storage (injection) costs. In the U.S. Geological Survey (USGS)’s National Assessment of Geologic CO<sub>2</sub> Storage Resources (USGS, 2013), the mean estimate of the theoretical storage capacity in the Mount Simon Sandstone was about 94 billion metric tons of CO<sub>2</sub>. However, our results suggest that the pressure-limited capacity after 50 years of injection could be only about 4% of the theoretical geologic storage capacity in this formation. Because this is far less than emissions of CO<sub>2</sub> from stationary sources in the region around the Mount Simon Sandstone, the costs to accommodate the potential annual demand for CO<sub>2</sub> storage in this formation could be significantly greater than current estimates. Our results could have implications for how long and to what extent decision makers can expect to be able to deploy CCS before transitioning to other low- or zero-carbon energy technologies.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"35th USAEE/IAEE North American Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"USAEE","usgsCitation":"Anderson, S.T., and Jahediesfanjani, H., 2017, Case study - Dynamic pressure-limited capacity and costs of CO2 storage in the Mount Simon sandstone, <i>in</i> 35th USAEE/IAEE North American Conference, 2 p.","productDescription":"2 p.","ipdsId":"IP-088967","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":349751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349543,"type":{"id":15,"text":"Index Page"},"url":"https://www.usaee.org/USAEE2017/program_concurrent.aspx#3"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a3e","contributors":{"authors":[{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":201000,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","affiliations":[],"preferred":false,"id":724051,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70194648,"text":"70194648 - 2017 - Detrital zircon geochronology of quartzose metasedimentary rocks from parautochthonous North America, east-central Alaska","interactions":[],"lastModifiedDate":"2017-12-20T09:32:35","indexId":"70194648","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2626,"text":"Lithosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon geochronology of quartzose metasedimentary rocks from parautochthonous North America, east-central Alaska","docAbstract":"<p>We report eight new U-Pb detrital zircon ages for quartzose metasedimentary rocks from four lithotectonic units of parautochthonous North America in east-central Alaska: the Healy schist, Keevy Peak Formation, and Sheep Creek Member of the Totatlanika Schist in the northern Alaska Range, and the Butte assemblage in the northwestern Yukon-Tanana Upland. Excepting 1 of 3 samples from the Healy schist, all have dominant detrital zircon populations of 1.9–1.8 Ga and a subordinate population of 2.7–2.6 Ga. Three zircons from Totatlanika Schist yield the youngest age of ca. 780 Ma. The anomalous Healy schist sample has abundant 1.6–0.9 Ga detrital zircon, as well as populations at 2.0–1.8 Ga and 2.7–2.5 Ga that overlap the ages from the rest of our samples; it has a minimum age population of ca. 1007 Ma.</p><p>Detrital zircon age populations from all but the anomalous sample are statistically similar to those from (1) other peri-Laurentian units in east-central Alaska; (2) the Snowcap assemblage in Yukon, basement of the allochthonous Yukon-Tanana terrane; (3) Neoproterozoic to Ordovician Laurentian passive margin strata in southern British Columbia, Canada; and (4) Proterozoic Laurentian Sequence C strata of northwestern Canada. Recycling of zircon from the Paleoproterozoic Great Bear magmatic zone in the Wopmay orogen and its Archean precursors could explain both the Precambrian zircon populations and arc trace element signatures of our samples. Zircon from the anomalous Healy schist sample resembles that in Nation River Formation and Adams Argillite in eastern Alaska, suggesting recycling of detritus in those units.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/L672.1","usgsCitation":"Dusel-Bacon, C., Holm-Denoma, C.S., Jones, J.V., Aleinikoff, J.N., and Mortensen, J.K., 2017, Detrital zircon geochronology of quartzose metasedimentary rocks from parautochthonous North America, east-central Alaska: Lithosphere, v. 9, no. 6, p. 927-952, https://doi.org/10.1130/L672.1.","productDescription":"28 p.","startPage":"927","endPage":"952","ipdsId":"IP-086335","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":482054,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/l672.1","text":"Publisher Index Page"},{"id":349886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Yukon Territory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -169.013671875,\n              51.45400691005982\n            ],\n            [\n              -120.673828125,\n              51.45400691005982\n            ],\n            [\n              -120.673828125,\n              68.87935761076949\n            ],\n            [\n              -169.013671875,\n              68.87935761076949\n            ],\n            [\n              -169.013671875,\n              51.45400691005982\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"5a60faf7e4b06e28e9c22a26","contributors":{"authors":[{"text":"Dusel-Bacon, Cynthia 0000-0001-8481-739X cdusel@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-739X","contributorId":2797,"corporation":false,"usgs":true,"family":"Dusel-Bacon","given":"Cynthia","email":"cdusel@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":724737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":724739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mortensen, James K.","contributorId":96794,"corporation":false,"usgs":true,"family":"Mortensen","given":"James","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":724741,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192105,"text":"70192105 - 2017 - Connecting the Soda–Avawatz and Bristol–Granite Mountains faults with gravity andaeromagnetic data, Mojave Desert, California","interactions":[],"lastModifiedDate":"2017-12-15T13:15:56","indexId":"70192105","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Connecting the Soda–Avawatz and Bristol–Granite Mountains faults with gravity andaeromagnetic data, Mojave Desert, California","docAbstract":"<p>The Soda–Avawatz and Bristol–Granite Mountains faults are considered by some to form the northeastern margin of the eastern California shear zone yet their connectivity and extents are obscured by surficial deposits and the estimates of total right-lateral offset from geologic data range from 0 to as much as 24 km. We use gravity and recently released detailed aeromagnetic data to map strands of these faults, examine structure within the fault zones and provide estimates of right-lateral offset. Gradients in gravity and aeromagnetic data define physical property contrasts that coincide with mapped strands of the faults and allow for extension of these faults, where concealed, to indicate continuity between the Soda–Avawatz and Bristol–Granite Mountains faults. Gravity data reveal local tectonic basins west of Silver Lake, beneath Soda Lake, and southwest of the Marble Mountains that are approximately 9–15 km long, 3–5 km wide, and 1–1.5 km deep. The basins are located where the local fault traces strike more northerly than the overall fault zone strike, suggesting that these basins are transtensional (pull-apart). If the lengths of these basins can be used as a proxy for rightlateral offset, the Soda–Avawatz and Bristol–Granite Mountains faults may have up to 9–15 km of post-early Miocene offset, consistent with our offset estimates from correlative magnetic anomalies across the fault zone. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"ECSZ does it: Revisiting the Eastern California Shear Zone 2017 Desert Symposium Field Guide and Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2017 Desert Symposium","language":"English","publisher":"California State University Desert Studies Center","usgsCitation":"Langenheim, V., and Miller, D., 2017, Connecting the Soda–Avawatz and Bristol–Granite Mountains faults with gravity andaeromagnetic data, Mojave Desert, California, <i>in</i> ECSZ does it: Revisiting the Eastern California Shear Zone 2017 Desert Symposium Field Guide and Proceedings, p. 83-92.","productDescription":"10 p.","startPage":"83","endPage":"92","ipdsId":"IP-083724","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":350038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347024,"type":{"id":15,"text":"Index Page"},"url":"https://nsm.fullerton.edu/dsc/desert-studies-center-additional-information"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.5,\n              34.5\n            ],\n            [\n              -116.25,\n              34.5\n            ],\n            [\n              -116.25,\n              35.5\n            ],\n            [\n              -115.5,\n              35.5\n            ],\n            [\n              -115.5,\n              34.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a5e","contributors":{"authors":[{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714250,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196590,"text":"70196590 - 2017 - Canyons microbiology studies","interactions":[],"lastModifiedDate":"2020-08-20T17:42:02.95172","indexId":"70196590","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"BOEM 2017-060","chapter":"12","title":"Canyons microbiology studies","docAbstract":"<p>Off the eastern coast of the United States, several deep canyons cut through the continental shelf, acting like funnels to move sediment from the shelf out to the deep seafloor. Exposed rock outcrops and ledges along the walls of these canyons provide important habitat for deepsea corals and sponges. Although a few scientific expeditions have visited these canyons in the 1970s (Hecker and Blechschmidt 1979, Hecker et al. 1980), their purpose was mainly to map the contours and capture photographs of the bottom using manned submersibles and towed cameras. Our knowledge of the biodiversity in these complex ecosystems is limited; we know little about the macrofauna (e.g., fishes, crabs, sponges, and deepsea corals) and even less about the microbiota.</p><p>The research described in this report was conducted from 2011 to 2015 as part of the Bureau of Ocean Energy Management (BOEM) study, entitled “Atlantic Deepwater Canyons” study. This work used molecular and microbiological techniques to examine the microbial ecology and diversity associated with Baltimore and Norfolk canyons. Specifically, this work focused on the microbial ecology of four species of octocorals (Acanthogorgia aspera, Anthothela grandiflora, Paramuricea placomus, and Primnoa resedaeformis), the microbial diversity in sediments within and outside the canyons, and a settling plate experiment designed to characterize microbial biofilm formation on a variety of hard substrates.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Exploration and research of Mid-Atlantic deepwater hard bottom habitats and shipwrecks with emphasis on canyons and coral communities: Atlantic Deepwater Canyons Study Vol. I","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Kellogg, C.A., and Lawler, S.N., 2017, Canyons microbiology studies: OCS Study BOEM 2017-060, 31 p.","productDescription":"31 p.","startPage":"579","endPage":"609","ipdsId":"IP-079790","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":354960,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353603,"type":{"id":15,"text":"Index Page"},"url":"https://www.boem.gov/espis/5/5655.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e62fe4b060350a15d26e","contributors":{"authors":[{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":733724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawler, Stephanie N.","contributorId":149424,"corporation":false,"usgs":false,"family":"Lawler","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":17733,"text":"University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":733725,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190237,"text":"sir20175072 - 2017 - Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","interactions":[],"lastModifiedDate":"2017-12-04T10:30:46","indexId":"sir20175072","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5072","title":"Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","docAbstract":"<p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">The groundwater model described in this report is a new version of previously published steady-state numerical groundwater flow models of the Great Basin carbonate and alluvial aquifer system, and was developed in conjunction with U.S. Geological Survey studies in Parowan, Pine, and Wah Wah Valleys, Utah. This version of the model is GBCAAS v. 3.0 and supersedes previous versions. The objectives of the model for Parowan Valley were to simulate revised conceptual estimates of recharge and discharge, to estimate simulated aquifer storage properties and the amount of reduction in storage as a result of historical groundwater withdrawals, and to assess reduction in groundwater withdrawals necessary to mitigate groundwater-level declines in the basin. The objectives of the model for the area near Pine and Wah Wah Valleys were to recalibrate the model using new observations of groundwater levels and evapotranspiration of groundwater; to provide new estimates of simulated recharge, hydraulic conductivity, and interbasin flow; and to simulate the effects of proposed groundwater withdrawals on the regional flow system. Meeting these objectives required the addition of 15 transient calibration stress periods and 14 projection stress periods, aquifer storage properties, historical withdrawals in Parowan Valley, and observations of water-level changes in Parowan Valley.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Recharge in Parowan Valley and withdrawal from wells in Parowan Valley and two nearby wells in Cedar City Valley vary for each calibration stress period representing conditions from March 1940 to November 2013. Stresses, including recharge, are the same in each stress period as in the steady-state stress period for all areas outside of Parowan Valley. The model was calibrated to transient conditions only in Parowan Valley. Simulated storage properties outside of Parowan Valley were set the same as the Parowan Valley properties and are not considered calibrated.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Model observations in GBCAAS v. 3.0 are groundwater levels at wells and discharge locations; water-level changes; and discharge to springs, evapotranspiration of groundwater, rivers, and lakes. All observations in the model outside of Parowan Valley are considered to represent steady-state conditions. Composite scaled sensitivities indicate the observations of discharge to rivers and springs provide more information about model parameters in the model focus area than&nbsp;</span><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">do water-level observations. Water levels and water-level changes, however, provide the only information about specific yield and specific storage parameters and provide more information about recharge and withdrawals in Parowan Valley than any other observation group.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Comparisons of simulated water levels and measured water levels in Parowan Valley indicated that the model fits the overall trend of declining water levels and provides reasonable estimates of long-term reduction in storage and of storage changes from 2012 to 2013. The conceptual and simulated groundwater budgets for Parowan Valley from November 2012 to November 2013 are similar, with recharge of about 20,000 acre-feet and discharge of about 45,000 acre-feet. In the simulation, historical withdrawals averaging about 28,000 acre-feet per year (acre-ft/yr) cause major changes in the groundwater system in Parowan Valley. These changes include the cessation of almost all natural discharge in the valley and the long-term removal of water from storage.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">Simulated recharge in Pine Valley of 11,000 acre-ft/yr and in Wah Wah Valley of 3,200 acre-ft/yr is substantially less in GBCAAS v. 3.0 than that simulated by previous model versions. In addition, the valleys have less simulated inflow from and outflow to other hydrographic areas than were simulated by previous model versions. The effects of groundwater development in these valleys, however, are independent of the amount of water recharging in and flowing through the valleys. Groundwater withdrawals in Pine and Wah Wah Valleys will decrease groundwater storage (causing drawdown) until discharge in surrounding areas and mountain springs around the two valleys is reduced by the rate of withdrawal.&nbsp;</span></p><p><span data-mce-style=\"font-family: arial, helvetica, sans-serif;\">The model was used to estimate that reducing withdrawals in Parowan Valley from 35,000 to about 22,000 acre-ft/yr would likely stabilize groundwater levels in the valley if recharge varies as it did from about 1950 to 2012. The model was also used to demonstrate that withdrawals of 15,000 acre-ft/yr from Pine Valley and 6,500 acre-ft/yr from Wah Wah Valley could ultimately cause long-term steady-state water-level declines of about 1,900 feet near the withdrawal wells and of more than 5 feet in an area of about 10,500 square miles. The timing of drawdown and capture and the ultimate amount of drawdown are dependent on the proximity to areas of simulated natural groundwater discharge, simulated transmissivity, and simulated storage properties. The model projections are a representation of possible effects.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175072","collaboration":"Prepared in cooperation with the Utah Department of Natural Resources and the U.S. Bureau of Land Management","usgsCitation":"Brooks, L.E., 2017, Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada: U.S. Geological Survey Scientific Investigations Report 2017–5072, 77 p., 2 appendixes, https://doi.org/10.3133/sir20175072.","productDescription":"Report: x, 77 p.; Appendix Tables; Data Release","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-073792","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":349442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5072"},{"id":349441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5072/coverthb.jpg"},{"id":349505,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2017-5072.xml","text":"Data Release","description":"SIR 2017-5072","linkHelpText":"MODFLOW-LGR data sets for the Great Basin carbonate and alluvial aquifer system model version 3.0: Revisions in southwestern Utah and east central Nevada"},{"id":349444,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072_appendix1table5_6.zip","text":"Appendix 1 Tables 5 and 6","size":"400 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2017-5072"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.25,\n              37.5\n            ],\n            [\n              -111.75,\n              37.5\n            ],\n            [\n              -111.75,\n              40\n            ],\n            [\n              -114.25,\n              40\n            ],\n            [\n              -114.25,\n              37.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://ut.water.usgs.gov/about/employeedirectory.html\" data-mce-href=\"https://ut.water.usgs.gov/about/employeedirectory.html\">Director</a>,<br><a href=\"http://ut.water.usgs.gov/\" data-mce-href=\"http://ut.water.usgs.gov/\">Utah Water Science Center<br></a><a href=\"http://usgs.gov/\" data-mce-href=\"http://usgs.gov/\">U.S. Geological Survey<br></a>2329 West Orton Circle<br>Salt Lake City, UT 84119-2047</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Transient Model<br></li><li>Boundary Conditions<br></li><li>Hydraulic Properties<br></li><li>Observations Used in Model Calibration<br></li><li>Need for Recalibration<br></li><li>Calibration<br></li><li>Model Evaluation<br></li><li>Model Results<br></li><li>Model Projection<br></li><li>Model Limitations<br></li><li>Appropriate Uses of the Model<br></li><li>Summary<br></li><li>References<br></li><li>Appendixes<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-12-01","noUsgsAuthors":false,"publicationDate":"2017-12-01","publicationStatus":"PW","scienceBaseUri":"5a60fafae4b06e28e9c22a6d","contributors":{"authors":[{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":708044,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70194437,"text":"ofr20171155 - 2017 - Cobalt—Styles of deposits and the search for primary deposits","interactions":[],"lastModifiedDate":"2018-11-19T11:35:29","indexId":"ofr20171155","displayToPublicDate":"2017-11-30T17:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1155","title":"Cobalt—Styles of deposits and the search for primary deposits","docAbstract":"<p>Cobalt (Co) is a potentially critical mineral. The vast majority of cobalt is a byproduct of copper and (or) nickel production. Cobalt is increasingly used in magnets and rechargeable batteries. More than 50 percent of primary cobalt production is from the Central African Copperbelt. The Central African Copperbelt is the only sedimentary rock-hosted stratiform copper district that contains significant cobalt. Its presence may indicate significant mafic-ultramafic rocks in the local basement. The balance of primary cobalt production is from magmatic nickel-copper and nickel laterite deposits. Cobalt is present in several carbonate-hosted lead-zinc and copper districts. It is also variably present in Besshi-type volcanogenic massive sulfide and siliciclastic sedimentary rock-hosted deposits in back arc and rift environments associated with mafic-ultramafic rocks. Metasedimentary cobalt-copper-gold deposits (such as Blackbird, Idaho), iron oxide-copper-gold deposits, and the five-element vein deposits (such as Cobalt, Ontario) contain different amounts of cobalt. None of these deposit types show direct links to mafic-ultramafic rocks; the deposits may result from crustal-scale hydrothermal systems capable of leaching and transporting cobalt from great depths. Hydrothermal deposits associated with ultramafic rocks, typified by the Bou Azzer district of Morocco, represent another type of primary cobalt deposit.</p><p>In the United States, exploration for cobalt deposits may focus on magmatic nickel-copper deposits in the Archean and Proterozoic rocks of the Midwest and the east coast (Pennsylvania) and younger mafic rocks in southeastern and southern Alaska; also, possibly basement rocks in southeastern Missouri. Other potential exploration targets include—</p><ul><li>The Belt-Purcell basin of British Columbia (Canada), Idaho, Montana, and Washington for different styles of sedimentary rock-hosted cobalt deposits;</li><li>Besshi-type VMS deposits, such as the Greens Creek (Alaska) deposit and the Ducktown (Tennessee) waste and tailings; and</li><li>Known five-element vein districts in Arizona and New Mexico, as well as in the Yukon-Tanana terrane of Alaska; and hydrothermal deposits associated with ultramafic rocks along the west coast, in Alaska, and in the Appalachian Mountains.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171155","usgsCitation":"Hitzman, M.W., Bookstrom, A.A., Slack, J.F., and Zientek, M.L., 2017, Cobalt—Styles of deposits and the search for primary deposits: U.S. Geological Survey Open-File Report 2017–1155, 47 p., https://doi.org/10.3133/ofr20171155.","productDescription":"v, 47 p.","numberOfPages":"53","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091136","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"links":[{"id":349420,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1155/coverthb.jpg"},{"id":349431,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1155/ofr20171155.pdf","text":"Report","size":"1.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1155"}],"contact":"<p><a href=\"https://www.usgs.gov/science/mission-areas/energy-and-minerals?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\" data-mce-href=\"https://www.usgs.gov/science/mission-areas/energy-and-minerals?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\">Office of the Associate Director for Energy and Minerals</a><br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive<br> MS 102<br> Reston, VA 20192</p>","tableOfContents":"<ul><li>Slide Presentation</li><li>Abstract</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-11-30","noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5a60fafae4b06e28e9c22a70","contributors":{"authors":[{"text":"Hitzman, Murray W. 0000-0002-3876-0537 mhitzman@usgs.gov","orcid":"https://orcid.org/0000-0002-3876-0537","contributorId":200913,"corporation":false,"usgs":true,"family":"Hitzman","given":"Murray","email":"mhitzman@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":false,"id":723786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bookstrom, Arthur A. 0000-0003-1336-3364 abookstrom@usgs.gov","orcid":"https://orcid.org/0000-0003-1336-3364","contributorId":1542,"corporation":false,"usgs":true,"family":"Bookstrom","given":"Arthur","email":"abookstrom@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":723787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":723788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":723789,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70190624,"text":"sir20175092 - 2017 - Groundwater flux and nutrient loading in the northeast section of Bear Lake, Muskegon County, Michigan, 2015","interactions":[],"lastModifiedDate":"2017-11-30T16:58:14","indexId":"sir20175092","displayToPublicDate":"2017-11-30T11:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5092","title":"Groundwater flux and nutrient loading in the northeast section of Bear Lake, Muskegon County, Michigan, 2015","docAbstract":"<p>Bear Lake in North Muskegon, Michigan, is listed as part of the Muskegon Lake area of concern as designated by the U.S. Environmental Protection Agency. This area of concern was designated as a result of eutrophication and beneficial use impairments. On the northeast end of Bear Lake, two man-made retention ponds (Willbrandt Pond East and Willbrandt Pond West), formerly used for celery farming, may contribute nutrients to Bear Lake. Willbrandt Ponds (East and West) were previously muck fields that were actively used for celery farming from the early 1900s until 2002. The restoration and reconnection of the Willbrandt Ponds into Bear Lake prompted concerns of groundwater nutrient loading into Bear Lake. Studies done by the State of Michigan and Grand Valley State University revised initial internal phosphorus load estimates and indicated an imbalance in the phosphorus budget in Bear Lake. From June through November 2015, the U.S. Geological Survey (USGS) did an investigative study to quantify the load of nutrients from shallow groundwater around the Willbrandt Ponds in an effort to update the phosphorus budget to Bear Lake. Seven sampling locations were established, including five shallow groundwater wells and two surface-water sites, in the Willbrandt pond study area and Bear Lake. A total of 12 nutrient samples and discrete water-level measurements were collected from each site from June through November 2015. Continuous water-level data were recorded for both surface-water monitoring locations for the entire sampling period.</p><p>Water-level data indicated that Willbrandt Pond West had the highest average water-level elevation of all sites monitored, which indicated the general direction of flux is from Willbrandt Pond West to Bear Lake. Nutrient and chloride loading from Willbrandt Pond West to Bear Lake was calculated using two distinct methods: Dupuit and direct seepage methods. Shallow groundwater loading calculations were determined by using groundwater levels to first determine a flux of shallow groundwater, then nutrient concentrations to determine a load. It was determined that Willbrandt Pond East and Willbrandt Pond West contributed between 2 to 4 percent of the total annual phosphorus load to Bear Lake by way of shallow groundwater flow. Annual loads calculated for other constituents include orthophosphate (40–100 pounds per year [lb P/yr]), total nitrogen (200–830 lb/yr), chloride (12,700–32,100 lb/yr), and ammonia (130–670 lb N/yr). Study results indicated that mean groundwater and surface-water nutrient concentrations calculated in this study were higher than reported Michigan statewide values. The data collected in this study allow understanding of groundwater nutrient loading into Bear Lake in an effort to help inform future restoration and management decisions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175092","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Totten, A.R., Maurer, J.A., and Duris, J.W., 2017, Groundwater flux and nutrient loading in the northeast section of Bear Lake, Muskegon County, Michigan, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5092, 16 p., https://doi.org/10.3133/sir20175092.","productDescription":"v, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074168","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":349260,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73J3BVJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater Seepage Measurements in Northeast Section of Bear Lake, Muskegon County, Michigan, October 2015"},{"id":349259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5092/sir20175092.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5092"},{"id":349258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5092/coverthb.jpg"}],"country":"United States","state":"Michigan","county":"Muskegon County","otherGeospatial":"Bear Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.27194404602051,\n              43.25970598443754\n            ],\n            [\n              -86.25323295593262,\n              43.25970598443754\n            ],\n            [\n              -86.25323295593262,\n              43.27145609469072\n            ],\n            [\n              -86.27194404602051,\n              43.27145609469072\n            ],\n            [\n              -86.27194404602051,\n              43.25970598443754\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_mi@usgs.gov\" data-mce-href=\"mailto:dc_mi@usgs.gov\">Director</a>, <a href=\"https://mi.water.usgs.gov/\" data-mce-href=\"https://mi.water.usgs.gov/\">Upper Midwest Water Science Center</a><br> U.S. Geological Survey<br>6520 Mercantile Way<br> Suite 5<br> Lansing, MI 48911</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Description of Study Area</li><li>Methods</li><li>Results</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-11-30","noUsgsAuthors":false,"publicationDate":"2017-11-30","publicationStatus":"PW","scienceBaseUri":"5a60fafae4b06e28e9c22a72","contributors":{"authors":[{"text":"Totten, Alexander R. 0000-0003-4893-5588 atotten@usgs.gov","orcid":"https://orcid.org/0000-0003-4893-5588","contributorId":139389,"corporation":false,"usgs":true,"family":"Totten","given":"Alexander R.","email":"atotten@usgs.gov","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":710033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maurer, Jessica A. 0000-0002-3351-8565 jmaurer@usgs.gov","orcid":"https://orcid.org/0000-0002-3351-8565","contributorId":196312,"corporation":false,"usgs":true,"family":"Maurer","given":"Jessica","email":"jmaurer@usgs.gov","middleInitial":"A.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":710035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":710034,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194477,"text":"70194477 - 2017 - The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA)","interactions":[],"lastModifiedDate":"2018-11-19T11:34:54","indexId":"70194477","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA)","docAbstract":"<p><span>Black shales of the Late Devonian to Early Mississippian Bakken Formation are characterized by high concentrations of organic carbon and the hyper-enrichment (&gt;</span><span>&nbsp;</span><span>500 to 1000s of mg/kg) of V and Zn. Deposition of black shales resulted from shallow seafloor depths that promoted rapid development of euxinic conditions. Vanadium hyper-enrichments, which are unknown in modern environments, are likely the result of very high levels of dissolved H</span><sub>2</sub><span>S (~</span><span>&nbsp;</span><span>10</span><span>&nbsp;</span><span>mM) in bottom waters or sediments. Because modern hyper-enrichments of Zn are documented only in Framvaren Fjord (Norway), it is likely that the biogeochemical trigger responsible for Zn hyper-enrichment in Framvaren Fjord was also present in the Bakken basin. With Framvaren Fjord as an analogue, we propose a causal link between the activity of phototrophic sulfide oxidizing bacteria, related to the development of photic-zone euxinia, and the hyper-enrichment of Zn in black shales of the Bakken Formation.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.01.026","usgsCitation":"Scott, C., Slack, J.F., and Kelley, K.D., 2017, The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA): Chemical Geology, v. 452, p. 24-33, https://doi.org/10.1016/j.chemgeo.2017.01.026.","productDescription":"10 p.","startPage":"24","endPage":"33","ipdsId":"IP-078833","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2017.01.026","text":"Publisher Index Page"},{"id":349501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Manitoba, Montana, North Dakota, Saskatchewan, South Dakota, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108,\n              43\n            ],\n            [\n              -96,\n              43\n            ],\n            [\n              -96,\n              50\n            ],\n            [\n              -108,\n              50\n            ],\n            [\n              -108,\n              43\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"452","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a87","contributors":{"authors":[{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen Duttweiler 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":192758,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"Duttweiler","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194483,"text":"70194483 - 2017 - Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-22T16:02:15.153901","indexId":"70194483","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","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":"Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","docAbstract":"<p><span>Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination&nbsp;</span><i>R</i><sup>2</sup><span><span>&nbsp;</span>of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs9121181","usgsCitation":"Reitz, M., Senay, G., and Sanford, W.E., 2017, Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States: Remote Sensing, v. 9, no. 12, 1181, 17 p.; Data release, https://doi.org/10.3390/rs9121181.","productDescription":"1181, 17 p.; Data release","ipdsId":"IP-090961","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469292,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9121181","text":"Publisher Index Page"},{"id":349568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397955,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC02FK","text":"USGS data release","description":"USGS data release","linkHelpText":"Combined remote sensing and water-balance evapotranspiration estimates (SSEBop-WB) for the conterminous United States"}],"country":"United 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senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":724059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":724060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194476,"text":"70194476 - 2017 - Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation","interactions":[],"lastModifiedDate":"2017-11-29T10:25:30","indexId":"70194476","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation","docAbstract":"<p><span>Various geochemical records suggest that atmospheric O</span><sub>2</sub><span><span>&nbsp;</span>increased in the Ediacaran (635–541 Ma), broadly coincident with the emergence and diversification of large animals and increasing marine ecosystem complexity. Furthermore, geochemical proxies indicate that seawater sulfate levels rose at this time too, which has been hypothesized to reflect increased sulfide oxidation in marine sediments caused by sediment mixing of the newly evolved macrofauna. However, the exact timing of oxygenation is not yet understood, and there are claims for significant oxygenation prior to the Ediacaran. Furthermore, recent evidence suggests that physical mixing of sediments did not become important until the late Silurian. Here we report a multiple sulfur isotope record from a ca. 835–630 Ma succession from Svalbard, further supported by data from Proterozoic strata in Canada, Australia, Russia, and the United States, in order to investigate the timing of oxygenation. We present isotopic evidence for onset of globally significant bacterial sulfur disproportionation and reoxidative sulfur cycling following the 635 Ma Marinoan glaciation. Widespread sulfide oxidation helps to explain the observed first-order increase in seawater sulfate concentration from the earliest Ediacaran to the Precambrian-Cambrian boundary by reducing the amount of sulfur buried as pyrite. Expansion of reoxidative sulfur cycling to a global scale also indicates increasing environmental O</span><sub>2</sub><span><span>&nbsp;</span>levels. Thus, our data suggest that increasing atmospheric O</span><sub>2</sub><span><span>&nbsp;</span>levels may have played a role in the emergence of the Ediacaran macrofauna and increasing marine ecosystem complexity.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38602.1","usgsCitation":"Kunzmann, M., Bui, T.H., Crockford, P.W., Halverson, G.P., Scott, C., Lyons, T.W., and Wing, B.A., 2017, Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation: Geology, v. 45, no. 3, p. 207-210, https://doi.org/10.1130/G38602.1.","productDescription":"4 p.","startPage":"207","endPage":"210","ipdsId":"IP-076614","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":349503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, Canada, Russia, United States","volume":"45","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a8a","contributors":{"authors":[{"text":"Kunzmann, Marcus","contributorId":200984,"corporation":false,"usgs":false,"family":"Kunzmann","given":"Marcus","email":"","affiliations":[],"preferred":false,"id":724006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bui, Thi Hao","contributorId":200985,"corporation":false,"usgs":false,"family":"Bui","given":"Thi","email":"","middleInitial":"Hao","affiliations":[],"preferred":false,"id":724007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crockford, Peter W.","contributorId":200986,"corporation":false,"usgs":false,"family":"Crockford","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":724008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halverson, Galen P.","contributorId":200987,"corporation":false,"usgs":false,"family":"Halverson","given":"Galen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":724009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyons, Timothy W.","contributorId":196850,"corporation":false,"usgs":false,"family":"Lyons","given":"Timothy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":724010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wing, Boswell A.","contributorId":200989,"corporation":false,"usgs":false,"family":"Wing","given":"Boswell","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724011,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194354,"text":"70194354 - 2017 - Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","interactions":[],"lastModifiedDate":"2018-11-26T09:39:13","indexId":"70194354","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation","docAbstract":"e of this research is to identify the solid-phase sources and geochemical mechanisms of release of As in aquifers of the Des Moines Lobe glacial advance. The overarching concept is that conditions present at the aquifer-aquitard interfaces promote a suite of geochemical reactions leading to mineral alteration and release of As to groundwater. A microprobe X-ray absorption spectroscopy (lXAS) approach is developed and applied to rotosonic drill core samples to identify the solid-phase speciation of As in aquifer, aquitard, and aquifer-aquitard interface sediments. This approach addresses the low solid-phase As concentrations, as well as the fine-scale physical and chemical heterogeneity of the sediments. The spectroscopy data are analyzed using novel cosine-distance and correlation-distance hierarchical clustering for Fe 1s and As 1s lXAS datasets. The solid-phase Fe and As speciation is then interpreted using sediment and well-water chemical data to propose solid-phase As reservoirs and release mechanisms. The results confirm that in two of the three locations studied, the glacial sediment forming the aquitard is the source of As to the aquifer sediments. The results are consistent with three different As release mechanisms: (1) desorption from Fe (oxyhydr)oxides, (2) reductive dissolution of Fe (oxyhydr)oxides, and (3) oxidative dissolution of Fe sulfides. The findings confirm that glacial sediments at the interface between aquifer and aquitard are geochemically active zones for As. The diversity of As release mechanisms is consistent with the geographic heterogeneity observed in the distribution of elevated-As wells.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2017.05.018","usgsCitation":"Nicholas, S.L., Erickson, M., Woodruff, L.G., Knaeble, A.R., Marcus, M.A., Lynch, J.K., and Toner, B.M., 2017, Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation: Geochimica et Cosmochimica Acta, v. 211, p. 228-255, https://doi.org/10.1016/j.gca.2017.05.018.","productDescription":"28 p.","startPage":"228","endPage":"255","ipdsId":"IP-081306","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":469295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2017.05.018","text":"Publisher Index Page"},{"id":349424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.87695312499999,\n              41.57436130598913\n            ],\n            [\n              -89.384765625,\n              41.57436130598913\n            ],\n            [\n              -89.384765625,\n              50.51342652633956\n            ],\n            [\n              -98.87695312499999,\n              50.51342652633956\n            ],\n            [\n              -98.87695312499999,\n              41.57436130598913\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"211","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faffe4b06e28e9c22ad1","contributors":{"authors":[{"text":"Nicholas, Sarah L.","contributorId":200812,"corporation":false,"usgs":false,"family":"Nicholas","given":"Sarah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":723435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knaeble, Alan R.","contributorId":200813,"corporation":false,"usgs":false,"family":"Knaeble","given":"Alan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marcus, Matthew A.","contributorId":200814,"corporation":false,"usgs":false,"family":"Marcus","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Joshua K.","contributorId":200815,"corporation":false,"usgs":false,"family":"Lynch","given":"Joshua","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toner, Brandy M.","contributorId":200816,"corporation":false,"usgs":false,"family":"Toner","given":"Brandy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723440,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194335,"text":"70194335 - 2017 - A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","interactions":[],"lastModifiedDate":"2017-11-29T09:56:13","indexId":"70194335","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break","docAbstract":"Biogeographic breaks are often described as locations where a large number of species reach their geographic range limits. Samalga Pass, in the eastern Aleutian Archipelago, is a known biogeographic break for the spatial distribution of several species of offshore-pelagic communities, including numerous species of cold-water corals, zooplankton, fish, marine mammals, and seabirds. However, it remains unclear whether Samalga Pass also serves as a biogeographic break for nearshore benthic communities. The occurrence of biogeographic breaks across multiple habitats has not often been described. In this study, we examined if the biogeographic break for offshore-pelagic communities applies to nearshore kelp forests. To examine whether Samalga Pass serves as a biogeographic break for kelp forest communities, this study compared abundance, biomass and percent bottom cover of species associated with kelp forests on either side of the pass. We observed marked differences in kelp forest community structure, with some species reaching their geographic range limits on the opposing sides of the pass. In particular, the habitat-forming kelp Nereocystis luetkeana, and the predatory sea stars Pycnopodia helianthoides and Orthasterias koehleri all occurred on the eastern side of Samalga Pass but were not observed west of the pass. In contrast, the sea star Leptasterias camtschatica dispar was observed only on the western side of the pass. We also observed differences in overall abundance and biomass of numerous associated fish, invertebrate and macroalgal species on opposing sides of the pass. We conclude that Samalga Pass is important biogeographic break for kelp forest communities in the Aleutian Archipelago and may demark the geographic range limits of several ecologically important species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.06.007","usgsCitation":"Konar, B.H., Edwards, M.S., Bland, A., Metzger, J., Ravelo, A., Traiger, S., and Weitzman, B., 2017, A swath across the great divide: Kelp forests across the Samalga Pass biogeographic break: Continental Shelf Research, v. 143, p. 78-88, https://doi.org/10.1016/j.csr.2017.06.007.","productDescription":"11 p.","startPage":"78","endPage":"88","ipdsId":"IP-082946","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.06.007","text":"Publisher Index Page"},{"id":349445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Archipelago, Samalga Pass","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -177.5390625,\n              49.26780455063753\n            ],\n            [\n              -159.521484375,\n              49.26780455063753\n            ],\n            [\n              -159.521484375,\n              56.48676175249086\n            ],\n            [\n              -177.5390625,\n              56.48676175249086\n            ],\n            [\n              -177.5390625,\n              49.26780455063753\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"143","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ae1","contributors":{"authors":[{"text":"Konar, Brenda H. 0000-0002-8998-1612","orcid":"https://orcid.org/0000-0002-8998-1612","contributorId":200787,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":723339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Matthew S.","contributorId":200788,"corporation":false,"usgs":false,"family":"Edwards","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":723340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Aaron","contributorId":200789,"corporation":false,"usgs":false,"family":"Bland","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":723341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Metzger, Jacob","contributorId":200790,"corporation":false,"usgs":false,"family":"Metzger","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":723342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ravelo, Alexandra","contributorId":200791,"corporation":false,"usgs":false,"family":"Ravelo","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":723343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Traiger, Sarah","contributorId":200792,"corporation":false,"usgs":false,"family":"Traiger","given":"Sarah","affiliations":[],"preferred":false,"id":723344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":723338,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194341,"text":"70194341 - 2017 - Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","interactions":[],"lastModifiedDate":"2017-11-28T11:11:23","indexId":"70194341","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors","docAbstract":"Seabirds are thought to be reliable, real-time indicators of forage fish availability and the climatic and\r\nbiotic factors affecting pelagic food webs in marine ecosystems. In this study, we tested the hypothesis\r\nthat temporal trends and interannual variability in seabird indicators reflect simultaneously occurring\r\nbottom-up (climatic) and competitor (pink salmon) forcing of food webs. To test this hypothesis, we\r\nderived multivariate seabird indicators for the Bering Sea–Aleutian Island (BSAI) ecosystem and related\r\nthem to physical and biological conditions known to affect pelagic food webs in the ecosystem. We\r\nexamined covariance in the breeding biology of congeneric pelagic gulls (kittiwakes Rissa tridactyla and\r\nR. brevirostris) andauks (murres Uria aalge and U. lomvia), all of whichare abundant and well-studiedinthe\r\nBSAI. At the large ecosystem scale, kittiwake and murre breeding success and phenology (hatch dates)\r\ncovaried among congeners, so data could be combined using multivariate techniques, but patterns of\r\nresponsedifferedsubstantially betweenthe genera.Whiledata fromall sites (n = 5)inthe ecosystemcould\r\nbe combined, the south eastern Bering Sea shelf colonies (St. George, St. Paul, and Cape Peirce) provided\r\nthe strongest loadings on indicators, and hence had the strongest influence on modes of variability. The\r\nkittiwake breeding success mode of variability, dominated by biennial variation, was significantly related\r\nto both climatic factors and potential competitor interactions. The murre indicator mode was interannual\r\nand only weakly related to the climatic factors measured. The kittiwake phenology indicator mode of\r\nvariability showed multi-year periods (“stanzas”) of late or early breeding, while the murre phenology\r\nindicator showed a trend towards earlier timing. Ocean climate relationships with the kittiwake breeding\r\nsuccess indicator suggestthat early-season (winter–spring) environmental conditions and the abundance\r\nof pink salmon affect the pelagic food webs that support these seabirds in the BSAI ecosystem.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.03.013","usgsCitation":"Sydeman, W., Thompson, S.A., Piatt, J.F., García-Reyes, M., Zador, S., Williams, J.C., Romano, M., and Renner, H., 2017, Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors: Ecological Indicators, v. 78, p. 458-469, https://doi.org/10.1016/j.ecolind.2017.03.013.","productDescription":"12 p.","startPage":"458","endPage":"469","ipdsId":"IP-063143","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":349429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands, Bering Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -188.7890625,\n              50.3454604086048\n            ],\n            [\n              -156.88476562499997,\n              50.3454604086048\n            ],\n            [\n              -156.88476562499997,\n              60.54377524118842\n            ],\n            [\n              -188.7890625,\n              60.54377524118842\n            ],\n            [\n              -188.7890625,\n              50.3454604086048\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"78","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ade","contributors":{"authors":[{"text":"Sydeman, William J.","contributorId":172574,"corporation":false,"usgs":false,"family":"Sydeman","given":"William J.","affiliations":[],"preferred":false,"id":723371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":723372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":723370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Reyes, Marisol","contributorId":200914,"corporation":false,"usgs":false,"family":"García-Reyes","given":"Marisol","affiliations":[],"preferred":false,"id":723373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zador, Stephani","contributorId":60992,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","affiliations":[],"preferred":false,"id":723374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":723375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romano, Marc","contributorId":200806,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","affiliations":[],"preferred":false,"id":723376,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Renner, Heather","contributorId":200807,"corporation":false,"usgs":false,"family":"Renner","given":"Heather","affiliations":[],"preferred":false,"id":723377,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194343,"text":"70194343 - 2017 - Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","interactions":[],"lastModifiedDate":"2017-11-28T11:00:53","indexId":"70194343","displayToPublicDate":"2017-11-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2745,"text":"Mine Water and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA","docAbstract":"We investigated the impact of acid mine drainage (AMD) contamination from the Minnesota Mine, an inactive gold and silver mine, on Lion Creek, a headwater mountain stream near Empire, Colorado. The objective was to map the sources of AMD contamination, including discrete sources visible at the surface and diffuse inputs that were not readily apparent. This was achieved using geochemical sampling, in-stream and in-seep fluid electrical conductivity (EC) logging, and electrical resistivity imaging (ERI) of the subsurface. The low pH of the AMD-impacted water correlated to high fluid EC values that served as a target for the ERI. From ERI, we identified two likely sources of diffuse contamination entering the stream: (1) the subsurface extent of two seepage faces visible on the surface, and (2) rainfall runoff washing salts deposited on the streambank and in a tailings pile on the east bank of Lion Creek. Additionally, rainfall leaching through the tailings pile is a potential diffuse source of contamination if the subsurface beneath the tailings pile is hydraulically connected with the stream. In-stream fluid EC was lowest when stream discharge was highest in early summer and then increased throughout the summer as stream discharge decreased, indicating that the concentration of dissolved solids in the stream is largely controlled by mixing of groundwater and snowmelt. Total dissolved solids (TDS) load is greatest in early summer and displays a large diel signal. Identification of diffuse sources and variability in TDS load through time should allow for more targeted remediation options.","language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/s10230-017-0452-6","usgsCitation":"Johnston, A., Runkel, R.L., Navarre-Sitchler, A., and Singha, K., 2017, Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA: Mine Water and the Environment, v. 36, no. 4, p. 463-478, https://doi.org/10.1007/s10230-017-0452-6.","productDescription":"16 p.","startPage":"463","endPage":"478","ipdsId":"IP-077543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":349427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Empire","otherGeospatial":"Lion Creek","volume":"36","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-29","publicationStatus":"PW","scienceBaseUri":"5a60fb00e4b06e28e9c22ada","contributors":{"authors":[{"text":"Johnston, Allison","contributorId":200808,"corporation":false,"usgs":false,"family":"Johnston","given":"Allison","email":"","affiliations":[],"preferred":false,"id":723380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":723381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini","contributorId":76733,"corporation":false,"usgs":true,"family":"Singha","given":"Kamini","affiliations":[],"preferred":false,"id":723382,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188289,"text":"ofr20171052 - 2017 - Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","interactions":[],"lastModifiedDate":"2024-03-04T18:57:59.926401","indexId":"ofr20171052","displayToPublicDate":"2017-11-22T07:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1052","title":"Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina","docAbstract":"<p>Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.</p><p>Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.</p><p>The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (16<sup>14</sup>), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.</p><p>The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171052","usgsCitation":"Tavernia, B.G., Stanton, J.D., and Lyons, J.E., 2017, Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina: U.S. Geological Survey Open-File Report 2017–1052, 43 p., https://doi.org/10.3133/ofr20171052.","productDescription":"vii, 43 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074603","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":348384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1052/coverthb.jpg"},{"id":348385,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1052/ofr20171052.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1052"}],"country":"United States","state":"North Carolina","otherGeospatial":"Mattamuskeet National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.36459350585938,\n              35.42262976362149\n            ],\n            [\n              -76.03363037109374,\n              35.42262976362149\n            ],\n            [\n              -76.03363037109374,\n              35.59031875398378\n            ],\n            [\n              -76.36459350585938,\n              35.59031875398378\n            ],\n            [\n              -76.36459350585938,\n              35.42262976362149\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eesc\" data-mce-href=\"https://www.usgs.gov/centers/eesc\">Eastern Ecological Science Center</a><br>U.S. Geological Survey <br>12100 Beech Forest Road, Ste 4039<br>Laurel, MD 20708</p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Purpose and Scope</li><li>Objectives</li><li>Alternatives</li><li>Predictive Models</li><li>Tradeoffs Using Portfolio Analysis</li><li>Future Changes to the Decision Framework</li><li>References Cited</li><li>Appendix 1.&nbsp;Glossary of Hydroperiod Terms</li><li>Appendix 2.&nbsp;Waterfowl Habitat Modeling</li><li>Appendix 3. Building Predictive Models with Expert Judgment&nbsp;</li><li>Appendix 4.&nbsp;Expert Elicitation of Conditional Probability Tables</li><li>Appendix 5.&nbsp;Bird-Use Day Estimates</li><li>Appendix 6.&nbsp;Genetic Algorithm Approach to Portfolio Analysis&nbsp;</li><li>Appendix 7.&nbsp;Management Action Costs</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2017-11-22","noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5a60fb01e4b06e28e9c22af0","contributors":{"authors":[{"text":"Tavernia, Brian G. btavernia@usgs.gov","contributorId":5876,"corporation":false,"usgs":true,"family":"Tavernia","given":"Brian G.","email":"btavernia@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":720952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, John D.","contributorId":145798,"corporation":false,"usgs":false,"family":"Stanton","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":720953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":697140,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194215,"text":"70194215 - 2017 - Intraspecific evolutionary relationships among peregrine falcons in western North American high latitudes","interactions":[],"lastModifiedDate":"2018-08-19T10:05:56","indexId":"70194215","displayToPublicDate":"2017-11-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Intraspecific evolutionary relationships among peregrine falcons in western North American high latitudes","docAbstract":"<p><span>Subspecies relationships within the peregrine falcon (</span><i>Falco peregrinus</i><span>) have been long debated because of the polytypic nature of melanin-based plumage characteristics used in subspecies designations and potential differentiation of local subpopulations due to philopatry. In North America, understanding the evolutionary relationships among subspecies may have been further complicated by the introduction of captive bred peregrines originating from non-native stock, as part of recovery efforts associated with mid 20</span><sup>th</sup><span><span>&nbsp;</span>century population declines resulting from organochloride pollution. Alaska hosts all three nominal subspecies of North American peregrine falcons–</span><i>F</i><span>.<span>&nbsp;</span></span><i>p</i><span>.<span>&nbsp;</span></span><i>tundrius</i><span>,<span>&nbsp;</span></span><i>anatum</i><span>, and<span>&nbsp;</span></span><i>pealei</i><span>–for which distributions in Alaska are broadly associated with nesting locales within Arctic, boreal, and south coastal maritime habitats, respectively. Unlike elsewhere, populations of peregrine falcon in Alaska were not augmented by captive-bred birds during the late 20</span><sup>th</sup><span><span>&nbsp;</span>century recovery efforts. Population genetic differentiation analyses of peregrine populations in Alaska, based on sequence data from the mitochondrial DNA control region and fragment data from microsatellite loci, failed to uncover genetic distinction between populations of peregrines occupying Arctic and boreal Alaskan locales. However, the maritime subspecies,<span>&nbsp;</span></span><i>pealei</i><span>, was genetically differentiated from Arctic and boreal populations, and substructured into eastern and western populations. Levels of interpopulational gene flow between<span>&nbsp;</span></span><i>anatum</i><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>tundrius</i><span><span>&nbsp;</span>were generally higher than between<span>&nbsp;</span></span><i>pealei</i><span><span>&nbsp;</span>and either<span>&nbsp;</span></span><i>anatum</i><span><span>&nbsp;</span>or<span>&nbsp;</span></span><i>tundrius</i><span>. Estimates based on both marker types revealed gene flow between augmented Canadian populations and unaugmented Alaskan populations. While we make no attempt at formal taxonomic revision, our data suggest that peregrine falcons occupying habitats in Alaska and the North Pacific coast of North America belong to two distinct regional groupings–a coastal grouping (</span><i>pealei</i><span>) and a boreal/Arctic grouping (currently<span>&nbsp;</span></span><i>anatum</i><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>tundrius</i><span>)–each comprised of discrete populations that are variously intra-regionally connected.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188185","usgsCitation":"Talbot, S.L., Sage, G.K., Sonsthagen, S.A., Gravley, M.C., Swem, T., Williams, J.C., Longmire, J.L., Ambrose, S., Flamme, M.J., Lewis, S.B., Phillips, L.M., Anderson, C., and White, C., 2017, Intraspecific evolutionary relationships among peregrine falcons in western North American high latitudes: PLoS ONE, v. 12, no. 11, p. 1-25, https://doi.org/10.1371/journal.pone.0188185.","productDescription":"e0188185; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-070365","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469305,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188185","text":"Publisher Index Page"},{"id":438145,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18WV0","text":"USGS data release","linkHelpText":"Peregrine Falcon (Falco peregrinus) mtDNA and Microsatellite Genetic Data, Alaska, Canada and Russia, 1880-2012"},{"id":349123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -180.17578125,\n              50.17689812200107\n            ],\n            [\n              -99.84374999999999,\n              50.17689812200107\n            ],\n            [\n              -99.84374999999999,\n              72.0739114882038\n            ],\n            [\n              -180.17578125,\n              72.0739114882038\n            ],\n            [\n              -180.17578125,\n              50.17689812200107\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5a60fb0de4b06e28e9c22b69","contributors":{"authors":[{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":722723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":722724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swem, Ted","contributorId":200583,"corporation":false,"usgs":false,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":722725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Jeffrey C.","contributorId":126882,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":722726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Longmire, Jonathan L.","contributorId":35845,"corporation":false,"usgs":false,"family":"Longmire","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":722727,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ambrose, Skip","contributorId":200584,"corporation":false,"usgs":false,"family":"Ambrose","given":"Skip","email":"","affiliations":[],"preferred":false,"id":722728,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Flamme, Melanie J.","contributorId":200585,"corporation":false,"usgs":false,"family":"Flamme","given":"Melanie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722729,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lewis, Stephen B.","contributorId":200586,"corporation":false,"usgs":false,"family":"Lewis","given":"Stephen","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":722730,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Phillips, Laura M.","contributorId":49497,"corporation":false,"usgs":false,"family":"Phillips","given":"Laura","email":"","middleInitial":"M.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":722731,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Anderson, Clifford","contributorId":200587,"corporation":false,"usgs":false,"family":"Anderson","given":"Clifford","email":"","affiliations":[],"preferred":false,"id":722732,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"White, Clayton M","contributorId":200588,"corporation":false,"usgs":false,"family":"White","given":"Clayton M","affiliations":[],"preferred":false,"id":722733,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70191327,"text":"sir20175105 - 2017 - Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","interactions":[],"lastModifiedDate":"2018-11-19T10:10:32","indexId":"sir20175105","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5105","title":"Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015","docAbstract":"<p>Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.</p><p>At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.</p><p>For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.</p><p>Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded. </p><p>For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples&nbsp;from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively).&nbsp;</p><p>For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.</p><p>For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.</p><p>Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175105","collaboration":"Prepared in cooperation with Midwest Region Initiative on Natural Sources of Fracture Sand","usgsCitation":"Zelt, R.B., Hobza, C.M., Burton, B.L., Schaepe, N.J., and Piatak, Nadine, 2017, Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5105, 51 p., https://doi.org/10.3133/sir20175105.","productDescription":"Report: viii, 51 p.; Tables: 4; Data Release","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077776","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":348988,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5105"},{"id":348987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5105/coverthb2.jpg"},{"id":348989,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table4.xlsx","text":"Table 4","size":"38.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 4"},{"id":348990,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table5.xlsx","text":"Table 5","size":"26.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 5"},{"id":348991,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table6.xlsx","text":"Table 6","size":"70.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 6"},{"id":348992,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5105/sir20175105_table9.xlsx","text":"Table 9","size":"75.0","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5105 Table 9"},{"id":348993,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79W0CQB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Streambed sediment data for Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015"}],"country":"United States","state":"Nebraska, South Dakota","otherGeospatial":"Missouri River, Niobrara River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.75,\n              42.5\n            ],\n            [\n              -97.45,\n              42.5\n            ],\n            [\n              -97.45,\n              43\n            ],\n            [\n              -98.75,\n              43\n            ],\n            [\n              -98.75,\n              42.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_ne@usgs.gov\" data-mce-href=\"mailto: dc_ne@usgs.gov\">Director</a>,&nbsp;<a href=\"https://ne.water.usgs.gov\" data-mce-href=\"https://ne.water.usgs.gov\">Nebraska Water Science Center</a> <br>U.S. Geological Survey<br>5231 South 19th Street <br>Lincoln, NE 68512</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Suitability Assessment of River Delta Sediment<br></li><li>Suitability Assessment of Upstream Sources<br></li><li>Summary and Conclusions<br></li><li>References Cited<br></li><li>Glossary<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2017-11-16","noUsgsAuthors":false,"publicationDate":"2017-11-16","publicationStatus":"PW","scienceBaseUri":"5a60fb10e4b06e28e9c22b98","contributors":{"authors":[{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":138925,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany","email":"blburton@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":711937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaepe, Nathaniel J. 0000-0003-1776-7411 nschaepe@usgs.gov","orcid":"https://orcid.org/0000-0003-1776-7411","contributorId":2377,"corporation":false,"usgs":true,"family":"Schaepe","given":"Nathaniel","email":"nschaepe@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piatak, Nadine M. 0000-0002-1973-8537 npiatak@usgs.gov","orcid":"https://orcid.org/0000-0002-1973-8537","contributorId":193010,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine","email":"npiatak@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711938,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70194144,"text":"70194144 - 2017 - Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges","interactions":[],"lastModifiedDate":"2017-12-19T16:33:38","indexId":"70194144","displayToPublicDate":"2017-11-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges","docAbstract":"<p><span>Mechanisms relating offshore geologic framework to shoreline evolution are determined through geologic investigations, oceanographic deployments, and numerical modeling. Analysis of shoreline positions from the past 50 years along Fire Island, New York, a 50 km long barrier island, demonstrates a persistent undulating shape along the western half of the island. The shelf offshore of these persistent undulations is characterized with shoreface-connected sand ridges (SFCR) of a similar alongshore length scale, leading to a hypothesis that the ridges control the shoreline shape through the modification of flow. To evaluate this, a hydrodynamic model was configured to start with the US East Coast and scale down to resolve the Fire Island nearshore. The model was validated using observations along western Fire Island and buoy data, and used to compute waves, currents and sediment fluxes. To isolate the influence of the SFCR on the generation of the persistent shoreline shape, simulations were performed with a linearized nearshore bathymetry to remove alongshore transport gradients associated with shoreline shape. The model accurately predicts the scale and variation of the alongshore transport that would generate the persistent shoreline undulations. In one location, however, the ridge crest connects to the nearshore and leads to an offshore-directed transport that produces a difference in the shoreline shape. This qualitatively supports the hypothesized effect of cross-shore fluxes on coastal evolution. Alongshore flows in the nearshore during a representative storm are driven by wave breaking, vortex force, advection and pressure gradient, all of which are affected by the SFCR.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017JC012808","usgsCitation":"Safak, I., List, J.H., Warner, J., and Schwab, W.C., 2017, Persistent shoreline shape induced from offshore geologic framework: Effects of shoreface connected ridges: Journal of Geophysical Research C: Oceans, v. 122, no. 11, p. 8721-8738, https://doi.org/10.1002/2017JC012808.","productDescription":"18 p.","startPage":"8721","endPage":"8738","ipdsId":"IP-082366","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/9472","text":"Publisher Index Page"},{"id":349010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.33099365234375,\n              40.588928169693745\n            ],\n            [\n              -72.35321044921875,\n              40.588928169693745\n            ],\n            [\n              -72.35321044921875,\n              40.865756786006806\n            ],\n            [\n              -73.33099365234375,\n              40.865756786006806\n            ],\n            [\n              -73.33099365234375,\n              40.588928169693745\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"122","issue":"11","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","scienceBaseUri":"5a60fb0fe4b06e28e9c22b8e","contributors":{"authors":[{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":722352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192952,"text":"70192952 - 2017 - Design tradeoffs in long-term research for stream salamanders","interactions":[],"lastModifiedDate":"2017-11-13T09:27:30","indexId":"70192952","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2017","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":"Design tradeoffs in long-term research for stream salamanders","docAbstract":"<p>Long-term research programs can benefit from early and periodic evaluation of their ability to meet stated objectives. In particular, consideration of the spatial allocation of effort is key. We sampled 4 species of stream salamanders intensively for 2 years (2010–2011) in the Chesapeake and Ohio Canal National Historical Park, Maryland, USA to evaluate alternative distributions of sampling locations within stream networks, and then evaluated via simulation the ability of multiple survey designs to detect declines in occupancy and to estimate dynamic parameters (colonization, extinction) over 5 years for 2 species. We expected that fine-scale microhabitat variables (e.g., cobble, detritus) would be the strongest determinants of occupancy for each of the 4 species; however, we found greater support for all species for models including variables describing position within the stream network, stream size, or stream microhabitat. A monitoring design focused on headwater sections had greater power to detect changes in occupancy and the dynamic parameters in each of 3 scenarios for the dusky salamander (<i>Desmognathus fuscus</i>) and red salamander (<i>Pseudotriton ruber</i>). Results for transect length were more variable, but across all species and scenarios, 25-m transects are most suitable as a balance between maximizing detection probability and describing colonization and extinction. These results inform sampling design and provide a general framework for setting appropriate goals, effort, and duration in the initial planning stages of research programs on stream salamanders in the eastern United States.<br></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21310","usgsCitation":"Brand, A.B., and Grant, E., 2017, Design tradeoffs in long-term research for stream salamanders: Journal of Wildlife Management, v. 81, no. 8, p. 1430-1438, https://doi.org/10.1002/jwmg.21310.","productDescription":"9 p.","startPage":"1430","endPage":"1438","ipdsId":"IP-074864","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":348663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake and Ohio Canal National Historical Park","volume":"81","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-11","publicationStatus":"PW","scienceBaseUri":"5a60fb15e4b06e28e9c22c0a","contributors":{"authors":[{"text":"Brand, Adrianne B. 0000-0003-2664-0041 abrand@usgs.gov","orcid":"https://orcid.org/0000-0003-2664-0041","contributorId":3352,"corporation":false,"usgs":true,"family":"Brand","given":"Adrianne","email":"abrand@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":717419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Evan H. Campbell 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":167017,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","email":"ehgrant@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":717420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193824,"text":"70193824 - 2017 - Conservation status of an imperiled crayfish, Faxonius marchandi Hobbs, 1948 (Decapoda: Cambaridae)","interactions":[],"lastModifiedDate":"2017-11-09T11:00:07","indexId":"70193824","displayToPublicDate":"2017-11-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5546,"text":"Journal of Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Conservation status of an imperiled crayfish, Faxonius marchandi Hobbs, 1948 (Decapoda: Cambaridae)","docAbstract":"<p><span>We summarize the distribution, ecology, threats, and conservation status of&nbsp;</span><i>Faxonius marchandi</i><span><span>&nbsp;</span>(</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"CIT0023\">Hobbs, 1948</a><span>), the Mammoth Spring crayfish, a limited-range endemic species to the Spring River drainage of Missouri and Arkansas, USA. The species is known from 51 locations on lower-order perennial and intermittent streams in only the eastern portion of the drainage.<span>&nbsp;</span></span><i>Faxonius marchandi</i><span><span>&nbsp;</span>is found in larger rocky substrates in shallower, slower-velocity habitats of well-buffered, mineral-rich streams. The invading alien crayfish<span>&nbsp;</span></span><i>Faxonius neglectus chaenodactylus</i><span><span>&nbsp;</span>(</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"CIT0047\">Williams, 1952</a><span>) is the most likely threat to<span>&nbsp;</span></span><i>F</i><span>.<span>&nbsp;</span></span><i>marchandi</i><span>. These compiled data should serve as a baseline for future comparison, and facilitate discussion about future management, conservation, and research efforts.</span></p>","language":"English","publisher":"The Crustacean Society","doi":"10.1093/jcbiol/rux075","usgsCitation":"DiStefano, R.J., Magoulick, D.D., Flinders, C., and Imhoff, E., 2017, Conservation status of an imperiled crayfish, Faxonius marchandi Hobbs, 1948 (Decapoda: Cambaridae): Journal of Conservation Biology, v. 37, no. 5, p. 529-534, https://doi.org/10.1093/jcbiol/rux075.","productDescription":"6 p.","startPage":"529","endPage":"534","ipdsId":"IP-087504","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jcbiol/rux075","text":"Publisher Index Page"},{"id":348532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Spring River","volume":"37","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-23","publicationStatus":"PW","scienceBaseUri":"5a05771be4b09af898c7085c","contributors":{"authors":[{"text":"DiStefano, Robert J.","contributorId":178202,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":720613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flinders, C.A.","contributorId":6257,"corporation":false,"usgs":true,"family":"Flinders","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":721426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imhoff, Emily M.","contributorId":145444,"corporation":false,"usgs":false,"family":"Imhoff","given":"Emily M.","affiliations":[],"preferred":false,"id":721427,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193830,"text":"70193830 - 2017 - Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","interactions":[],"lastModifiedDate":"2017-11-08T11:16:08","indexId":"70193830","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","docAbstract":"<p><span>Understanding how both quality and quantity of prey affect the population dynamics of marine predators is a crucial step toward predicting the effects of environmental perturbations on population-level processes. The Junk Food Hypothesis, which posits that energetic content of prey species may influence reproductive capacity of marine top predators regardless of prey availability, has been proposed as a mechanism by which changes in prey populations could affect predator populations in high latitude systems; however, support for this hypothesis has been inconsistent across studies, and further data are needed to elucidate variation in the relative importance of prey quantity and quality, both among predator species and across ecological systems. We tested the relative importance of prey quantity and quality to nestling survival in the eastern brown pelican&nbsp;</span><i>Pelecanus occidentalis carolinensis</i><span><span>&nbsp;</span>across 9 breeding colonies in the northern Gulf of Mexico that varied in underlying availability of a key prey resource, the Gulf menhaden<span>&nbsp;</span></span><i>Brevoortia patronus</i><span>. Both feeding frequency and meal mass were significantly correlated to energy provisioning rates and nestling survival, while energy density of meals had little effect on either metric. Compared to previous results from cold-water systems, we found lower and less variable energy densities (4.4 kJ g</span><sup>-1</sup><span>, vs. 5.2 to 6.5 kJ g</span><sup>-1</sup><span><span>&nbsp;</span>in other studies) and lipid content (9% dry mass, vs. 16 to 23% in other studies) of common prey items. While Gulf menhaden was the most common prey species at all colonies, the proportion of menhaden fed to nestlings varied and was not strongly correlated to fledging success. We conclude that quantity rather than quality of prey, particularly small schooling fish, is the main driver of brown pelican reproductive success in this system, and that environmental perturbations affecting biomass, distribution, and abundance of forage fish could substantially affect brown pelican reproductive success.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12301","usgsCitation":"Lamb, J.S., Jodice, P.G., and Satge, Y.G., 2017, Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird: Marine Ecology Progress Series, v. 581, p. 149-164, https://doi.org/10.3354/meps12301.","productDescription":"16 p.","startPage":"149","endPage":"164","ipdsId":"IP-083227","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469338,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps12301","text":"Publisher Index Page"},{"id":438155,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78D6J","text":"USGS data release","linkHelpText":"Composition of diet of juvenile Brown Pelican in the northern Gulf of Mexico (2013-2015)"},{"id":348429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.525390625,\n              25.403584973186703\n            ],\n            [\n              -81.38671875,\n              25.403584973186703\n            ],\n            [\n              -81.38671875,\n              30.826780904779774\n            ],\n            [\n              -98.525390625,\n              30.826780904779774\n            ],\n            [\n              -98.525390625,\n              25.403584973186703\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"581","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f4","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":721087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193832,"text":"70193832 - 2017 - Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model","interactions":[],"lastModifiedDate":"2017-11-08T10:51:36","indexId":"70193832","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Integrating the effects of salinity on the physiology of the eastern oyster, <i>Crassostrea virginica</i>, in the northern Gulf of Mexico through a Dynamic Energy Budget model","title":"Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model","docAbstract":"<p><span>We present a Dynamic Energy Budget (DEB) model for the eastern oyster,&nbsp;</span><i>Crassostrea virginica</i><span>, which enables the inclusion of salinity as a third environmental variable, on top of the standard foodr and temperature variables. Salinity changes have various effects on the physiology of oysters, potentially altering filtration and respiration rates, and ultimately impacting growth, reproduction and mortality. We tested different hypotheses as to how to include these effects in a DEB model for<span>&nbsp;</span></span><i>C. virginica</i><span>. Specifically, we tested two potential mechanisms to explain changes in oyster shell growth (cm), tissue dry weight (g) and gonad dry weight (g) when salinity moves away from the ideal range: 1) a negative effect on filtration rate and 2) an additional somatic maintenance cost. Comparative simulations of shell growth, dry tissue biomass and dry gonad weight in two monitored sites in coastal Louisiana experiencing salinity from 0 to 28 were statistically analyzed to determine the best hypothesis. Model parameters were estimated through the covariation method, using literature data and a set of specifically designed ecophysiological experiments. The model was validated through independent field studies in estuaries along the northern Gulf of Mexico. Our results suggest that salinity impacts<span>&nbsp;</span></span><i>C. virginica</i><span>’s energy budget predominantly through effects on filtration rate. With an overwhelming number of environmental factors impacting organisms, and increasing exposure to novel and extreme conditions, the mechanistic nature of the DEB model with its ability to incorporate more than the standard food and temperature variables provides a powerful tool to verify hypotheses and predict individual organism performance across a range of conditions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2017.09.003","usgsCitation":"Lavaud, R., LaPeyre, M.K., Casas, S.M., Bacher, C., and La Peyre, J.F., 2017, Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model: Ecological Modelling, v. 363, p. 221-233, https://doi.org/10.1016/j.ecolmodel.2017.09.003.","productDescription":"13 p.","startPage":"221","endPage":"233","ipdsId":"IP-086164","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.140625,\n              24.367113562651262\n            ],\n            [\n              -79.189453125,\n              24.367113562651262\n            ],\n            [\n              -79.189453125,\n              33.063924198120645\n            ],\n            [\n              -99.140625,\n              33.063924198120645\n            ],\n            [\n              -99.140625,\n              24.367113562651262\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"363","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f1","contributors":{"authors":[{"text":"Lavaud, Romain","contributorId":200114,"corporation":false,"usgs":false,"family":"Lavaud","given":"Romain","email":"","affiliations":[],"preferred":false,"id":721040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":720625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casas, Sandra M.","contributorId":145452,"corporation":false,"usgs":false,"family":"Casas","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacher, C.","contributorId":69742,"corporation":false,"usgs":true,"family":"Bacher","given":"C.","email":"","affiliations":[],"preferred":false,"id":721042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":721043,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193726,"text":"ofr20171144 - 2017 - Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","interactions":[],"lastModifiedDate":"2017-11-08T17:33:23","indexId":"ofr20171144","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1144","title":"Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","docAbstract":"<p class=\"p1\">The Columbia River, in Washington and Oregon, and Coos Bay, in Oregon, are economically important shipping channels that are inhabited by several fishes protected under the Endangered Species Act (ESA). Maintenance of shipping channels involves dredge operations to maintain sufficient in-channel depths to allow large ships to navigate the waterways safely. Fishes entrained by dredge equipment often die or experience delayed mortality. Other potential negative effects of dredging include increased turbidity, reductions in prey resources, and the release of harmful contaminants from the dredged sediments. One species of concern is the ESA-listed green sturgeon (<i>Acipenser medirostris</i>; Southern Distinct Population Segment). In this study, we used acoustic telemetry to identify habitat use, arrival and departure timing, and the extent of upstream migration of green sturgeon in the Columbia River and Coos Bay to help inform dredge operations to minimize potential take of green sturgeon. Autonomous acoustic receivers were deployed in Coos Bay from the mouth to river kilometer (rkm) 21.6 from October 2009 through October 2010. In the Columbia River Estuary, receivers were deployed between the mouth and rkm 37.8 from April to November in 2010 and 2011. A total of 29 subadult and adult green sturgeon were tagged with temperature and pressure sensor tags and released during the study, primarily in Willapa Bay and Grays Harbor, Washington, and the Klamath River, Oregon. Green sturgeon detected during the study but released by other researchers also were included in the study.</p><p class=\"p1\">The number of tagged green sturgeon detected in the two estuaries differed markedly. In Coos Bay, only one green sturgeon was detected for about 2 hours near the estuary mouth. In the Columbia River Estuary, 9 green sturgeon were detected in 2010 and 10 fish were detected in 2011. Green sturgeon entered the Columbia River from May through October during both years, with the greatest numbers of fish being present in August and September. One green sturgeon was detected at the uppermost receiver station (rkm 37.8), but overall, the number of fish detected upriver decreased rapidly with distance from the estuary mouth. Residence times of fish that were only detected in the lower 4.8 rkm generally were less than 24 hours, but fish detected farther upriver had a median residence time greater than 10 days. Green sturgeon were widely dispersed among channel and&nbsp;non-channel habitats in the lower estuary in 2010. In 2011, the fish were more concentrated near the estuary mouth. The intensity of use, measured as the total number of fish detections at each station, generally was greatest from Point Ellice (rkm 20.1) to Rice Island (rkm 33.0) in channel and shallow shoal areas, and lowest at the stations west of Point Ellice with the exception of the area near the entrance to the Ilwaco Channel.</p><p class=\"p1\">Sensor tag data indicated that the deeper South and North Channel habitats (bottom depth ≥10 m) were used, as were the more shallow sandy shoal, shoreline, and bay habitats (bottom depth &lt;10 m). Median fish depths among fish and receiver locations ranged from 2.5 to 28.2 m below water surface (bws) and water temperatures ranged from 9.1 to 22.0 °C during late May through mid-October. In the deeper channel habitat, near the Ilwaco Channel, fish inhabited water with median temperatures ranging from 11.4 to 16.7 °C, whereas east of Point Ellice, predominantly in shallow non-channel habitats, fish inhabited water with median temperatures ranging from about 17.0 to 21.0 °C.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171144","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansel, H.C., Romine, J.G., and Perry, R.W., 2017, Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11: U.S. Geological Survey Open-File Report 2017-1144, 30 p., https://doi.org/10.3133/ofr20171144.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-088817","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":348413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1144/ofr20171144.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1144"},{"id":348412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1144/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Astoria","otherGeospatial":"Coos Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.36283111572264,\n              43.33067209551502\n            ],\n            [\n              -124.12696838378908,\n              43.33067209551502\n            ],\n            [\n              -124.12696838378908,\n              43.476591264232674\n            ],\n            [\n              -124.36283111572264,\n              43.476591264232674\n            ],\n            [\n              -124.36283111572264,\n              43.33067209551502\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.09263610839842,\n              46.14416148780093\n            ],\n            [\n              -123.61129760742186,\n              46.14416148780093\n            ],\n            [\n              -123.61129760742186,\n              46.32559414426375\n            ],\n            [\n              -124.09263610839842,\n              46.32559414426375\n            ],\n            [\n              -124.09263610839842,\n              46.14416148780093\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://wfrc.usgs.gov/\" target=\"blank\" data-mce-href=\"https://wfrc.usgs.gov/\">Western Fisheries Research Center</a><br> U.S. Geological Survey<br> 6505 NE 65th Street<br>Seattle, Washington 98115</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Study Area<br></li><li>Methods<br></li><li>Results<br></li><li>Discussion<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix A. Dates When Acoustic-Receiver Stations in the Detection Array Were Operational in the lower Columbia River Estuary, Washington and Oregon, 2010–11<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-08","noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"5a0425b0e4b0dc0b45b452fe","contributors":{"authors":[{"text":"Hansel, Hal C. 0000-0002-3537-8244 hhansel@usgs.gov","orcid":"https://orcid.org/0000-0002-3537-8244","contributorId":2887,"corporation":false,"usgs":true,"family":"Hansel","given":"Hal","email":"hhansel@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":720081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":720083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":720082,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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