We combined geophysical, geochemical, mineralogical, and geological data to evaluate the regional presence of rare earth element (REE)−bearing minerals in heavy mineral sand deposits of the southeastern U.S. Coastal Plain. We also analyzed regional differences in these data to determine probable sedimentary provenance. Analyses of heavy mineral separates covering the region show strong correlations between thorium, monazite, and xenotime, suggesting that radiometric equivalent thorium (eTh) can be used as a geophysical proxy for those REE-bearing minerals. Airborne radiometric data collected during the National Uranium Resource Evaluation (NURE) program cover the southeastern United States with line spacing varying from ∼2 to 10 km. These data show eTh highs over Cretaceous and Tertiary Coastal Plain sediments from the Cape Fear arch in North Carolina to eastern Alabama; these highs decrease with distance from the Piedmont. Quaternary sediments along the modern coasts show weaker eTh anomalies, except near coast-parallel ridges from South Carolina to northern Florida. Prominent eTh anomalies are also observed over large riverbeds and their floodplains, even north of the Cape Fear arch where surrounding areas are relatively low. These variations were verified using ground geophysical measurements and sample analyses, indicating that radiometric methods are a useful exploration tool at varying scales. Further analyses of heavy mineral separates showed regional differences, not only in concentrations of monazite, but also of rutile and staurolite, and in magnetic susceptibility. The combined properties suggest the presence of subregions where heavy mineral sediments are primarily sourced from high-grade metamorphic, low-grade metamorphic, or igneous terrains, or where they represent a mixing of these sources. Comparisons between interpreted sources of heavy mineral sands near the Fall Line and igneous and metamorphic Piedmont and Blue Ridge units showed a strong correspondence with rocks closest to the Fall Line and poor correspondence with rocks farther inland. This strongly suggests that the primary source of those heavy minerals, especially monazite, is the rocks that formed the rocky coast that was present during opening of the Atlantic Ocean, which in turn indicates the importance of coastal processes in forming heavy mineral sand concentrations. Furthermore, narrow radiometric eTh and K anomalies are associated with major rivers, indicating limited spatial influence of fluvial processes. Later coastal plain sediment deposition appears to have involved reworking of sediments, providing an “inheritance” of the rocky coast composition that persists for some distance from the Fall Line. However, this inheritance is reduced with distance, and sediments within ∼100 km of the coast in Georgia and Florida exhibit properties indicative of mixing from multiple sources.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31481.1","usgsCitation":"Shah, A.K., Bern, C.R., Van Gosen, B.S., Daniels, D.L., Benzel, W., Budahn, J.R., Ellefsen, K.J., Karst, A.T., and Davis, R., 2017, Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches: GSA Bulletin, v. 129, no. 9-10, p. 1140-1157, https://doi.org/10.1130/B31481.1.","productDescription":"18 p.","startPage":"1140","endPage":"1157","ipdsId":"IP-066088","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357278,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70189106/70189106.pdf","text":"USGS open-access version of 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cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":166816,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":702899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources 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Center","active":true,"usgs":true}],"preferred":true,"id":702906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Budahn, James R. 0000-0001-9794-8882 jbudahn@usgs.gov","orcid":"https://orcid.org/0000-0001-9794-8882","contributorId":1175,"corporation":false,"usgs":true,"family":"Budahn","given":"James","email":"jbudahn@usgs.gov","middleInitial":"R.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":702907,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science 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Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landsat-based trend analysis of lake dynamics across northern permafrost regions","docAbstract":"Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.","language":"English","publisher":"Multidisciplinary Digital Publishing Institute (MDPI)","doi":"10.3390/rs9070640","usgsCitation":"Nitze, I., Grosse, G., Jones, B.M., Arp, C.D., Ulrich, M., Federov, A., and Veremeeva, A., 2017, Landsat-based trend analysis of lake dynamics across northern permafrost regions: Remote Sensing, v. 9, no. 7, 640, 28 p., https://doi.org/10.3390/rs9070640.","productDescription":"640, 28 p.","ipdsId":"IP-087096","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":469730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9070640","text":"Publisher Index Page"},{"id":343193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.421875,\n 68.78414378041504\n ],\n [\n -140.625,\n 68.78414378041504\n ],\n [\n -140.625,\n 71.52490903732816\n ],\n [\n -162.421875,\n 71.52490903732816\n ],\n [\n -162.421875,\n 68.78414378041504\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.9609375,\n 62.75472592723178\n ],\n [\n -149.765625,\n 62.75472592723178\n ],\n [\n -149.765625,\n 66.23145747862573\n ],\n [\n -159.9609375,\n 66.23145747862573\n ],\n [\n -159.9609375,\n 62.75472592723178\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 149.765625,\n 67.87554134672945\n ],\n [\n 163.828125,\n 67.87554134672945\n ],\n [\n 163.828125,\n 71.85622888185527\n ],\n [\n 149.765625,\n 71.85622888185527\n ],\n [\n 149.765625,\n 67.87554134672945\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 135.35156249999997,\n 61.10078883158897\n ],\n [\n 155.0390625,\n 61.10078883158897\n ],\n [\n 155.0390625,\n 66.93006025862448\n ],\n [\n 135.35156249999997,\n 66.93006025862448\n ],\n [\n 135.35156249999997,\n 61.10078883158897\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-27","publicationStatus":"PW","scienceBaseUri":"595611afe4b0d1f9f0506738","contributors":{"authors":[{"text":"Nitze, 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Center","active":true,"usgs":true}],"preferred":true,"id":702948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":702951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ulrich, Mathias","contributorId":194029,"corporation":false,"usgs":false,"family":"Ulrich","given":"Mathias","email":"","affiliations":[],"preferred":false,"id":702952,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Federov, Alexander","contributorId":194027,"corporation":false,"usgs":false,"family":"Federov","given":"Alexander","email":"","affiliations":[],"preferred":false,"id":702953,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Veremeeva, Alexandra","contributorId":194028,"corporation":false,"usgs":false,"family":"Veremeeva","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":702954,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70260165,"text":"70260165 - 2017 - Relative seismic velocity variations correlate with deformation at Kilauea volcano","interactions":[],"lastModifiedDate":"2024-10-29T16:36:28.328642","indexId":"70260165","displayToPublicDate":"2017-06-28T11:31:51","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Relative seismic velocity variations correlate with deformation at Kilauea volcano","docAbstract":"Seismic noise interferometry allows the continuous and real-time measurement of relative seismic velocity through a volcanic edifice. Because seismic velocity is sensitive to the pressurization state of the system, this method is an exciting new monitoring tool at active volcanoes. Despite the potential of this tool, no studies have yet comprehensively compared velocity to other geophysical observables on a short-term time scale at a volcano over a significant length of time. We use volcanic tremor (~0.3 to 1.0 Hz) at Kīlauea as a passive source for interferometry to measure relative velocity changes with time. By cross-correlating the vertical component of day-long seismic records between ~230 station pairs, we extract coherent and temporally consistent coda wave signals with time lags of up to 120 s. Our resulting time series of relative velocity shows a remarkable correlation between relative velocity and the radial tilt record measured at Kīlauea summit, consistently correlating on a time scale of days to weeks for almost the entire study period (June 2011 to November 2015). As the summit continually deforms in deflation-inflation events, the velocity decreases and increases, respectively. Modeling of strain at Kīlauea suggests that, during inflation of the shallow magma reservoir (1 to 2 km below the surface), most of the edifice is dominated by compression—hence closing cracks and producing faster velocities—and vice versa. The excellent correlation between relative velocity and deformation in this study provides an opportunity to understand better the mechanisms causing seismic velocity changes at volcanoes, and therefore realize the potential of passive interferometry as a monitoring tool.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1700219","usgsCitation":"Donaldson, C., Caudron, C., Green, R.G., Thelen, W., and White, R.S., 2017, Relative seismic velocity variations correlate with deformation at Kilauea volcano: Science Advances, v. 3, no. 6, e1700219, 11 p., https://doi.org/10.1126/sciadv.1700219.","productDescription":"e1700219, 11 p.","ipdsId":"IP-083447","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1700219","text":"Publisher Index Page"},{"id":463355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.325723708716,\n 19.49947196116156\n ],\n [\n -155.325723708716,\n 19.284036313524524\n ],\n [\n -155.0991657820145,\n 19.284036313524524\n ],\n [\n -155.0991657820145,\n 19.49947196116156\n ],\n [\n -155.325723708716,\n 19.49947196116156\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donaldson, Clare","contributorId":345696,"corporation":false,"usgs":false,"family":"Donaldson","given":"Clare","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":917281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caudron, Corentin 0000-0002-3748-0007","orcid":"https://orcid.org/0000-0002-3748-0007","contributorId":224799,"corporation":false,"usgs":false,"family":"Caudron","given":"Corentin","email":"","affiliations":[{"id":40942,"text":"Université Grenoble Alpes, Université Savoie, ISTerre, Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":917282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Robert G.","contributorId":345697,"corporation":false,"usgs":false,"family":"Green","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":917283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Robert S","contributorId":345698,"corporation":false,"usgs":false,"family":"White","given":"Robert","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":917285,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226987,"text":"70226987 - 2017 - New methodology for computing tsunami generation by subaerial landslides: Application to the 2015 Tyndall Glacier landslide, Alaska","interactions":[],"lastModifiedDate":"2021-12-23T15:34:12.285722","indexId":"70226987","displayToPublicDate":"2017-06-28T09:27:47","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"New methodology for computing tsunami generation by subaerial landslides: Application to the 2015 Tyndall Glacier landslide, Alaska","docAbstract":"Landslide-generated tsunamis pose significant hazards and involve complex, multiphase physics that are challenging to model. We present a new methodology in which our depth-averaged two-phase model D-Claw is used to seamlessly simulate all stages of landslide dynamics as well as tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via direct longitudinal momentum transfer—a dominant physical mechanism that has not been previously addressed in this manner. To test our methodology, we used D-Claw to model a large subaerial landslide and resulting tsunami that occurred on 17 October 2015, in Taan Fjord near the terminus of Tyndall Glacier, Alaska. Modeled shoreline inundation patterns compare well with those observed in satellite imagery.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL074341","usgsCitation":"George, D.L., Iverson, R.M., and Cannon, C.M., 2017, New methodology for computing tsunami generation by subaerial landslides: Application to the 2015 Tyndall Glacier landslide, Alaska: Geophysical Research Letters, v. 44, no. 14, p. 7276-7284, https://doi.org/10.1002/2017GL074341.","productDescription":"9 p.","startPage":"7276","endPage":"7284","ipdsId":"IP-079249","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":393361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tyndall Glacier landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.21963500976562,\n 60.1524422143808\n ],\n [\n -141.1372375488281,\n 60.1524422143808\n ],\n [\n -141.1372375488281,\n 60.18796390589544\n ],\n [\n -141.21963500976562,\n 60.18796390589544\n ],\n [\n -141.21963500976562,\n 60.1524422143808\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"14","noUsgsAuthors":false,"publicationDate":"2017-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":829095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":829096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, Charles M. 0000-0003-4136-2350 ccannon@usgs.gov","orcid":"https://orcid.org/0000-0003-4136-2350","contributorId":247680,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":829097,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188361,"text":"70188361 - 2017 - Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries","interactions":[],"lastModifiedDate":"2017-07-03T10:03:08","indexId":"70188361","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries","docAbstract":"Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/1747423X.2017.1340525","usgsCitation":"Sohl, T.L., Dornbierer, J., Wika, S., Sayler, K., and Quenzer, R., 2017, Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries: Journal of Land Use Science, v. 12, no. 4, p. 197-217, https://doi.org/10.1080/1747423X.2017.1340525.","productDescription":"21 p.","startPage":"197","endPage":"217","ipdsId":"IP-074474","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":343087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-19","publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536dad","contributors":{"authors":[{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dornbierer, Jordan 0000-0003-2099-5095 jdornbierer@usgs.gov","orcid":"https://orcid.org/0000-0003-2099-5095","contributorId":167854,"corporation":false,"usgs":true,"family":"Dornbierer","given":"Jordan","email":"jdornbierer@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wika, Steve 0000-0001-9992-8973 swika@usgs.gov","orcid":"https://orcid.org/0000-0001-9992-8973","contributorId":5656,"corporation":false,"usgs":true,"family":"Wika","given":"Steve","email":"swika@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quenzer, Robert 0000-0002-1886-374X rquenzer@usgs.gov","orcid":"https://orcid.org/0000-0002-1886-374X","contributorId":4041,"corporation":false,"usgs":true,"family":"Quenzer","given":"Robert","email":"rquenzer@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188977,"text":"70188977 - 2017 - Assessment of phytoplankton resources suitable for bigheaded carps in Lake Michigan derived from remote sensing and bioenergetics","interactions":[],"lastModifiedDate":"2021-06-07T11:56:43.805323","indexId":"70188977","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of phytoplankton resources suitable for bigheaded carps in Lake Michigan derived from remote sensing and bioenergetics","docAbstract":"We used bioenergetic simulations combined with satellite-measured water temperature and estimates of algal food availability to predict the habitat suitability of Lake Michigan for adult silver carp (Hypophthalmichthys \r\nmolitrix) and bighead carp (H. nobilis). Depending on water temperature, we found that bigheaded carp require ambient algal concentrations between 1 and 7 μg chlorophyll/L or between 0.25 × 105 and 1.20 × 105 cells/mL \r\nMicrocystis to maintain body weight. When the bioenergetics model is forced with the observed average annual temperature cycle, our simulations predicted silver carp bioenergetics predicted annual weight change ranging \r\nfrom 9% weight loss to 23% gain; bighead carp ranged from 68 to 177% weight gain. Algal concentrations b4 μg chlorophyll/L and b200,000 cells/mL were below the detection limits of the remote sensing method. However, all areas with detectable algae have sufficient concentrations of algal foods for bigheaded carp weight-maintenance and growth. Those areas are predominately along the nearshore areas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.03.005","usgsCitation":"Anderson, K.R., Chapman, D., Wynne, T.T., and Paukert, C.P., 2017, Assessment of phytoplankton resources suitable for bigheaded carps in Lake Michigan derived from remote sensing and bioenergetics: Journal of Great Lakes Research, v. 43, no. 3, p. 90-99, https://doi.org/10.1016/j.jglr.2017.03.005.","productDescription":"10 p.","startPage":"90","endPage":"99","ipdsId":"IP-077126","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":343065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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Center","active":true,"usgs":true}],"preferred":true,"id":702081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":702082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynne, Tim T.","contributorId":193798,"corporation":false,"usgs":false,"family":"Wynne","given":"Tim","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":702083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig P. 0000-0002-9369-8545 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To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.
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Management decisions to address these effects (i.e., adaptation) require an understanding of the relative vulnerability of various resources to these stressors. To meet this need, the four Landscape Conservation Cooperatives along the Gulf partnered with the Gulf of Mexico Alliance to conduct this Gulf Coast Vulnerability Assessment (GCVA). Vulnerability in this context incorporates exposure and sensitivity to threats (potential impact), coupled with the adaptive capacity to mitigate those threats. Potential impact and adaptive capacity reflect natural history features of target species and ecosystems. The GCVA used an expert opinion approach to qualitatively assess the vulnerability of four ecosystems: mangrove, oyster reef, tidal emergent marsh, and barrier islands, and a suite of wildlife species that depend on them. More than 50 individuals participated in the completion of the GCVA, facilitated via Ecosystem and Species Expert Teams.
Of the species assessed, Kemp’s ridley sea turtle was identified as the most vulnerable species across the Gulf Coast. Experts identified the main threats as loss of nesting habitat to sea level rise, erosion, and urbanization. Kemp’s ridley also had an overall low adaptive capacity score due to their low genetic diversity, and higher nest site fidelity as compared to other assessed species. Tidal emergent marsh was the most vulnerable ecosystem, due in part to sea level rise and erosion. In general, avian species were more vulnerable than fish because of nesting habitat loss to sea level rise, erosion, and potential increases in storm surge.
Assessors commonly indicated a lack of information regarding impacts due to projected changes in the disturbance regime, biotic interactions, and synergistic effects in both the species and habitat assessments. Many of the assessors who focused on species also identified data gaps regarding genetic information, phenotypic plasticity, life history, and species responses to past climate change and sea level rise. Regardless of information gaps, the results from the GCVA can be used to inform Gulf-wide adaptation plans. Given the scale of climatic impacts, coordinated efforts to address Gulf-wide threats to species and ecosystems will enhance the effectiveness of management actions and also have the potential to maximize the efficacy of limited funding.
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tropical reef-lined coasts","interactions":[],"lastModifiedDate":"2017-06-28T16:58:22","indexId":"70188999","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wave dynamics and flooding on low-lying tropical reef-lined coasts","docAbstract":"Many tropical islands and coasts are lined with coral reefs. These reefs are host to valuable ecosystems that support\nabundant marine species and provide resources for fisheries and recreation. As a flood defense, reefs protect coastlines\nfrom coastal storm damage and flooding by reducing the majority of incident wave energy. However, during storm and\nlarge swell conditions, coastal wave-driven flooding and overwash still occur due to high water levels, (infra) gravity\nwaves, and/or low-frequency wave resonance. The wave and flooding effects cause erosion, damage to infrastructure,\nagricultural crops, and salinization of precious drinking water supplies. These impacts, which are likely to increase due\nto climate change and ongoing development on the islands, may cause many low-lying tropical islands and coastal\nareas to become uninhabitable before the end of the century. This paper investigates aspects of wave dynamics for the\ncase of a small island in the tropical Pacific Ocean, shows projections of flooding under climate change scenarios, and\noutlines approaches to generalize the results to other islands, including mitigation options.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings Coastal Dynamics 2017","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Dynamics 2017","conferenceDate":"June 12-16, 2017","conferenceLocation":"Helsingør, Denmark","language":"English","publisher":"Coastal Dynamics","usgsCitation":"van Dongeran, A., Storlazzi, C.D., Quataert, E., and Pearson, S., 2017, Wave dynamics and flooding on low-lying tropical reef-lined coasts, in Proceedings Coastal Dynamics 2017, Helsingør, Denmark, June 12-16, 2017, p. 654-664.","productDescription":"11 p.","startPage":"654","endPage":"664","ipdsId":"IP-085779","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343109,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://coastaldynamics2017.dk/proceedings.html"},{"id":343110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1b9e4b0d1f9f05b37a0","contributors":{"authors":[{"text":"van Dongeran, Ap","contributorId":176244,"corporation":false,"usgs":false,"family":"van Dongeran","given":"Ap","email":"","affiliations":[],"preferred":false,"id":702344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":702343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quataert, Ellen","contributorId":193834,"corporation":false,"usgs":false,"family":"Quataert","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":702345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Stuart","contributorId":193835,"corporation":false,"usgs":false,"family":"Pearson","given":"Stuart","affiliations":[],"preferred":false,"id":702346,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188998,"text":"70188998 - 2017 - Rigorously valuing the role of coral reefs in coastal protection: An example from Maui, Hawaii, U.S.A.","interactions":[],"lastModifiedDate":"2017-06-28T16:54:01","indexId":"70188998","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Rigorously valuing the role of coral reefs in coastal protection: An example from Maui, Hawaii, U.S.A.","docAbstract":"The degradation of coastal habitats, particularly coral reefs, raises risks by exposing communities to flooding hazards.\nThe protective services of these natural defenses are not assessed in the same rigorous, economic terms as artificial\ndefenses such as seawalls, and therefore often not considered in decision-making. Here we present a new methodology\nthat combines economic, ecological, and engineering tools to provide a rigorous financial valuation of the coastal\nprotection benefits of coral reefs off Maui, Hawaii, USA. We follow risk-based valuation guidelines to quantitatively\nestimate the risk reduction benefits from coral reefs in terms of annual expected benefits in economic terms. Our\nultimate goal is to identify how, where, and when coral reefs provide the most flood reduction benefits under current\nand future climates to inform reef conservation and management priorities.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of Coastal Dynamics 2017","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Dynamics 2017","conferenceDate":"June 12-16, 2017","conferenceLocation":"Helsingør, Denmark","language":"English","publisher":"Coastal Dynamics","usgsCitation":"Storlazzi, C.D., Reguero, B.G., Lowe, E., Shope, J.B., Gibbs, A.E., Beck, M., and Nickel, B.A., 2017, Rigorously valuing the role of coral reefs in coastal protection: An example from Maui, Hawaii, U.S.A., in Proceedings of Coastal Dynamics 2017, Helsingør, Denmark, June 12-16, 2017, p. 665-674.","productDescription":"10 p.","startPage":"665","endPage":"674","ipdsId":"IP-086222","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343107,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://coastaldynamics2017.dk/proceedings.html"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1b9e4b0d1f9f05b37a2","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":702329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reguero, Borja G. 0000-0001-5526-7157","orcid":"https://orcid.org/0000-0001-5526-7157","contributorId":193831,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","email":"","middleInitial":"G.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":702330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Erik","contributorId":140758,"corporation":false,"usgs":false,"family":"Lowe","given":"Erik","affiliations":[{"id":13554,"text":"USGS Pacific Coastal and Marine Science Center","active":true,"usgs":false}],"preferred":false,"id":702331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shope, James B.","contributorId":135949,"corporation":false,"usgs":false,"family":"Shope","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":702332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":702333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beck, Mike","contributorId":193832,"corporation":false,"usgs":false,"family":"Beck","given":"Mike","email":"","affiliations":[],"preferred":false,"id":702334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nickel, Barry A.","contributorId":193833,"corporation":false,"usgs":false,"family":"Nickel","given":"Barry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":702335,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188953,"text":"70188953 - 2017 - Designing a solution to enable agency-academic scientific collaboration for disasters","interactions":[],"lastModifiedDate":"2017-06-28T14:59:04","indexId":"70188953","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Designing a solution to enable agency-academic scientific collaboration for disasters","docAbstract":"As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.
","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ES-09246-220218","usgsCitation":"Mease, L.A., Gibbs-Plessl, T., Erickson, A., Ludwig, K.A., Reddy, C.M., and Lubchenco, J., 2017, Designing a solution to enable agency-academic scientific collaboration for disasters: Ecology and Society, v. 22, no. 2, Article 18; 18 p. , https://doi.org/10.5751/ES-09246-220218.","productDescription":"Article 18; 18 p. ","ipdsId":"IP-076631","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":461491,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09246-220218","text":"Publisher Index Page"},{"id":343063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publicComments":"Article 18","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1bae4b0d1f9f05b37a6","contributors":{"authors":[{"text":"Mease, Lindley A.","contributorId":193719,"corporation":false,"usgs":false,"family":"Mease","given":"Lindley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":701596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs-Plessl, Theodora","contributorId":193720,"corporation":false,"usgs":false,"family":"Gibbs-Plessl","given":"Theodora","email":"","affiliations":[],"preferred":false,"id":701597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Ashley","contributorId":193721,"corporation":false,"usgs":false,"family":"Erickson","given":"Ashley","email":"","affiliations":[],"preferred":false,"id":701598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ludwig, K. A. 0000-0002-0935-9410 kaludwig@usgs.gov","orcid":"https://orcid.org/0000-0002-0935-9410","contributorId":596,"corporation":false,"usgs":true,"family":"Ludwig","given":"K.","email":"kaludwig@usgs.gov","middleInitial":"A.","affiliations":[{"id":5059,"text":"Office of the Chief Scientist for National Hazards","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":701595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reddy, Christopher M.","contributorId":193722,"corporation":false,"usgs":false,"family":"Reddy","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":701599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lubchenco, Jane","contributorId":193723,"corporation":false,"usgs":false,"family":"Lubchenco","given":"Jane","email":"","affiliations":[],"preferred":false,"id":701600,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188694,"text":"70188694 - 2017 - Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam","interactions":[],"lastModifiedDate":"2018-03-27T11:17:35","indexId":"70188694","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam","docAbstract":"A model to compute reservoir sedimentation rates at daily timescales is presented. The model uses streamflow and sediment load data from nearby stream gauges to obtain an initial estimate of sediment yield for the reservoir’s watershed; it is then calibrated to the total deposition calculated from repeat bathymetric surveys. Long-term changes to reservoir trapping efficiency are also taken into account. The model was applied to the Fena Valley Reservoir, a water supply reservoir on the island of Guam. This reservoir became operational in 1951 and was recently surveyed in 2014. The model results show that the highest rate of deposition occurred during two typhoons (Typhoon Alice in 1953 and Typhoon Tingting in 2004); each storm decreased reservoir capacity by approximately 2–3% in only a few days. The presented model can be used to evaluate the impact of an extreme event, or it can be coupled with a watershed runoff model to evaluate potential impacts to storage capacity as a result of climate change or other hydrologic modifications.
","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)HY.1943-7900.0001344","usgsCitation":"Marineau, M.D., and Wright, S., 2017, Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam: Journal of Hydraulic Engineering, v. 143, no. 9, Article 05017003; 11 p., https://doi.org/10.1061/(ASCE)HY.1943-7900.0001344.","productDescription":"Article 05017003; 11 p.","ipdsId":"IP-082309","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1bae4b0d1f9f05b37a8","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":698945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":698946,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188985,"text":"70188985 - 2017 - Reproductive strategy, spawning induction, spawning temperatures and early life history of captive sicklefin chub Macrhybopsis meeki","interactions":[],"lastModifiedDate":"2017-07-10T14:35:39","indexId":"70188985","displayToPublicDate":"2017-06-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive strategy, spawning induction, spawning temperatures and early life history of captive sicklefin chub Macrhybopsis meeki","title":"Reproductive strategy, spawning induction, spawning temperatures and early life history of captive sicklefin chub Macrhybopsis meeki","docAbstract":"Macrhybopsis reproduction and propagule traits were studied in the laboratory using two temperature regimes and three hormone treatments to determine which methods produced the most spawns. Only sicklefin chub Macrhybopsis meeki spawned successfully although sturgeon chub Macrhybopsis gelida released unfertilized eggs. All temperature and hormone treatments produced M. meeki spawns, but two treatments had similar success rates at 44 and 43%, consisting of a constant daily temperature with no hormone added, or daily temperature fluctuations with hormone added to the water. Spawns consisted of multiple successful demersal circular swimming spawning embraces interspersed with circular swims without embraces. The most spawns observed for one female was four and on average, 327 eggs were collected after each spawn. The water-hardened eggs were semi-buoyant and non-adhesive, the first confirmation of this type of reproductive guild in the Missouri River Macrhybopsis sp. From spawn, larvae swam vertically until 123 accumulated degree days (° D) and 167° D for consumption of first food. Using average water speed and laboratory development time, the predicted drift distance for eggs and larvae could be 468–592 km in the lower Missouri River. Results from this study determined the reproductive biology and early life history of Macrhybopsis spp. and provided insight into their population dynamics in the Missouri River.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.13329","usgsCitation":"Albers, J.L., and Wildhaber, M.L., 2017, Reproductive strategy, spawning induction, spawning temperatures and early life history of captive sicklefin chub Macrhybopsis meeki: Journal of Fish Biology, v. 91, no. 1, p. 58-79, https://doi.org/10.1111/jfb.13329.","productDescription":"22 p.","startPage":"58","endPage":"79","ipdsId":"IP-064083","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":438285,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70P0X9Q","text":"USGS data release","linkHelpText":"Reproductive strategy, spawning induction, spawning temperatures and early life history of captive sicklefin chub Macrhybopsis meeki-Data"},{"id":343074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-13","publicationStatus":"PW","scienceBaseUri":"59649235e4b0d1f9f05acd44","contributors":{"authors":[{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":702247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":702248,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187863,"text":"tm7C14 - 2017 - User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments","interactions":[],"lastModifiedDate":"2019-03-14T11:09:17","indexId":"tm7C14","displayToPublicDate":"2017-06-27T11:25:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C14","title":"User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments","docAbstract":"MapMark4 is a software package that implements the probability calculations in three-part mineral resource assessments. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of this user’s guide are bundled together in R’s unit of shareable code, which is called a “package.” This user’s guide includes step-by-step instructions showing how the functions are used to carry out the probability calculations. The calculations are demonstrated using test data, which are included in the package.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer Programs in Book 7 Automated Data Processing and Computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C14","usgsCitation":"Ellefsen, K.J., 2017, User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments: U.S. Geological Survey Techniques and Methods, book 7, chap. C14, 23 p., https://doi.org/10.3133/tm7C14.","productDescription":"Report: iv, 23 p.; Installation Instructions: 4.0 kb txt; Example R Scripts: 4.0 kb; Downloadable Software Package: 856 kb; Downloadable Source Code: HTML","startPage":"1","endPage":"23","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-075749","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":438287,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96MN574","text":"USGS data release","linkHelpText":"MapMark4 Shiny: A self-contained implementation of the MapMark4 R package"},{"id":362063,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185149","text":"Scientific Investigations Report 2018-5149: ","linkHelpText":"Effect of Size-Biased Sampling on Resource Predictions from the Three-Part Method for Quantitative Mineral Resource Assessment—A Case Study of the Gold Mines in the Timmins-Kirkland Lake Area of the Abitibi Greenstone Belt, Canada"},{"id":342756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c14/coverthb.jpg"},{"id":342858,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm7C15","text":"Techniques and Methods 7C15: ","linkHelpText":"Probability calculations for three-part mineral resource assessments"},{"id":342758,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c14/InstallationInstructions.txt","text":"Installation Instructions","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C14 Installation Instructions"},{"id":342759,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c14/CalculationScripts_Gatm.R","text":"Example R Scripts for a Grade–and–Tonnage Model","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C14 Example R Scripts for a GradeandTonnage Model"},{"id":342757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c14/tm7c14.pdf","text":"Report","size":"1.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C14"},{"id":342770,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c14/CalculationScripts _Tm.R","text":"Example R Scripts for a Tonnage Model","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C14 Example R Scripts for a Tonnage Model"},{"id":342773,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c14/MapMark4_1.0.tar.gz","text":"MapMark4 Software Package","size":"856 kB","linkFileType":{"id":6,"text":"zip"},"description":"TM 7-C14 MapMark4 Software Package"},{"id":342776,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/USGS-R/MapMark4","text":"MapMark4 Source Code","description":"TM 7-C14 MapMark4 Source Code"}],"publicComments":"Chapter 14 of Section C: Computer Programs in Book 7 Automated Data Processing and Computations","contact":" Central Mineral and Environmental Resources
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Three-part mineral resource assessment is a methodology for predicting, in a specified geographic region, both the number of undiscovered mineral deposits and the amount of mineral resources in those deposits. These predictions are based on probability calculations that are performed with computer software that is newly implemented. Compared to the previous implementation, the new implementation includes new features for the probability calculations themselves and for checks of those calculations. The development of the new implementation lead to a new understanding of the probability calculations, namely the assumptions inherent in the probability calculations. Several assumptions strongly affect the mineral resource predictions, so it is crucial that they are checked during an assessment. The evaluation of the new implementation leads to new findings about the probability calculations,namely findings regarding the precision of the computations,the computation time, and the sensitivity of the calculation results to the input.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer Programs in Book 7 Automated Data Processing and Computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C15","usgsCitation":"Ellefsen, K.J., 2017, Probability calculations for three-part mineral resource assessments: U.S. Geological Survey Techniques and Methods, book 7, chap. C15, 14 p., https://doi.org/10.3133/tm7C15.","productDescription":"Report: iv, 14 p.; Calculation Scripts: 12.0 kb txt","startPage":"1","endPage":"14","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-075806","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":342784,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c15/tm7c15.pdf","text":"Report","size":"776 kB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C15"},{"id":342783,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c15/coverthb.jpg"},{"id":342786,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c15/CalculationScripts.R","text":"Calculation Scripts","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"TM 7-C15 Calculation Scripts"},{"id":342859,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm7C14","text":"Techniques and Methods 7-C14: ","linkHelpText":"User’s Guide for MapMark4—An R Package for the Probability Calculations in Three-Part Mineral Resource Assessments"},{"id":362064,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20185149","text":"Scientific Investigations Report 2018-5149: ","linkHelpText":"Effect of Size-Biased Sampling on Resource Predictions from the Three-Part Method for Quantitative Mineral Resource Assessment—A Case Study of the Gold Mines in the Timmins-Kirkland Lake Area of the Abitibi Greenstone Belt, Canada"}],"publicComments":"Chapter 15 of Section C: Computer Programs in Book 7 Automated Data Processing and Computations","contact":" Central Mineral and Environmental Resources
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Dissolved organic carbon (DOC) in lakes reduces light penetration and limits fish production in low nutrient lakes, reportedly via reduced primary and secondary production. Alternatively, DOC and light reductions could influence fish by altering their visual feeding. Previous studies report mixed effects of DOC on feeding rates of zooplanktivorous fish, but most investigators tested effects of a single concentration of DOC against clear-water, turbid, or algal treatments. We used a controlled laboratory study to quantify the effects of a DOC gradient (3–19 mg L−1) on average light climate and the zooplankton feeding rate of 3 common, north temperate fishes. Light availability, which was inversely related to DOC concentration, had a positive and linear effect on zooplankton consumption by juvenile largemouth bass (Micropterus salmoides) and bluegill (Lepomis macrochirus), explaining 22% and 28% of the variation in consumption, respectively. By contrast, zooplankton feeding rates by fathead minnow (Pimephales promelas) were best predicted by a nonlinear, negative influence of light (R2 = 0.13). In bluegill feeding trials we found a general trend for positive selection of larger zooplankton (Cladocera and Chaoboridae); however, the light climate did not influence the selection of prey type. Largemouth bass selected for larger-bodied zooplankton, with weak evidence that selectivity for large Cladocera changed from negative to neutral selection based on electivity values across the light gradient. Our results suggest that the effect of DOC on the light climate of lakes may directly influence fish zooplanktivory and that this influence may vary among fish species.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20442041.2017.1329121","usgsCitation":"Weidel, B., Baglini, K., Jones, S., Kelly, P.T., Solomon, C.T., and Zwart, J., 2017, Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory: Inland Waters, v. 7, no. 2, p. 210-217, https://doi.org/10.1080/20442041.2017.1329121.","productDescription":"8 p.","startPage":"210","endPage":"217","ipdsId":"IP-060067","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":342932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-20","publicationStatus":"PW","scienceBaseUri":"59536ea3e4b062508e3c7a59","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":700859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baglini, Katherine","contributorId":193576,"corporation":false,"usgs":false,"family":"Baglini","given":"Katherine","email":"","affiliations":[],"preferred":false,"id":700860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":700861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Patrick T.","contributorId":193577,"corporation":false,"usgs":false,"family":"Kelly","given":"Patrick","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":700862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":700863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":700864,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70185497,"text":"sir20175022B - 2017 - Field-trip guide to subaqueous volcaniclastic facies in the Ancestral Cascades arc in southern Washington State—The Ohanapecosh Formation and Wildcat Creek beds","interactions":[{"subject":{"id":70185497,"text":"sir20175022B - 2017 - Field-trip guide to subaqueous volcaniclastic facies in the Ancestral Cascades arc in southern Washington State—The Ohanapecosh Formation and Wildcat Creek beds","indexId":"sir20175022B","publicationYear":"2017","noYear":false,"chapter":"B","title":"Field-trip guide to subaqueous volcaniclastic facies in the Ancestral Cascades arc in southern Washington State—The Ohanapecosh Formation and Wildcat Creek beds"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2017-07-27T12:29:14","indexId":"sir20175022B","displayToPublicDate":"2017-06-27T00:00:00","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":"2017-5022","chapter":"B","title":"Field-trip guide to subaqueous volcaniclastic facies in the Ancestral Cascades arc in southern Washington State—The Ohanapecosh Formation and Wildcat Creek beds","docAbstract":"Partly situated in the idyllic Mount Rainier National Park, this field trip visits exceptional examples of Oligocene subaqueous volcaniclastic successions in continental basins adjacent to the Ancestral Cascades arc. The >800-m-thick Ohanapecosh Formation (32–26 Ma) and the >300-m-thick Wildcat Creek (27 Ma) beds record similar sedimentation processes from various volcanic sources. Both show evidence of below-wave-base deposition, and voluminous accumulation of volcaniclastic facies from subaqueous density currents and suspension settling. Eruption-fed facies include deposits from pyroclastic flows that crossed the shoreline, from tephra fallout over water, and from probable Surtseyan eruptions, whereas re-sedimented facies comprise subaqueous density currents and debris flow deposits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022B","usgsCitation":"Jutzeler, M., and McPhie, J., 2017, Field-trip guide to subaqueous volcaniclastic facies in the Ancestral Cascades arc in southern Washington State—The Ohanapecosh Formation and Wildcat Creek beds: U.S. Geological Survey Scientific Investigations Report 2017–5022–B, 24 p., https://doi.org/10.3133/sir20175022B.","productDescription":"vii, 24 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-076025","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":342970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/b/sir20175022b.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-B"},{"id":342969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/b/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Ancestral Cascades Arc, Ohanapecosh Formation, Wildcat Creek Beds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.62139892578125,\n 46.649436163350245\n ],\n [\n -120.9814453125,\n 46.649436163350245\n ],\n [\n -120.9814453125,\n 46.903369029728054\n ],\n [\n -121.62139892578125,\n 46.903369029728054\n ],\n [\n -121.62139892578125,\n 46.649436163350245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
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Menlo Park, CA 94025
Four species of the planktonic foraminiferal genus Streptochilus from key Neogene marine localities are documented in relation to the evolution of the Gulf of California: S. globigerus, S. latus, S. macdougallae sp. nov., and S. inglei sp. nov. Planktonic foraminiferal bioevents and strontium isotopes in the Bouse, Tirabuzón, Carmen and Ojo de Buey lithostratigraphic units constrain the local distribution range between 6 and 5.3 Ma for the last three species, whereas S. globigerus appears locally at 5.5 Ma and disappears between 3.79 and 3.46 Ma in the Imperial and Trinidad Formations. The last occurrence of Streptochilus latus, and the first and last occurrences of S. globigerus in the ancient Gulf of California are correlated with bioevents calibrated in the equatorial Pacific; therefore, they can be used as reliable local biostratigraphic markers. The presence of Streptochilus in the ancient Gulf of California seems to correlate with upwelling, in a pattern similar to that observed in the modern oceans.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marmicro.2017.05.001","usgsCitation":"Miranda Martinez, A., Carreno, A., and McDougall, K., 2017, The Neogene genus Streptochilus (Brönnimann and Resig, 1971) from the Gulf of California: Marine Micropaleontology, v. 132, p. 35-52, https://doi.org/10.1016/j.marmicro.2017.05.001.","productDescription":"18 p.","startPage":"35","endPage":"52","ipdsId":"IP-071100","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":342935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Gulf of California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.5,\n 34\n ],\n [\n -111.5,\n 18\n ],\n [\n -104,\n 19.5\n ],\n [\n -113,\n 35\n ],\n [\n -119.5,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea3e4b062508e3c7a5d","contributors":{"authors":[{"text":"Miranda Martinez, A.Y.","contributorId":193567,"corporation":false,"usgs":false,"family":"Miranda Martinez","given":"A.Y.","email":"","affiliations":[],"preferred":false,"id":700833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carreno, A.L.","contributorId":193568,"corporation":false,"usgs":false,"family":"Carreno","given":"A.L.","email":"","affiliations":[],"preferred":false,"id":700834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDougall, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":85610,"corporation":false,"usgs":true,"family":"McDougall","given":"Kristin","affiliations":[],"preferred":false,"id":700832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188891,"text":"70188891 - 2017 - The contribution of lakes to global inland fisheries harvest","interactions":[],"lastModifiedDate":"2017-08-03T08:43:25","indexId":"70188891","displayToPublicDate":"2017-06-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"The contribution of lakes to global inland fisheries harvest","docAbstract":"Freshwater ecosystems provide numerous services for communities worldwide, including irrigation, hydropower, and municipal water; however, the services provided by inland fisheries – nourishment, employment, and recreational opportunities – are often comparatively undervalued. We provide an independent estimate of global lake harvest to improve biological and socioeconomic assessments of inland fisheries. On the basis of satellite-derived estimates of chlorophyll concentration from 80,012 globally distributed lakes, lake-specific fishing effort based on human population, and output from a Bayesian hierarchical model, we estimated that the global lake fishery harvest in the year 2011 was 8.4 million tons (mt). Our calculations excluded harvests from highly productive rivers, wetlands, and very small lakes; therefore, the true cumulative global fishery harvest from all freshwater sources likely exceeded 11 mt as reported by the Food and Agriculture Organization of the United Nations (FAO). This putative underestimate by the FAO could diminish the perceived importance of inland fisheries and perpetuate decisions that adversely affect these fisheries and millions of people.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.1503","usgsCitation":"Deines, A.M., Bunnell, D., Rogers, M.W., Bennion, D., Woelmer, W., Sayers, M.J., Grimm, A.G., Shuchman, R.A., Raymer, Z.B., Brooks, C.N., Mychek-Londer, J.G., Taylor, W.W., and Beard, 2017, The contribution of lakes to global inland fisheries harvest: Frontiers in Ecology and the Environment, v. 15, no. 6, p. 293-298, https://doi.org/10.1002/fee.1503.","productDescription":"6 p.","startPage":"293","endPage":"298","ipdsId":"IP-073799","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":342933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-26","publicationStatus":"PW","scienceBaseUri":"59536ea3e4b062508e3c7a5b","contributors":{"authors":[{"text":"Deines, Andrew M.","contributorId":166920,"corporation":false,"usgs":false,"family":"Deines","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":700847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":169859,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":700846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Mark W. 0000-0001-7205-5623 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wwoelmer@usgs.gov","orcid":"https://orcid.org/0000-0001-5147-3877","contributorId":150485,"corporation":false,"usgs":true,"family":"Woelmer","given":"Whitney","email":"wwoelmer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":700850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sayers, Michael J.","contributorId":172893,"corporation":false,"usgs":false,"family":"Sayers","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":27113,"text":"Michigan Tech University","active":true,"usgs":false}],"preferred":false,"id":700851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grimm, Amanda G.","contributorId":150482,"corporation":false,"usgs":false,"family":"Grimm","given":"Amanda","email":"","middleInitial":"G.","affiliations":[{"id":16203,"text":"Michigan Technological 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The gravity cores collected within San Pablo Bay contain bioturbated laminated silts and sandy clays, whole and broken bivalve shells (mostly mussels), fossil tube structures, and fine-grained plant or wood fragments. Gravity cores from the channel wall of Carquinez Strait east of San Pablo Bay consist of sand and clay layers, whole and broken bivalve shells (less than in San Pablo Bay), trace fossil tubes, and minute fragments of plant material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171078","usgsCitation":"Woodrow, D.L., Chin, J.L., Wong, F.L., Fregoso, Theresa, Jaffe, B.E., 2017, Description of gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California: U.S. Geological Survey Open-File Report 2017–1078, 14 p., https://doi.org/10.3133/ofr20171078.","productDescription":"Report: iv, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-084096","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438291,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9PB0","text":"USGS data release","linkHelpText":"Gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California"},{"id":343001,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5849b74fe4b071492e42db02","text":"USGS data 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A broad study of zircons from plutonic rocks of the Sawatch and Mosquito ranges of west-central Colorado (U.S.A.) was undertaken to significantly refine the magmatic chronology and chemistry of this under-studied region of the Colorado province. This region was chosen because it lies just to the north of the suspected arc-related Gunnison-Salida volcano-plutonic terrane, which has been the subject of many recent investigations—and whose origin is still debated. Our new results provide important insights into the processes active during Proterozoic crustal evolution in this region, and they have important ramifications for broader-scope crustal evolution models for southwestern North America.
Twenty-four new U-Pb ages and sequentially acquired rare-earth element (REE), U, Th, and Hf contents of zircon have been determined using the sensitive high-resolution ion microprobe-reverse geometry (SHRIMP-RG). These zircon geochemistry data, in conjunction with whole-rock major- and trace-element data, provide important insights into zircon crystallization and melt fractionation, and they help to further constrain the tectonic environment of magma generation.
Our detailed zircon and whole-rock data support the following three interpretations:
(1) The Roosevelt Granite in the southern Sawatch Range was the oldest rock dated at 1,766 ± 7 Ma, and it intruded various metavolcanic and metasedimentary rocks. Geochemistry of both whole-rock and zircon supports the contention that this granite was produced in a magmatic arc environment and, therefore, is likely an extension of the older Dubois Greenstone Belt of the Gunnison Igneous Complex (GIC) and the Needle Mountains (1,770–1,755 Ma). Rocks of the younger Cochetopa succession of the GIC, the Salida Greenstone Belt, and the Sangre de Cristo Mountains (1,740–1,725 Ma) were not found in the Sawatch and Mosquito ranges. This observation strongly suggests that the northern edge of the Gunnison-Salida arc terrane underlies the southern portion of the Sawatch and Mosquito ranges.
(2) Calc-alkalic to alkali-calcic magmas intruded this region approximately 55 m.y. after the Roosevelt Granite with emplacement of pre-deformational plutons at ca. 1,710 Ma (e.g., Henry Mountain Granite and diorite of Denny Creek), and this continued for at least 30 m.y., ending with emplacement of post-deformational plutons at ca. 1,680 Ma (e.g., Kroenke Granodiorite, granite of Fairview Peak, and syenite of Mount Yale). The timing of deformation can be constrained to sometime after intrusion of the diorite of Denny Creek and likely before the emplacement of the undeformed granite of Fairview Peak. Geochemistry of both whole-rock and zircon indicates that the older group of ca. 1,710-Ma plutons formed at shallower depths, and then they intruded the younger group of more deeply generated, commonly peraluminous and sodic plutons. Although absent in the Sawatch and Mosquito ranges, Mazatzal-age (ca. 1,680–1,620 Ma) plutonic rocks are present regionally. Inherited zircon components of Mazatzal-age were found as cores in some 1.4-Ga Sawatch and Mosquito Range zircons, indicating the likelihood of a relatively local source. These combined data suggest the possibility that all were produced within a continental-margin magmatic arc created as a result of southward-migrating (slab rollback?), north-dipping subduction to the south of the region.
(3) Widespread Mesoproterozoic plutonism—with emplacement at various depths and exhibiting bimodal geochemistry—is recognized in 16 different samples. An older group of predominantly peraluminous, yet magnesian granitoids (e.g., granodiorite of Sayers, granite of Taylor River, and the St. Kevin Granite) were emplaced between ca. 1,450 and 1,425 Ma. These geochemical parameters suggest moderate degrees of partial melting in a low-pressure environment. Three younger metaluminous, but ferroan plutons (diorite of Grottos, diorite of Mount Elbert, and granodiorite of Mount Harvard), probably represent a final magmatic pulse at ca. 1,416 Ma.
A comprehensive treatment of zircon REE and whole-rock trace-element behavior from Proterozoic rocks is scarce. Discriminant U/Yb versus Y diagrams using zircon data show that the Sawatch and Mosquito plutons are of continental origin, not oceanic. Additional bivariate diagrams incorporating cation ratio combinations of Gd, Ce, Yb, U, Th, Hf, and Eu offer refined insight into differences in fractionation trends and depth of magma generation for the various plutons. These interpretations, on the basis of zircon trace-element data, are mirrored in the whole-rock geochemistry data.
","language":"English","publisher":"GeoScienceWorld","doi":"10.24872/rmgjournal.52.1.17","usgsCitation":"Moscati, R.J., Premo, W.R., Dewitt, E., and Wooden, J.L., 2017, U-Pb ages and geochemistry of zircon from Proterozoic plutons of the Sawatch and Mosquito ranges, Colorado, U.S.A.: Implications for crustal growth of the central Colorado province: Rocky Mountain Geology, v. 52, no. 1, p. 17-106, https://doi.org/10.24872/rmgjournal.52.1.17.","productDescription":"90 p.","startPage":"17","endPage":"106","ipdsId":"IP-054984","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":342965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Mosquito Range, Sawatch Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 39.5\n ],\n [\n -107,\n 38.7\n ],\n [\n -107.8,\n 38.7\n ],\n [\n -107.8,\n 38.0\n ],\n [\n -105.8,\n 38.0\n ],\n [\n -105.8,\n 39.5\n ],\n [\n -107,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-26","publicationStatus":"PW","scienceBaseUri":"59536ea2e4b062508e3c7a57","contributors":{"authors":[{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":700889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Premo, Wayne R. 0000-0001-9904-4801 wpremo@usgs.gov","orcid":"https://orcid.org/0000-0001-9904-4801","contributorId":1697,"corporation":false,"usgs":true,"family":"Premo","given":"Wayne","email":"wpremo@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":700890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dewitt, Ed edewitt@usgs.gov","contributorId":193586,"corporation":false,"usgs":true,"family":"Dewitt","given":"Ed","email":"edewitt@usgs.gov","affiliations":[],"preferred":true,"id":700891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wooden, Joseph L.","contributorId":193587,"corporation":false,"usgs":false,"family":"Wooden","given":"Joseph","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":700892,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188916,"text":"70188916 - 2017 - Essential information: Uncertainty and optimal control of Ebola outbreaks","interactions":[],"lastModifiedDate":"2017-06-27T14:56:55","indexId":"70188916","displayToPublicDate":"2017-06-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Essential information: Uncertainty and optimal control of Ebola outbreaks","docAbstract":"Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1617482114","usgsCitation":"Li, S., Bjornstad, O., Ferrari, M., Mummah, R., Runge, M.C., Fonnesbeck, C.J., Tildesley, M., Probert, W., and Shea, K., 2017, Essential information: Uncertainty and optimal control of Ebola outbreaks: Proceedings of the National Academy of Sciences of the United States of America, v. 114, no. 22, p. 5659-5664, https://doi.org/10.1073/pnas.1617482114.","productDescription":"6 p.","startPage":"5659","endPage":"5664","ipdsId":"IP-082199","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://europepmc.org/articles/PMC5465899","text":"Publisher Index Page"},{"id":343011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"22","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-15","publicationStatus":"PW","scienceBaseUri":"59536ea1e4b062508e3c7a53","contributors":{"authors":[{"text":"Li, Shou-Li","contributorId":193644,"corporation":false,"usgs":false,"family":"Li","given":"Shou-Li","email":"","affiliations":[],"preferred":false,"id":701211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bjornstad, Ottar","contributorId":193645,"corporation":false,"usgs":false,"family":"Bjornstad","given":"Ottar","affiliations":[],"preferred":false,"id":701212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrari, Matthew J.","contributorId":67082,"corporation":false,"usgs":true,"family":"Ferrari","given":"Matthew J.","affiliations":[],"preferred":false,"id":701241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mummah, Riley","contributorId":193663,"corporation":false,"usgs":false,"family":"Mummah","given":"Riley","affiliations":[],"preferred":false,"id":701242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":701243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fonnesbeck, Christopher J.","contributorId":83047,"corporation":false,"usgs":true,"family":"Fonnesbeck","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":701244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tildesley, Michael J.","contributorId":100772,"corporation":false,"usgs":true,"family":"Tildesley","given":"Michael J.","affiliations":[],"preferred":false,"id":701245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Probert, William J. M.","contributorId":44759,"corporation":false,"usgs":false,"family":"Probert","given":"William J. M.","affiliations":[],"preferred":false,"id":701246,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shea, Katriona 0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":701247,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70188918,"text":"70188918 - 2017 - Trace element contamination in feather and tissue samples from Anna’s hummingbirds","interactions":[],"lastModifiedDate":"2017-07-02T08:50:47","indexId":"70188918","displayToPublicDate":"2017-06-27T00:00:00","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":"Trace element contamination in feather and tissue samples from Anna’s hummingbirds","docAbstract":"Trace element contamination (17 elements; Be, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Ba, Hg, Tl, and Pb) of live (feather samples only) and deceased (feather and tissue samples) Anna's hummingbirds (Calypte anna) was evaluated. Samples were analyzed using inductively coupled plasma-mass spectrometry (ICP-MS; 17 elements) and atomic absorption spectrophotometry (Hg only). Mean plus one standard deviation (SD) was considered the benchmark, and concentrations above the mean + 1 SD were considered elevated above normal. Contour feathers were sampled from live birds of varying age, sex, and California locations. In order to reduce thermal impacts, minimal feathers were taken from live birds, therefore a novel method was developed for preparation of low mass feather samples for ICP-MS analysis. The study found that the novel feather preparation method enabled small mass feather samples to be analyzed for trace elements using ICP-MS. For feather samples from live birds, all trace elements, with the exception of beryllium, had concentrations above the mean + 1 SD. Important risk factors for elevated trace element concentrations in feathers of live birds were age for iron, zinc, and arsenic, and location for iron, manganese, zinc, and selenium. For samples from deceased birds, ICP-MS results from body and tail feathers were correlated for Fe, Zn, and Pb, and feather concentrations were correlated with renal (Fe, Zn, Pb) or hepatic (Hg) tissue concentrations. Results for AA spectrophotometry analyzed samples from deceased birds further supported the ICP-MS findings where a strong correlation between mercury concentrations in feather and tissue (pectoral muscle) samples was found. These study results support that sampling feathers from live free-ranging hummingbirds might be a useful, non-lethal sampling method for evaluating trace element exposure and provides a sampling alternative since their small body size limits traditional sampling of blood and tissues. The results from this study provide a benchmark for the distribution of trace element concentrations in feather and tissue samples from hummingbirds and suggests a reference mark for exceeding normal. Lastly, pollinating avian species are minimally represented in the literature as bioindicators for environmental trace element contamination. Given that trace elements can move through food chains by a variety of routes, our study indicates that hummingbirds are possible bioindicators of environmental trace element contamination.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2017.04.053","usgsCitation":"Mikoni, N.A., Poppenga, R.H., Ackerman, J., Foley, J.E., Hazlehurst, J., Purdin, G., Aston, L., Hargrave, S., Jelks, K., and Tell, L.A., 2017, Trace element contamination in feather and tissue samples from Anna’s hummingbirds: Ecological Indicators, v. 80, p. 96-105, https://doi.org/10.1016/j.ecolind.2017.04.053.","productDescription":"10 p.","startPage":"96","endPage":"105","ipdsId":"IP-082206","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438289,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75H7DG7","text":"USGS data release","linkHelpText":"Mercury contamination in Annas hummingbirds"},{"id":343012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea0e4b062508e3c7a51","contributors":{"authors":[{"text":"Mikoni, Nicole A.","contributorId":193647,"corporation":false,"usgs":false,"family":"Mikoni","given":"Nicole","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":701216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppenga, Robert H.","contributorId":76063,"corporation":false,"usgs":false,"family":"Poppenga","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":701217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":701215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foley, Janet E.","contributorId":148029,"corporation":false,"usgs":false,"family":"Foley","given":"Janet","email":"","middleInitial":"E.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":701218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hazlehurst, Jenny","contributorId":193648,"corporation":false,"usgs":false,"family":"Hazlehurst","given":"Jenny","email":"","affiliations":[],"preferred":false,"id":701219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Purdin, Guthrum","contributorId":193649,"corporation":false,"usgs":false,"family":"Purdin","given":"Guthrum","email":"","affiliations":[],"preferred":false,"id":701220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aston, Linda","contributorId":193650,"corporation":false,"usgs":false,"family":"Aston","given":"Linda","email":"","affiliations":[],"preferred":false,"id":701221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hargrave, Sabine","contributorId":193651,"corporation":false,"usgs":false,"family":"Hargrave","given":"Sabine","email":"","affiliations":[],"preferred":false,"id":701222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jelks, Karen","contributorId":193652,"corporation":false,"usgs":false,"family":"Jelks","given":"Karen","email":"","affiliations":[],"preferred":false,"id":701223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tell, Lisa A.","contributorId":193653,"corporation":false,"usgs":false,"family":"Tell","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":701224,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70188939,"text":"70188939 - 2017 - California Spotted Owl (Strix occidentalis occidentalis) habitat use patterns in a burned landscape","interactions":[],"lastModifiedDate":"2017-06-27T16:20:16","indexId":"70188939","displayToPublicDate":"2017-06-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"displayTitle":"California Spotted Owl (Strix occidentalis occidentalis) habitat use patterns in a burned landscape","title":"California Spotted Owl (Strix occidentalis occidentalis) habitat use patterns in a burned landscape","docAbstract":"Fire is a dynamic ecosystem process of mixed-conifer forests of the Sierra Nevada, but there is limited scientific information addressing wildlife habitat use in burned landscapes. Recent studies have presented contradictory information regarding the effects of stand-replacing wildfires on Spotted Owls (Strix occidentalis) and their habitat. While fire promotes heterogeneous forest landscapes shown to be favored by owls, high severity fire may create large canopy gaps that can fragment the closed-canopy habitat preferred by Spotted Owls. We used radio-telemetry to determine whether foraging California Spotted Owls (S. o. occidentalis) in Yosemite National Park, California, USA, showed selection for particular fire severity patch types within their home ranges. Our results suggested that Spotted Owls exhibited strong habitat selection within their home ranges for locations near the roost and edge habitats, and weak selection for lower fire severity patch types. Although owls selected high contrast edges with greater relative probabilities than low contrast edges, we did not detect a statistical difference between these probabilities. Protecting forests from stand-replacing fires via mechanical thinning or prescribed fire is a priority for management agencies, and our results suggest that fires of low to moderate severity can create habitat conditions within California Spotted Owls' home ranges that are favored for foraging.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-16-184.1","usgsCitation":"Eyes, S., Roberts, S.L., and Johnson, M.D., 2017, California Spotted Owl (Strix occidentalis occidentalis) habitat use patterns in a burned landscape: The Condor, v. 119, no. 3, p. 375-388, https://doi.org/10.1650/CONDOR-16-184.1.","productDescription":"14 p.","startPage":"375","endPage":"388","ipdsId":"IP-080251","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":461495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-184.1","text":"Publisher Index Page"},{"id":343040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536ea0e4b062508e3c7a4f","contributors":{"authors":[{"text":"Eyes, Stephanie 0000-0002-6969-9927","orcid":"https://orcid.org/0000-0002-6969-9927","contributorId":193688,"corporation":false,"usgs":false,"family":"Eyes","given":"Stephanie","email":"","affiliations":[],"preferred":false,"id":701413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Susan L.","contributorId":85312,"corporation":false,"usgs":true,"family":"Roberts","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":701412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Matthew D. mjjohnson@usgs.gov","contributorId":193689,"corporation":false,"usgs":false,"family":"Johnson","given":"Matthew","email":"mjjohnson@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":701414,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}