{"pageNumber":"357","pageRowStart":"8900","pageSize":"25","recordCount":46619,"records":[{"id":70193690,"text":"70193690 - 2017 - Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","interactions":[],"lastModifiedDate":"2017-11-22T16:55:01","indexId":"70193690","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","docAbstract":"<p>Conserving wide-ranging animals requires knowledge about their year-round movements and resource use. Golden Eagles (<i>Aquila chrysaetos</i>) exhibit a wide range of movement patterns across North America. We combined tracking data from 571 Golden Eagles from multiple independent satellite-telemetry projects from North America to provide a comprehensive look at the magnitude and extent of these movements on a continental scale. We compared patterns of use relative to four alternative administrative and ecological mapping systems, namely Bird Conservation Regions (BCRs), U.S. administrative migratory bird flyways, Migratory Bird Joint Ventures, and Landscape Conservation Cooperatives. Our analyses suggested that eagles initially captured in eastern North America used space differently than those captured in western North America. Other groups of eagles that exhibited distinct patterns in space use included long-distance migrants from northern latitudes, and southwestern and Californian desert residents. There were also several groupings of eagles in the Intermountain West. Using this collaborative approach, we have identified large-scale movement patterns that may not have been possible with individual studies. These results will support landscape-scale conservation measures for Golden Eagles across North America.</p>","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-72.1","usgsCitation":"Brown, J.L., Bedrosian, B., Bell, D.A., Braham, M.A., Cooper, J., Crandall, R.H., DiDonato, J., Domenech, R., Duerr, A.E., Katzner, T., Lanzone, M.J., LaPlante, D.W., McIntyre, C.L., Miller, T.A., Murphy, R.K., Shreading, A., Slater, S.J., Smith, J.P., Smith, B.W., Watson, J.W., and Woodbridge, B., 2017, Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?: Journal of Raptor Research, v. 51, no. 3, p. 197-215, https://doi.org/10.3356/JRR-16-72.1.","productDescription":"19 p.","startPage":"197","endPage":"215","ipdsId":"IP-082399","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":461353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-72.1","text":"Publisher Index Page"},{"id":348145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"51","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea1e4b0531197b27f75","contributors":{"authors":[{"text":"Brown, Jessi L.","contributorId":44817,"corporation":false,"usgs":false,"family":"Brown","given":"Jessi","email":"","middleInitial":"L.","affiliations":[{"id":13184,"text":"Program in Ecology, Evolution and Conservation Biology, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":719895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Bryan","contributorId":199738,"corporation":false,"usgs":false,"family":"Bedrosian","given":"Bryan","affiliations":[{"id":35591,"text":"Teton Raptor Center","active":true,"usgs":false}],"preferred":false,"id":719896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Douglas A.","contributorId":199739,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":719897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Melissa A.","contributorId":199740,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":34303,"text":"West Virginia University, Department of Geology & Geography","active":true,"usgs":false}],"preferred":false,"id":719898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":719899,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crandall, Ross H.","contributorId":198926,"corporation":false,"usgs":false,"family":"Crandall","given":"Ross","email":"","middleInitial":"H.","affiliations":[{"id":6657,"text":"Craighead Beringia South","active":true,"usgs":false}],"preferred":false,"id":719900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiDonato, Joe","contributorId":199742,"corporation":false,"usgs":false,"family":"DiDonato","given":"Joe","email":"","affiliations":[{"id":35593,"text":"Wildlife Consulting and Photography","active":true,"usgs":false}],"preferred":false,"id":719901,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Domenech, Robert","contributorId":199743,"corporation":false,"usgs":false,"family":"Domenech","given":"Robert","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719902,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719903,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":719894,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lanzone, Michael J.","contributorId":147851,"corporation":false,"usgs":false,"family":"Lanzone","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13392,"text":"Cellular Tracking Technologies","active":true,"usgs":false}],"preferred":false,"id":719904,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"LaPlante, David W.","contributorId":199744,"corporation":false,"usgs":false,"family":"LaPlante","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":35595,"text":"Natural Resource Geospatial","active":true,"usgs":false}],"preferred":false,"id":719905,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McIntyre, Carol L.","contributorId":196673,"corporation":false,"usgs":false,"family":"McIntyre","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":719906,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719907,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Murphy, Robert K.","contributorId":67643,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":719908,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shreading, Adam","contributorId":199745,"corporation":false,"usgs":false,"family":"Shreading","given":"Adam","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719909,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Slater, Steven J.","contributorId":199746,"corporation":false,"usgs":false,"family":"Slater","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":719910,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Smith, Jeff P.","contributorId":199747,"corporation":false,"usgs":false,"family":"Smith","given":"Jeff","email":"","middleInitial":"P.","affiliations":[{"id":35597,"text":"H.T. Harvey & Associates","active":true,"usgs":false}],"preferred":false,"id":719911,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, Brian W.","contributorId":199748,"corporation":false,"usgs":false,"family":"Smith","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719912,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Watson, James W.","contributorId":198921,"corporation":false,"usgs":false,"family":"Watson","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":719913,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Woodbridge, Brian","contributorId":198923,"corporation":false,"usgs":false,"family":"Woodbridge","given":"Brian","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719914,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70208431,"text":"70208431 - 2017 - Assessing the risk of non-native marine species in the Bering Sea","interactions":[],"lastModifiedDate":"2020-02-11T06:42:26","indexId":"70208431","displayToPublicDate":"2017-11-01T06:52:53","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Assessing the risk of non-native marine species in the Bering Sea","docAbstract":"<p>Invasive species are one of the leading global conservation concerns, which can have strong, negative impacts on ecosystems, vulnerable species, and valuable natural resources. Arctic regions have experienced a relatively low number of biological introductions to date. Their geographical remoteness, cold waters, and presence of sea ice present challenging conditions for both non-native organisms and the vessels that transport them, presumably leading to low rates of introduction and establishment. However, observed increases in water temperatures reductions in sea ice, and projected increases in shipping traffic are expected to render arctic marine regions more susceptible to the arrival and colonization of marine invasives. Risk assessments for these Arctic regions are important to inform management and monitoring priorities by determining which species pose the greatest risk. To this end, we developed a ranking system for non-native marine species and used this system to assess the risk of non-native species to the Bering Sea. Using species’ published physiological tolerances, we mapped habitat suitability under current and future climate scenarios to identify geographic areas of current and future concern. In addition, we described shipping traffic from commercial and fishing vessels to identify ports of entry for non-native species. Collectively, these analyses identify which marine species have the greatest risk for invasion, where in the Bering Sea invasion risk and species establishment is greatest, and which ports are most likely to serve as an entry point for marine invasives into Alaska’s Bering Sea. The ranking system we developed for non-native marine species consists of 33 questions grouped into five categories. The first four categories evaluate a species’ ability to arrive and establish in the Bering Sea, its reliance on humans for introductions, its biology, and its impacts on ecological and human systems. The fifth category is not included in the total ranking score, but provides information on management considerations. The ranking system has methods to account for data deficiencies and calculates these deficiencies to allow readers to weigh the lack of knowledge with the ranking score. We prioritized non-native species for ranking based on their geographic proximity to the Bering Sea. We evaluated 46 species and ranking scores ranged from 29.1 to 74.3 (out of a possible 100), with highest scores indicating greatest risk. Taxonomy at the level of phylum did not explain variation in ranking values, likely due to the substantial biological variation relative to our ranking criteria among members of the same phylum. To investigate where non-native species may survive and persist in the Bering Sea, we compared species’ temperature and salinity thresholds to environmental conditions of the Bering Sea. Environmental conditions were obtained from three Regional Ocean Modeling Systems (ROMS) and investigated under two time periods: current (2003-2012) and mid-century (2030-2039). We identified potential habitat for survival for 42 species, and potential habitat for reproduction for 29 species. Under current conditions, all species had temperature and salinity thresholds that would allow survival in the Bering Sea for at least part of the year, and most species (79% to 83%) had thresholds that would allow for survival year-round. For species with temperature and salinity thresholds unsuitable for survival in the Bering Sea, winter temperatures appear to be the limiting factor. Most species had six to nine weeks of suitable conditions for reproduction. Future increases in water temperatures are expected to open more habitat for marine invasives. Two of the three ROMs project an increase in the number of non-native species that would be able to survive year-round by mid-century. Moreover, models project between 37% and 60% of the Bering Sea shelf habitat to become more suitable under mid-century climate condition.</p>","language":"English","publisher":"North Pacific Research Board","collaboration":"University of Alaska Anchorage, NOAA, Aleutian Bering Sea Islands Landscape Conservation Cooperative","usgsCitation":"Reimer, J., Droghini, A., Fischbach, A., Watson, J., Bernard, B., and Poe, A., 2017, Assessing the risk of non-native marine species in the Bering Sea, 46 p.","productDescription":"46 p.","ipdsId":"IP-094656","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372163,"type":{"id":15,"text":"Index Page"},"url":"https://accs.uaa.alaska.edu/wp-content/uploads/Reimeretal2017_FinalReport.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -172.79296875,\n              51.890053935216926\n            ],\n            [\n              -161.89453125,\n              51.890053935216926\n            ],\n            [\n              -161.89453125,\n              65.94647177615738\n            ],\n            [\n              -172.79296875,\n              65.94647177615738\n            ],\n            [\n              -172.79296875,\n              51.890053935216926\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reimer, Jesika","contributorId":222311,"corporation":false,"usgs":false,"family":"Reimer","given":"Jesika","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droghini, Amanda 0000-0001-6692-2348","orcid":"https://orcid.org/0000-0001-6692-2348","contributorId":222312,"corporation":false,"usgs":false,"family":"Droghini","given":"Amanda","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":781852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watson, Jordan 0000-0002-1686-0377","orcid":"https://orcid.org/0000-0002-1686-0377","contributorId":222313,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","email":"","affiliations":[{"id":40517,"text":"NOAA Alaska Fisheries Science Center Auke Bay Laboratories","active":true,"usgs":false}],"preferred":false,"id":781855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, Bonnie","contributorId":222314,"corporation":false,"usgs":false,"family":"Bernard","given":"Bonnie","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poe, Aaron","contributorId":222315,"corporation":false,"usgs":false,"family":"Poe","given":"Aaron","email":"","affiliations":[{"id":40518,"text":"Aleutian and Bering Sea Islands LCC U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":781857,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192845,"text":"70192845 - 2017 - Effects of industrial and investigator disturbance on Arctic-nesting geese","interactions":[],"lastModifiedDate":"2017-11-01T16:54:00","indexId":"70192845","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of industrial and investigator disturbance on Arctic-nesting geese","docAbstract":"<p><span>Oil and gas development on the Arctic Coastal Plain (ACP) of Alaska, USA may have effects on Arctic-nesting birds. To estimate effects of industrial activity and investigator disturbance on avian productivity, we monitored nests of greater white-fronted geese (</span><i>Anser albifrons</i><span>) with digital cameras and periodic nest visits during 2013–2014 at 2 sites on the ACP. A disturbed site was adjacent to human-made infrastructure and industrial clean-up activities initiated at the onset of the study and a control site was &gt;2 km from sources of industrial disturbance. We assessed variation in estimates of incubation constancy, nest survival, and predator behavior relative to site, year, and distance from industrial activity using nest photographs obtained at 1-minute intervals. We compared analysis of hourly nest survival informed by intensive monitoring with cameras to analysis of daily nest survival informed by traditional nest visit data obtained at intervals of 5–7 days to assess how method and time scale of sampling affect ecological inference. Geese in both sites exhibited high levels of nest attendance and initiated incubation breaks less than once per day. Observer-caused incubation breaks associated with nest visits (</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0011.png?v=1&amp;s=9cecff1a4b3d1efa6dbd2134a0875836a87bb4c1\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0011.png?v=1&amp;s=9cecff1a4b3d1efa6dbd2134a0875836a87bb4c1\"></span></span><span> = 37.8 min) were longer than other types of incubation breaks (</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0012.png?v=1&amp;s=91394fd6ce910ee4166598af33db96e3ee00d3fb\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0012.png?v=1&amp;s=91394fd6ce910ee4166598af33db96e3ee00d3fb\"></span></span><span> = 8.7 min), demonstrating a differential response by nesting geese to direct human encroachment versus indirect vehicular and aircraft traffic. During both years, geese were absent from nests more frequently in the disturbed (</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0013.png?v=1&amp;s=2ad328b46109601b89b46d54f991ea33664b1d58\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0013.png?v=1&amp;s=2ad328b46109601b89b46d54f991ea33664b1d58\"></span></span><span> = 0.9 breaks/day) than control (</span><span class=\"math-equation-construct\" data-equation-construct=\"true\"><span class=\"math-equation-image\" data-equation-image=\"true\"><img class=\"inlineGraphic\" src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0014.png?v=1&amp;s=9a7d7f88e90675b63a56b9d0bdf30a3337f713d2\" alt=\"math formula\" data-mce-src=\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21312/asset/equation/jwmg21312-math-0014.png?v=1&amp;s=9a7d7f88e90675b63a56b9d0bdf30a3337f713d2\"></span></span><span> = 0.6 breaks/day) site, and this break frequency was slightly higher for nests closer to industrial activity. In the year with high rates of depredation, nest survival was positively related to distance from industrial activity and abandoned infrastructure, consistent with predictions of industry-caused effects. This relationship, however, was not evident in the year with reduced predation pressure, likely because of annual variation in arctic fox (</span><i>Vulpes lagopus</i><span>) behavior. Analysis of nest survival probability informed by camera data allowed for detection of detailed patterns of variation that were not supported when using only visit data for the same nests. Observer visits were responsible for reductions of 7–35% in nest survival probability, highlighting the importance of minimizing, and controlling for, observer effects in studies of avian productivity. Indirect vehicular and aircraft disturbance posed less risk to nest survival than direct encroachment by observers at nest sites. Therefore, effects of industrial activities on avian productivity in the Arctic can be minimized through practices that limit direct encounters with nests.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21312","usgsCitation":"Meixell, B.W., and Flint, P.L., 2017, Effects of industrial and investigator disturbance on Arctic-nesting geese: Journal of Wildlife Management, v. 81, no. 8, p. 1372-1385, https://doi.org/10.1002/jwmg.21312.","productDescription":"14 p.","startPage":"1372","endPage":"1385","ipdsId":"IP-082311","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438162,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9GP9","text":"USGS data release","linkHelpText":"Greater White-fronted Goose (Anser albifrons) Nest Characteristics and Nesting Behavior Classifications from Time-lapse Photographs; Point Lonely, Alaska, 2013-2014"},{"id":348059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.31369400024414,\n              70.89024547571003\n            ],\n            [\n              -153.21224212646484,\n              70.89024547571003\n            ],\n            [\n              -153.21224212646484,\n              70.91613598862408\n            ],\n            [\n              -153.31369400024414,\n              70.91613598862408\n            ],\n            [\n              -153.31369400024414,\n              70.89024547571003\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"81","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-17","publicationStatus":"PW","scienceBaseUri":"59fadd1ee4b0531197b13c6c","contributors":{"authors":[{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717171,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193277,"text":"70193277 - 2017 - Alternative pathways to landscape transformation: Invasive grasses, burn severity and fire frequency in arid ecosystems","interactions":[],"lastModifiedDate":"2017-11-06T13:06:31","indexId":"70193277","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Alternative pathways to landscape transformation: Invasive grasses, burn severity and fire frequency in arid ecosystems","docAbstract":"<ol id=\"jec12863-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Arid ecosystems are often vulnerable to transformation to invasive-dominated states following fire, but data on persistence of these states are sparse. The grass/fire cycle is a feedback process between invasive annual grasses and fire frequency that often leads to the formation of alternative vegetation states dominated by the invasive grasses. However, other components of fire regimes, such as burn severity, also have the potential to produce long-term vegetation transformations. Our goal was to evaluate the influence of both fire frequency and burn severity on the transformation of woody-dominated communities to communities dominated by invasive grasses in major elevation zones of the Mojave Desert of western North America.</li><li>We used a chronosequence design to collect data on herbaceous and woody cover at 229 unburned reference plots and 578 plots that burned between 1972 and 2010. We stratified the plots by elevation zone (low, mid, high), fire frequency (1–3 times) and years post-fire (YPF; 1–5, 6–10, 11–20 and 21–40 YPF). Burn severity for each plot was estimated by the difference normalized burn ratio.</li><li>We identified two broad post-fire successional pathways. One was an outcome of fire frequency, resulting in a strong potential transformation via the grass/fire cycle. The second pathway was driven by burn severity, the critical aspect being that long-term transformation of a community could occur from just one fire in areas that burned at high or sometimes moderate severity. Dominance by invasive grasses was most likely to occur in low-and high-elevation communities; cover of native herbaceous species was often greater than that of invasive grasses in the mid-elevation zone.</li><li><i>Synthesis</i>. Invasive grasses can dominate a site that burned only one time in many decades at high severity, or a site that burned at low severity but multiple times in the same time period. However, high burn severity may predispose areas to more frequent fire because they have relatively high cover of invasive annual grass, suggesting burn severity and fire frequency have both independent and synergistic effects. Resilience in vegetation structure following fire in many arid communities may be limited to a narrow window of low burn severity in areas that have not burned in many decades.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.12863","usgsCitation":"Klinger, R.C., and Brooks, M.L., 2017, Alternative pathways to landscape transformation: Invasive grasses, burn severity and fire frequency in arid ecosystems: Journal of Ecology, v. 105, p. 1521-1533, https://doi.org/10.1111/1365-2745.12863.","productDescription":"13 p.","startPage":"1521","endPage":"1533","ipdsId":"IP-084387","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469364,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.12863","text":"Publisher Index Page"},{"id":438160,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79022PZ","text":"USGS data release","linkHelpText":"Cover of Woody and Herbaceous Functional Groups in Burned and Unburned Plots, Mojave Desert, 2009-2013"},{"id":348273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","volume":"105","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"5a07e84be4b09af898c8cb40","contributors":{"authors":[{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":718506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":718505,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192620,"text":"70192620 - 2017 - Basis function models for animal movement","interactions":[],"lastModifiedDate":"2017-11-10T11:12:34","indexId":"70192620","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2527,"text":"Journal of the American Statistical Association","active":true,"publicationSubtype":{"id":10}},"title":"Basis function models for animal movement","docAbstract":"<p><span>Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01621459.2016.1246250","usgsCitation":"Hooten, M., and Johnson, D., 2017, Basis function models for animal movement: Journal of the American Statistical Association, v. 112, no. 518, p. 578-589, https://doi.org/10.1080/01621459.2016.1246250.","productDescription":"12 p.","startPage":"578","endPage":"589","ipdsId":"IP-072343","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469371,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Basis_Function_Models_for_Animal_Movement/4052175","text":"External Repository"},{"id":348569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"518","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-13","publicationStatus":"PW","scienceBaseUri":"5a06c8c7e4b09af898c860ee","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":716570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193169,"text":"70193169 - 2017 - Environmental niche models for riverine desert fishes and their similarity according to phylogeny and functionality","interactions":[],"lastModifiedDate":"2017-11-20T15:26:00","indexId":"70193169","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Environmental niche models for riverine desert fishes and their similarity according to phylogeny and functionality","docAbstract":"<p><span>Environmental filtering and competitive exclusion are hypotheses frequently invoked in explaining species' environmental niches (i.e., geographic distributions). A key assumption in both hypotheses is that the functional niche (i.e., species traits) governs the environmental niche, but few studies have rigorously evaluated this assumption. Furthermore, phylogeny could be associated with these hypotheses if it is predictive of functional niche similarity via phylogenetic signal or convergent evolution, or of environmental niche similarity through phylogenetic attraction or repulsion. The objectives of this study were to investigate relationships between environmental niches, functional niches, and phylogenies of fishes of the Upper (UCRB) and Lower (LCRB) Colorado River Basins of southwestern North America. We predicted that functionally similar species would have similar environmental niches (i.e., environmental filtering) and that closely related species would be functionally similar (i.e., phylogenetic signal) and possess similar environmental niches (i.e., phylogenetic attraction). Environmental niches were quantified using environmental niche modeling, and functional similarity was determined using functional trait data. Nonnatives in the UCRB provided the only support for environmental filtering, which resulted from several warmwater nonnatives having dam number as a common predictor of their distributions, whereas several cool- and coldwater nonnatives shared mean annual air temperature as an important distributional predictor. Phylogenetic signal was supported for both natives and nonnatives in both basins. Lastly, phylogenetic attraction was only supported for native fishes in the LCRB and for nonnative fishes in the UCRB. Our results indicated that functional similarity was heavily influenced by evolutionary history, but that phylogenetic relationships and functional traits may not always predict the environmental distribution of species. However, the similarity of environmental niches among warmwater centrarchids, ictalurids, fundulids, and poeciliids in the UCRB indicated that dam removals could influence the distribution of these nonnatives simultaneously, thus providing greater conservation benefits. However, this same management strategy would have more limited effects on nonnative salmonids, catostomids, and percids with colder temperature preferences, thus necessitating other management strategies to control these species.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1658","usgsCitation":"Whitney, J.E., Whittier, J.B., and Paukert, C.P., 2017, Environmental niche models for riverine desert fishes and their similarity according to phylogeny and functionality: Ecosphere, v. 8, no. 1, p. 1-21, https://doi.org/10.1002/ecs2.1658.","productDescription":"Article e01658; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-076772","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1658","text":"Publisher Index Page"},{"id":349155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115,\n              30\n            ],\n            [\n              -105,\n              30\n            ],\n            [\n              -105,\n              43\n            ],\n            [\n              -115,\n              43\n            ],\n            [\n              -115,\n              30\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-06","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d23","contributors":{"authors":[{"text":"Whitney, James E.","contributorId":176500,"corporation":false,"usgs":false,"family":"Whitney","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":722918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":722919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":147821,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":718117,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192497,"text":"70192497 - 2017 - Estimating the high-arsenic domestic-well population in the conterminous United States","interactions":[],"lastModifiedDate":"2017-12-14T16:34:10","indexId":"70192497","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the high-arsenic domestic-well population in the conterminous United States","docAbstract":"<p><span>Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic &gt;10 μg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic &gt;10 μg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration &gt;10 μg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.7b02881","usgsCitation":"Ayotte, J.D., Medalie, L., Qi, S.L., Backer, L.C., and Nolan, B.T., 2017, Estimating the high-arsenic domestic-well population in the conterminous United States: Environmental Science & Technology, v. 51, no. 21, p. 12443-12454, https://doi.org/10.1021/acs.est.7b02881.","productDescription":"12 p.","startPage":"12443","endPage":"12454","ipdsId":"IP-085175","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8842838","text":"Publisher Index 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 \"}}]}\n","volume":"51","issue":"21","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-18","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d29","contributors":{"authors":[{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Backer, Lorraine C.","contributorId":198459,"corporation":false,"usgs":false,"family":"Backer","given":"Lorraine","email":"","middleInitial":"C.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":true,"id":716077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":716078,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193284,"text":"70193284 - 2017 - High altitude flights by ruddy shelduck Tadorna ferruginea during trans-Himalayan migrations","interactions":[],"lastModifiedDate":"2017-11-01T16:41:04","indexId":"70193284","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"High altitude flights by ruddy shelduck <i>Tadorna ferruginea</i> during trans-Himalayan migrations","title":"High altitude flights by ruddy shelduck Tadorna ferruginea during trans-Himalayan migrations","docAbstract":"<p><span>Birds that migrate across high altitude mountain ranges are faced with the challenge of maintaining vigorous exercise in environments with limited oxygen. Ruddy shelducks are known to use wintering grounds south of the Tibetan Plateau at sea level and breeding grounds north of Himalayan mountain range. Therefore, it is likely these shelducks are preforming high altitude migrations. In this study we analyse satellite telemetry data collected from 15 ruddy shelduck from two populations wintering south of the Tibetan Plateau from 2007 to 2011. During north and south migrations ruddy shelduck travelled 1481 km (range 548–2671 km) and 1238 km (range 548–2689 km) respectively. We find mean maximum altitudes of birds in flight reached 5590 m (range of means 4755–6800 m) and mean maximum climb rates of 0.45 m s</span><sup>–1</sup><span><span>&nbsp;</span>(range 0.23–0.74 m s</span><sup>–1</sup><span>). The ruddy shelduck is therefore an extreme high altitude migrant that has likely evolved a range of physiological adaptations in order to complete their migrations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jav.01443","usgsCitation":"Parr, N., Bearhop, S., Douglas, D.C., Takekawa, J., Prosser, D.J., Newman, S., Perry, W., Balachandran, S., Witt, M., Hou, Y., Lu, Z., and Hawkes, L., 2017, High altitude flights by ruddy shelduck Tadorna ferruginea during trans-Himalayan migrations: Journal of Avian Biology, v. 48, no. 10, p. 1310-1315, https://doi.org/10.1111/jav.01443.","productDescription":"6 p.","startPage":"1310","endPage":"1315","ipdsId":"IP-080832","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469368,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10871/31703","text":"External Repository"},{"id":348054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, India, Mongolia, Myanmar, Nepal","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              80,\n              15\n            ],\n            [\n              102,\n              15\n            ],\n            [\n              102,\n              50\n            ],\n            [\n              80,\n              50\n            ],\n            [\n              80,\n              15\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"48","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd1de4b0531197b13c62","contributors":{"authors":[{"text":"Parr, N.","contributorId":199268,"corporation":false,"usgs":false,"family":"Parr","given":"N.","email":"","affiliations":[],"preferred":false,"id":718531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bearhop, S.","contributorId":199269,"corporation":false,"usgs":false,"family":"Bearhop","given":"S.","email":"","affiliations":[],"preferred":false,"id":718532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, J.Y.","contributorId":199270,"corporation":false,"usgs":false,"family":"Takekawa","given":"J.Y.","email":"","affiliations":[],"preferred":false,"id":718533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":718534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, S.H.","contributorId":199271,"corporation":false,"usgs":false,"family":"Newman","given":"S.H.","email":"","affiliations":[],"preferred":false,"id":718535,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perry, W.M.","contributorId":199272,"corporation":false,"usgs":false,"family":"Perry","given":"W.M.","email":"","affiliations":[],"preferred":false,"id":718536,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Balachandran, S.","contributorId":199273,"corporation":false,"usgs":false,"family":"Balachandran","given":"S.","affiliations":[],"preferred":false,"id":718537,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Witt, M.J.","contributorId":199274,"corporation":false,"usgs":false,"family":"Witt","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":718538,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hou, Y.","contributorId":199275,"corporation":false,"usgs":false,"family":"Hou","given":"Y.","email":"","affiliations":[],"preferred":false,"id":718539,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lu, Z.","contributorId":199276,"corporation":false,"usgs":false,"family":"Lu","given":"Z.","affiliations":[],"preferred":false,"id":718540,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hawkes, L.A.","contributorId":199277,"corporation":false,"usgs":false,"family":"Hawkes","given":"L.A.","email":"","affiliations":[],"preferred":false,"id":718541,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70195182,"text":"70195182 - 2017 - Distribution and status of five non-native fish species in the Tampa Bay drainage (USA), a hot spot for fish introductions","interactions":[],"lastModifiedDate":"2018-02-07T12:54:01","indexId":"70195182","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":994,"text":"BioInvasions Records","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and status of five non-native fish species in the Tampa Bay drainage (USA), a hot spot for fish introductions","docAbstract":"<p><span>The Tampa Bay region of Florida (USA) is a hot spot for non-native freshwater fishes. However, published information on most non-native fishes in the basin is not current. Systematic sampling efforts targeting non-native fishes in the region were conducted from 2013–2015 by the University of Florida Tropical Aquaculture Laboratory. Data from these recent surveys were analyzed, along with historic and new data from published and unpublished sources, to assess current fish distributions and determine status. We focus on five of the non-native species sampled: pike killifish&nbsp;</span><i>Belonesox belizanus</i><span><span>&nbsp;</span>Kner, 1860, green swordtail<span>&nbsp;</span></span><i>Xiphophorus hellerii</i><span><span>&nbsp;</span>Heckel, 1848, southern platyfish<span>&nbsp;</span></span><i>Xiphophorus maculatus</i><span><span>&nbsp;</span>(Günther, 1866), Mayan cichlid<span>&nbsp;</span></span><i>Mayaheros urophthalmus</i><span><span>&nbsp;</span>(Günther, 1862), and Jack Dempsey<span>&nbsp;</span></span><i>Rocio octofasciata</i><span><span>&nbsp;</span>(Regan, 1903). All five were found to have reproducing populations in the basin, each showing broader distributions than previously indicated. Non-native populations of four of the species have persisted in the Tampa Bay region since at least the 1990s. In contrast, the presence of Mayan cichlid in the basin was not confirmed until 2004. Based on numbers, distributions, and years of persistence, these five species all maintain established populations. Pike killifish and Mayan cichlid are established and spreading throughout multiple habitat types, while green swordtail, southern platyfish, and Jack Dempsey are localized and found primarily in more marginal habitats (e.g., small ditches and first order tributary streams). Factors affecting continued existence and distributions likely include aquaculture, biotic resistance, and thermal and salinity tolerances. We also clarify non-native species status determination using a multi-agency collaborative approach, and reconcile differences in terminology usage and interpretation.</span></p>","language":"English","publisher":"REABIC","doi":"10.3391/bir.2017.6.4.15","usgsCitation":"Lawson, K., Tuckett, Q.M., Ritch, J.L., Nico, L., Fuller, P., Matheson, R.E., and Hill, J.E., 2017, Distribution and status of five non-native fish species in the Tampa Bay drainage (USA), a hot spot for fish introductions: BioInvasions Records, v. 6, no. 4, p. 393-406, https://doi.org/10.3391/bir.2017.6.4.15.","productDescription":"14 p.","startPage":"393","endPage":"406","ipdsId":"IP-076367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":461361,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/bir.2017.6.4.15","text":"Publisher Index Page"},{"id":438164,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F790228K","text":"USGS data release","linkHelpText":"Distribution and status of five non-native fish species in the Tampa Bay drainage (USA), a hot spot for fish introductions-Data"},{"id":351243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Tampa Bay drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.33,\n              28.33\n            ],\n            [\n              -81.66,\n              28.33\n            ],\n            [\n              -81.66,\n              27.35\n            ],\n            [\n              -83.33,\n              27.35\n            ],\n            [\n              -83.33,\n              28.33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"6","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e7ae4b00f54eb22933f","contributors":{"authors":[{"text":"Lawson, Katelyn M.","contributorId":201981,"corporation":false,"usgs":false,"family":"Lawson","given":"Katelyn M.","affiliations":[{"id":36314,"text":"University of Florida/IFAS","active":true,"usgs":false}],"preferred":false,"id":727319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tuckett, Quenton M.","contributorId":201982,"corporation":false,"usgs":false,"family":"Tuckett","given":"Quenton","email":"","middleInitial":"M.","affiliations":[{"id":36314,"text":"University of Florida/IFAS","active":true,"usgs":false}],"preferred":false,"id":727320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ritch, Jared L.","contributorId":201983,"corporation":false,"usgs":false,"family":"Ritch","given":"Jared","email":"","middleInitial":"L.","affiliations":[{"id":36315,"text":"University of Florida/IFAS : Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":727321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nico, Leo 0000-0002-4488-7737 lnico@usgs.gov","orcid":"https://orcid.org/0000-0002-4488-7737","contributorId":138599,"corporation":false,"usgs":true,"family":"Nico","given":"Leo","email":"lnico@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":727323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Pam 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":167676,"corporation":false,"usgs":true,"family":"Fuller","given":"Pam","email":"pfuller@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":727318,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matheson, Richard E.","contributorId":201984,"corporation":false,"usgs":false,"family":"Matheson","given":"Richard","email":"","middleInitial":"E.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":727322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hill, Jeffrey E.","contributorId":201985,"corporation":false,"usgs":false,"family":"Hill","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":36314,"text":"University of Florida/IFAS","active":true,"usgs":false}],"preferred":false,"id":727324,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194283,"text":"70194283 - 2017 - Restoration of contaminated ecosystems: adaptive management in a changing climate","interactions":[],"lastModifiedDate":"2017-11-22T11:54:31","indexId":"70194283","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Restoration of contaminated ecosystems: adaptive management in a changing climate","docAbstract":"<p><span>Three case studies illustrate how adaptive management (AM) has been used in ecological restorations that involve contaminants. Contaminants addressed include mercury, selenium, and contaminants and physical disturbances delivered to streams by urban stormwater runoff. All three cases emphasize the importance of broad stakeholder input early and consistently throughout decision analysis for AM. Risk of contaminant exposure provided input to the decision analyses (e.g. selenium exposure to endangered razorback suckers, Stewart Lake; multiple contaminants in urban stormwater runoff, Melbourne) and was balanced with the protection of resources critical for a desired future state (e.g. preservation old growth trees, South River). Monitoring also played a critical role in the ability to conduct the decision analyses necessary for AM plans. For example, newer technologies in the Melbourne case provided a testable situation where contaminant concentrations and flow disturbance were reduced to support a return to good ecological condition. In at least one case (Stewart Lake), long-term monitoring data are being used to document the potential effects of climate change on a restoration trajectory. Decision analysis formalized the process by which stakeholders arrived at the priorities for the sites, which together constituted the desired future condition towards which each restoration is aimed. Alternative models were developed that described in mechanistic terms how restoration can influence the system towards the desired future condition. Including known and anticipated effects of future climate scenarios in these models will make them robust to the long-term exposure and effects of contaminants in restored ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/rec.12583","usgsCitation":"Farag, A., Larson, D.L., Stauber, J., Stahl, R., Isanhart, J., McAbee, K., and Walsh, C.J., 2017, Restoration of contaminated ecosystems: adaptive management in a changing climate: Restoration Ecology, v. 25, no. 6, p. 884-893, https://doi.org/10.1111/rec.12583.","productDescription":"10 p.","startPage":"884","endPage":"893","ipdsId":"IP-080300","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":487214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.12583","text":"Publisher Index Page"},{"id":349273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"5a60fb21e4b06e28e9c22d08","contributors":{"authors":[{"text":"Farag, Aida 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":200690,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":723065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stauber, Jenny","contributorId":200691,"corporation":false,"usgs":false,"family":"Stauber","given":"Jenny","email":"","affiliations":[],"preferred":false,"id":723067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stahl, Ralph","contributorId":200692,"corporation":false,"usgs":false,"family":"Stahl","given":"Ralph","affiliations":[],"preferred":false,"id":723068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Isanhart, John 0000-0003-0208-1839","orcid":"https://orcid.org/0000-0003-0208-1839","contributorId":200693,"corporation":false,"usgs":false,"family":"Isanhart","given":"John","email":"","affiliations":[],"preferred":false,"id":723069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAbee, Kevin T.","contributorId":141327,"corporation":false,"usgs":false,"family":"McAbee","given":"Kevin T.","affiliations":[],"preferred":false,"id":723292,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walsh, Christopher J.","contributorId":171683,"corporation":false,"usgs":false,"family":"Walsh","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723293,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194264,"text":"70194264 - 2017 - Use of swabs for sampling epithelial cells for molecular genetics analyses in Enteroctopus","interactions":[],"lastModifiedDate":"2018-05-20T12:29:34","indexId":"70194264","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":735,"text":"American Malacological Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Use of swabs for sampling epithelial cells for molecular genetics analyses in <i>Enteroctopus</i>","title":"Use of swabs for sampling epithelial cells for molecular genetics analyses in Enteroctopus","docAbstract":"<p><span>We evaluated the efficacy of using swabs to collect cells from the epidermis of octopus as a non-invasive DNA source for classical genetic studies, and demonstrated value of the technique by incorporating it into an effort to determine, within a day, the lineage of captured, live&nbsp;</span><i>Enteroctopus</i><span><span>&nbsp;</span>(</span><i>E. dofleini</i><span><span>&nbsp;</span>or a cryptic lineage). The cryptic lineage was targeted for captive behavioral and morphological studies, while once genetically identified, the non-target lineage could be more rapidly released back to the wild. We used commercially available sterile foamtipped swabs and a high-salt preservation buffer to collect and store paired swab and muscle (arm tip) tissue sampled from live<span>&nbsp;</span></span><i>Enteroctopus</i><span><span>&nbsp;</span>collected from Prince William Sound, Alaska. We performed a one-day extraction of DNA from epithelial swab samples and amplification of two diagnostic microsatellite loci to determine the lineage of each of the 21 individuals. Following this rapid lineage assessment, which allowed us to release non-target individuals within a day of laboratory work, we compared paired swab and muscle tissue samples from each individual to assess quantity of DNA yields and consistency of genotyping results, followed by assessment of locus-by-locus reliability of DNA extracts from swabs. Epithelial swabs yielded, on average, lower quantities of DNA (170.32 ± 74.72 (SD) ng/μL) relative to DNA obtained from tissues collected using invasive or destructive techniques (310.95 ± 147.37 (SD) ng/μL. We observed some decrease in yields of DNA from extractions of swab samples conducted 19 and 31 months after initial extractions when samples were stored at room temperature in lysis buffer. All extractions yielded quantities of DNA sufficient to amplify and score all loci, which included fragment data from 10 microsatellite loci (nine polymorphic loci and monomorphic locus EdoμA106), and nucleotide sequence data from a 528 base pair portion of the nuclear octopine dehydrogenase gene. All results from genotyping and sequencing using paired swab and muscle tissue extracts were concordant, and experimental reliability levels for multilocus genotypes generated from swab samples exceeded 97%. This technique is useful for studies in which invasive sampling is not optimal, and in remote field situations since samples can be stored at ambient temperatures for at least 31 months. The use of epithelial swabs is thus a noninvasive technique appropriate for sampling genetic material from live octopuses for use in classical genetic studies as well as supporting experimental and behavioral studies.</span></p>","language":"English","publisher":"American Malacological Society","doi":"10.4003/006.035.0207","usgsCitation":"Hollenback, N., Scheel, D., Gravley, M.C., Sage, G.K., Toussaint, R.K., and Talbot, S.L., 2017, Use of swabs for sampling epithelial cells for molecular genetics analyses in Enteroctopus: American Malacological Bulletin, v. 35, no. 2, p. 145-157, https://doi.org/10.4003/006.035.0207.","productDescription":"13 p.","startPage":"145","endPage":"157","ipdsId":"IP-070408","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438159,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VM49HJ","text":"USGS data release","linkHelpText":"Enteroctopus Sampling Effects on Genetic Data, Prince William Sound, Alaska, 2012-2015"},{"id":349291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d0d","contributors":{"authors":[{"text":"Hollenback, Nathan","contributorId":200637,"corporation":false,"usgs":false,"family":"Hollenback","given":"Nathan","email":"","affiliations":[],"preferred":false,"id":722947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheel, David","contributorId":53272,"corporation":false,"usgs":false,"family":"Scheel","given":"David","email":"","affiliations":[],"preferred":false,"id":722948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":722950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toussaint, Rebecca K.","contributorId":104376,"corporation":false,"usgs":false,"family":"Toussaint","given":"Rebecca","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":722951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":722946,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193363,"text":"70193363 - 2017 - Rapid exhumation of Cretaceous arc-rocks along the Blue Mountains restraining bend of the Enriquillo-Plantain Garden fault, Jamaica, using thermochronometry from multiple closure systems","interactions":[],"lastModifiedDate":"2017-11-29T16:12:53","indexId":"70193363","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Rapid exhumation of Cretaceous arc-rocks along the Blue Mountains restraining bend of the Enriquillo-Plantain Garden fault, Jamaica, using thermochronometry from multiple closure systems","docAbstract":"The effect of rapid erosion on kinematic partitioning along transpressional plate margins is not well understood, particularly in highly erosive climates. The Blue Mountains restraining bend (BMRB) of eastern Jamaica, bound to the south by the left-lateral Enriquillo-Plantain Garden fault (EPGF), offers an opportunity to test the effects of highly erosive climatic conditions on a 30-km-wide restraining bend system. No previous thermochronometric data exists in Jamaica to describe the spatial or temporal pattern of rock uplift and how oblique (> 20°) plate motion is partitioned into vertical strain. To define the exhumation history, we measured apatite (n = 10) and zircon (n = 6) (U-Th)/He ages, 40Ar/39Ar (n = 2; amphibole and K-spar) ages, and U/Pb zircon (n = 2) crystallization ages. Late Cretaceous U/Pb and 40Ar/39Ar ages (74–68 Ma) indicate rapid cooling following shallow emplacement of plutons during north-south subduction along the Great Caribbean Arc. Early to middle Miocene zircon helium ages (19–14 Ma) along a vertical transect suggest exhumation and island emergence at ~ 0.2 mm/yr. Older zircon ages 10–15 km to the north (44–35 Ma) imply less rock uplift. Apatite helium ages are young (6–1 Ma) across the entire orogen, suggesting rapid exhumation of the BMRB since the late Miocene. These constraints are consistent with previous reports of restraining bend formation and early emergence of eastern Jamaica. An age-elevation relationship from a vertical transect implies an exhumation rate of 0.8 mm/yr, while calculated closure depths and thermal modeling suggests exhumation as rapid as 2 mm/yr. The rapid rock uplift rates in Jamaica are comparable to the most intense transpressive zones worldwide, despite the relatively slow (5–7 mm/yr) strike-slip rate. We hypothesize highly erosive conditions in Jamaica enable a higher fraction of plate motion to be accommodated by vertical deformation. Thus, strike-slip restraining bends may evolve differently depending on erosivity and local climate.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2017.09.021","usgsCitation":"Cochran, W., Spotila, J.A., Prince, P.S., and McAleer, R., 2017, Rapid exhumation of Cretaceous arc-rocks along the Blue Mountains restraining bend of the Enriquillo-Plantain Garden fault, Jamaica, using thermochronometry from multiple closure systems: Tectonophysics, v. 721, p. 292-309, https://doi.org/10.1016/j.tecto.2017.09.021.","productDescription":"18 p.","startPage":"292","endPage":"309","ipdsId":"IP-087567","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":347957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Jamaica","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-77.5696,18.49053],[-76.89662,18.40087],[-76.36536,18.1607],[-76.19966,17.88687],[-76.90256,17.86824],[-77.20634,17.70112],[-77.76602,17.8616],[-78.33772,18.22597],[-78.21773,18.45453],[-77.79736,18.52422],[-77.5696,18.49053]]]},\"properties\":{\"name\":\"Jamaica\"}}]}","volume":"721","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd1be4b0531197b13c51","contributors":{"authors":[{"text":"Cochran, William J.","contributorId":199373,"corporation":false,"usgs":false,"family":"Cochran","given":"William J.","affiliations":[],"preferred":false,"id":718849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spotila, James A.","contributorId":199374,"corporation":false,"usgs":false,"family":"Spotila","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prince, Philip S.","contributorId":199375,"corporation":false,"usgs":false,"family":"Prince","given":"Philip","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":718851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":5301,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan J.","email":"rmcaleer@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":718848,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193022,"text":"70193022 - 2017 - Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs","interactions":[],"lastModifiedDate":"2017-11-07T12:15:19","indexId":"70193022","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs","docAbstract":"<p><span>The egg yolk precursor protein vitellogenin is widely used as a biomarker of estrogen exposure in male fish. However, standardized methodology is lacking and little is known regarding the reproducibility of results among laboratories using different equipment, reagents, protocols, and data analysis programs. To address this data gap we tested the reproducibility across laboratories to evaluate vitellogenin gene (</span><i>vtg</i><span>) expression and assessed the value of using a freely available software data analysis program. Samples collected from studies of male fathead minnows (</span><i>Pimephales promelas</i><span>) exposed to 17α-ethinylestradiol (EE2) and minnows exposed to processed wastewater effluent were evaluated for<span>&nbsp;</span></span><i>vtg</i><span><span>&nbsp;</span>expression in 4 laboratories. Our results indicate reasonable consistency among laboratories if the free software for expression analysis LinRegPCR is used, with 3 of 4 laboratories detecting<span>&nbsp;</span></span><i>vtg</i><span><span>&nbsp;</span>in fish exposed to 5 ng/L EE2 (</span><i>n </i><span>= 5). All 4 laboratories detected significantly increased<span>&nbsp;</span></span><i>vtg</i><span><span>&nbsp;</span>levels in 15 male fish exposed to wastewater effluent compared with 15 male fish held in a control stream. Finally, we were able to determine that the source of high interlaboratory variability from complementary deoxyribonucleic acid (cDNA) to quantitative polymerase chain reaction (qPCR) analyses was the expression analysis software unique to each real-time qPCR machine. We successfully eliminated the interlaboratory variability by reanalyzing raw fluorescence data with independent freeware, which yielded cycle thresholds and polymerase chain reaction (PCR) efficiencies that calculated results independently of proprietary software. Our results suggest that laboratories engaged in monitoring programs should validate their PCR protocols and analyze their gene expression data following the guidelines established in the present study for all gene expression biomarkers.<span>&nbsp;</span></span></p>","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.3885","usgsCitation":"Jastrow, A., Gordon, D.A., Auger, K.M., Punska, E.C., Arcaro, K.F., Keteles, K., Winkelman, D.L., Lattier, D., Biales, A., and Lazorchak, J.M., 2017, Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs: Environmental Toxicology and Chemistry, v. 36, no. 1, p. 3102-3107, https://doi.org/10.1002/etc.3885.","productDescription":"6 p.","startPage":"3102","endPage":"3107","ipdsId":"IP-080787","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469366,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5894818","text":"External Repository"},{"id":348367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-20","publicationStatus":"PW","scienceBaseUri":"5a07e84be4b09af898c8cb42","contributors":{"authors":[{"text":"Jastrow, Aaron","contributorId":200067,"corporation":false,"usgs":false,"family":"Jastrow","given":"Aaron","affiliations":[],"preferred":false,"id":720892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gordon, Denise A.","contributorId":200068,"corporation":false,"usgs":false,"family":"Gordon","given":"Denise","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auger, Kasie M.","contributorId":200069,"corporation":false,"usgs":false,"family":"Auger","given":"Kasie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Punska, Elizabeth C.","contributorId":200070,"corporation":false,"usgs":false,"family":"Punska","given":"Elizabeth","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":720895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arcaro, Kathleen F.","contributorId":200071,"corporation":false,"usgs":false,"family":"Arcaro","given":"Kathleen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":720896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keteles, Kristen","contributorId":200072,"corporation":false,"usgs":false,"family":"Keteles","given":"Kristen","email":"","affiliations":[],"preferred":false,"id":720897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lattier, David","contributorId":200073,"corporation":false,"usgs":false,"family":"Lattier","given":"David","email":"","affiliations":[],"preferred":false,"id":720898,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Biales, Adam","contributorId":200074,"corporation":false,"usgs":false,"family":"Biales","given":"Adam","email":"","affiliations":[],"preferred":false,"id":720899,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lazorchak, James M.","contributorId":14750,"corporation":false,"usgs":true,"family":"Lazorchak","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720900,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70193410,"text":"70193410 - 2017 - Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change","interactions":[],"lastModifiedDate":"2017-11-13T11:02:58","indexId":"70193410","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change","docAbstract":"<p><span>With growing demand and highly variable inter-annual water supplies, California’s water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as “lowest of the low” and “highest of the high” anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm</span><sup>3</sup><span>) in the lowest of the low scenario and decreased 0.8 Bm</span><sup>3</sup><span><span>&nbsp;</span>in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm</span><sup>3</sup><span>), high agricultural expansion (+4.6 Bm</span><sup>3</sup><span>), and high urbanization (+2.1 Bm</span><sup>3</sup><span>) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0187181","usgsCitation":"Wilson, T., Sleeter, B.M., and Cameron, D.R., 2017, Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change: PLoS ONE, v. 12, no. 10, p. 1-21, https://doi.org/10.1371/journal.pone.0187181.","productDescription":"e0187181; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-085977","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0187181","text":"Publisher Index 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,{"id":70197123,"text":"70197123 - 2017 - The relative effectiveness of empirical and physical models for simulating the dense undercurrent of pyroclastic flows under different emplacement conditions","interactions":[],"lastModifiedDate":"2018-05-17T16:41:43","indexId":"70197123","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"The relative effectiveness of empirical and physical models for simulating the dense undercurrent of pyroclastic flows under different emplacement conditions","docAbstract":"<p><span>High concentration pyroclastic density currents (PDCs) are hot avalanches of volcanic rock and gas and are among the most destructive volcanic hazards due to their speed and mobility. Mitigating the risk associated with these flows depends upon accurate forecasting of possible impacted areas, often using empirical or physical models. TITAN2D, VolcFlow, LAHARZ, and Δ</span><i>H/L</i><span><span>&nbsp;</span>or energy cone models each employ different rheologies or empirical relationships and therefore differ in appropriateness of application for different types of mass flows and topographic environments. This work seeks to test different statistically- and physically-based models against a range of PDCs of different volumes, emplaced under different conditions, over different topography in order to test the relative effectiveness, operational aspects, and ultimately, the utility of each model for use in hazard assessments. The purpose of this work is not to rank models, but rather to understand the extent to which the different modeling approaches can replicate reality in certain conditions, and to explore the dynamics of PDCs themselves. In this work, these models are used to recreate the inundation areas of the dense-basal undercurrent of all 13 mapped, land-confined, Soufrière Hills Volcano dome-collapse PDCs emplaced from 1996 to 2010 to test the relative effectiveness of different computational models. Best-fit model results and their input parameters are compared with results using observation- and deposit-derived input parameters. Additional comparison is made between best-fit model results and those using empirically-derived input parameters from the FlowDat global database, which represent “forward” modeling simulations as would be completed for hazard assessment purposes. Results indicate that TITAN2D is able to reproduce inundated areas well using flux sources, although velocities are often unrealistically high. VolcFlow is also able to replicate flow runout well, but does not capture the lateral spreading in distal regions of larger-volume flows. Both models are better at reproducing the inundated area of single-pulse, valley-confined, smaller-volume flows than sustained, highly unsteady, larger-volume flows, which are often partially unchannelized. The simple rheological models of TITAN2D and VolcFlow are not able to recreate all features of these more complex flows. LAHARZ is fast to run and can give a rough approximation of inundation, but may not be appropriate for all PDCs and the designation of starting locations is difficult. The Δ</span><i>H/L</i><span><span>&nbsp;</span>cone model is also very quick to run and gives reasonable approximations of runout distance, but does not inherently model flow channelization or directionality and thus unrealistically covers all interfluves. Empirically-based models like LAHARZ and Δ</span><i>H/L</i><span><span>&nbsp;</span>cones can be quick, first-approximations of flow runout, provided a database of similar flows, e.g., FlowDat, is available to properly calculate coefficients or Δ</span><i>H/L</i><span>. For hazard assessment purposes, geophysical models like TITAN2D and VolcFlow can be useful for producing both scenario-based or probabilistic hazard maps, but must be run many times with varying input parameters. LAHARZ and Δ</span><i>H/L</i><span><span>&nbsp;</span>cones can be used to produce simple modeling-based hazard maps when run with a variety of input volumes, but do not explicitly consider the probability of occurrence of different volumes. For forward modeling purposes, the ability to derive potential input parameters from global or local databases is crucial, though important input parameters for VolcFlow cannot be empirically estimated. Not only does this work provide a useful comparison of the operational aspects and behavior of various models for hazard assessment, but it also enriches conceptual understanding of the dynamics of the PDCs themselves.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2017.00083","usgsCitation":"Ogburn, S.E., and Calder, E.S., 2017, The relative effectiveness of empirical and physical models for simulating the dense undercurrent of pyroclastic flows under different emplacement conditions: Frontiers in Earth Science, v. 5, p. 1-26, https://doi.org/10.3389/feart.2017.00083.","productDescription":"Article 83; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-087176","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2017.00083","text":"Publisher Index Page"},{"id":354292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5afee7c6e4b0da30c1bfc36a","contributors":{"authors":[{"text":"Ogburn, Sarah E. 0000-0002-4734-2118","orcid":"https://orcid.org/0000-0002-4734-2118","contributorId":204751,"corporation":false,"usgs":true,"family":"Ogburn","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":735757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calder, Eliza S","contributorId":205018,"corporation":false,"usgs":false,"family":"Calder","given":"Eliza","email":"","middleInitial":"S","affiliations":[{"id":37023,"text":"School of Geosciences, University of Edinburgh, Edinburgh, U.K","active":true,"usgs":false}],"preferred":false,"id":735758,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191086,"text":"sir20175113 - 2017 - Suspended sediment, turbidity, and stream water temperature in the Sauk River Basin, western Washington, water years 2012-16","interactions":[],"lastModifiedDate":"2017-11-08T11:26:15","indexId":"sir20175113","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5113","title":"Suspended sediment, turbidity, and stream water temperature in the Sauk River Basin, western Washington, water years 2012-16","docAbstract":"<p class=\"p1\">The Sauk River is a federally designated Wild and Scenic River that drains a relatively undisturbed landscape along the western slope of the North Cascade Mountain Range, Washington, which includes the glaciated volcano, Glacier Peak. Naturally high sediment loads characteristic of basins draining volcanoes like Glacier Peak make the Sauk River a dominant contributor of sediment to the downstream main stem river, the Skagit River. Additionally, the Sauk River serves as important spawning and rearing habitat for several salmonid species in the greater Skagit River system. Because of the importance of sediment to morphology, flow-conveyance, and ecosystem condition, there is interest in understanding the magnitude and timing of suspended sediment and turbidity from the Sauk River system and its principal tributaries, the White Chuck and Suiattle Rivers, to the Skagit River.</p><p class=\"p1\">Suspended-sediment measurements, turbidity data, and water temperature data were collected at two U.S. Geological Survey streamgages in the upper and middle reaches of the Sauk River over a 4-year period extending from October 2011 to September 2015, and at a downstream location in the lower river for a 5-year period extending from October 2011 to September 2016. Over the collective 5-year study period, mean annual suspended-sediment loads at the three streamgages on the upper, middle, and lower Sauk River streamgages were 94,200 metric tons (t), 203,000 t, and 940,000 t streamgages, respectively. Fine (smaller than 0.0625 millimeter) total suspended-sediment load averaged 49 percent at the upper Sauk River streamgage, 42 percent at the middle Sauk River streamgage, and 34 percent at the lower Sauk River streamgage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175113","collaboration":"Prepared in cooperation with Sauk-Suiattle Indian Tribe","usgsCitation":"Jaeger, K.L., Curran, C.A., Anderson, S.W., Morris, S.T., Moran, P.W., and Reams, K.A., 2017, Suspended sediment, turbidity, and stream water temperature in the Sauk River Basin, Washington, water years 2012–16: U.S. Geological Survey Scientific Investigations Report 2017–5113, 47 p., https://doi.org/10.3133/sir20175113.","productDescription":"Report: vii, 47 p.; Appendix; Data Release","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-087993","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":347907,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5113/sir20175113.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5113"},{"id":347906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5113/coverthb.jpg"},{"id":347985,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77S7MNB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Suspended sediment and water temperature ​data, Sauk River, Washington, water years 2012–16"},{"id":348066,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5113/sir20175113_appendixa.xlsx","text":"Appendix A","size":"14 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017-5113 Appendix A"}],"country":"United States","state":"Washington","otherGeospatial":"Sauk River, Suiattle 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Salmon<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix A. Particle-Size Distribution for Suspended-Sediment Samples Collected at Three Streamgages on the Sauk River, Western Washington, 2012–14<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-01","noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","scienceBaseUri":"59fadd1fe4b0531197b13c75","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506 kjaeger@usgs.gov","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":199335,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","email":"kjaeger@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":107001,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morris, Scott T.","contributorId":199336,"corporation":false,"usgs":false,"family":"Morris","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":18052,"text":"Sauk-Suiattle Indian Tribe","active":true,"usgs":false}],"preferred":false,"id":711121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reams, Katherine A. 0000-0001-7468-7026 kreams@usgs.gov","orcid":"https://orcid.org/0000-0001-7468-7026","contributorId":199337,"corporation":false,"usgs":true,"family":"Reams","given":"Katherine","email":"kreams@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192621,"text":"70192621 - 2017 - Potential for spatial displacement of Cook Inlet beluga whales by anthropogenic noise in critical habitat","interactions":[],"lastModifiedDate":"2017-11-10T11:10:24","indexId":"70192621","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Potential for spatial displacement of Cook Inlet beluga whales by anthropogenic noise in critical habitat","docAbstract":"<p class=\"abstract_block\">The population of beluga whales in Cook Inlet, Alaska, USA, declined by nearly half in the mid-1990s, primarily from an unsustainable harvest, and was listed as endangered in 2008. In 2014, abundance was ~340 whales, and the population trend during 1999-2014 was -1.3% yr<sup>-1</sup>. Cook Inlet beluga whales are particularly vulnerable to anthropogenic impacts, and noise that has the potential to reduce communication and echolocation range considerably has been documented in critical habitat; thus, noise was ranked as a high potential threat in the Cook Inlet beluga Recovery Plan. The current recovery strategy includes research on effects of threats potentially limiting recovery, and thus we examined the potential impact of anthropogenic noise in critical habitat, specifically, spatial displacement. Using a subset of data on anthropogenic noise and beluga detections from a 5 yr acoustic study, we evaluated the influence of noise events on beluga occupancy probability. We used occupancy models, which account for factors that affect detection probability when estimating occupancy, the first application of these models to examine the potential impacts of anthropogenic noise on marine mammal behavior. Results were inconclusive, primarily because beluga detections were relatively infrequent. Even though noise metrics (sound pressure level and noise duration) appeared in high-ranking models as covariates for occupancy probability, the data were insufficient to indicate better predictive ability beyond those models that only included environmental covariates. Future studies that implement protocols designed specifically for beluga occupancy will be most effective for accurately estimating the effect of noise on beluga displacement.</p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00786","usgsCitation":"Small, R.J., Brost, B.M., Hooten, M., Castellote, M., and Mondragon, J., 2017, Potential for spatial displacement of Cook Inlet beluga whales by anthropogenic noise in critical habitat: Endangered Species Research, v. 32, p. 43-57, https://doi.org/10.3354/esr00786.","productDescription":"15 p.","startPage":"43","endPage":"57","ipdsId":"IP-070647","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00786","text":"Publisher Index Page"},{"id":348568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.46777343749997,\n              58.95000823335702\n            ],\n            [\n              -149.23828125,\n              58.95000823335702\n            ],\n            [\n              -149.23828125,\n              61.543641475549954\n            ],\n            [\n              -154.46777343749997,\n              61.543641475549954\n            ],\n            [\n              -154.46777343749997,\n              58.95000823335702\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8c7e4b09af898c860e8","contributors":{"authors":[{"text":"Small, Robert J.","contributorId":171486,"corporation":false,"usgs":false,"family":"Small","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castellote, Manuel","contributorId":200241,"corporation":false,"usgs":false,"family":"Castellote","given":"Manuel","email":"","affiliations":[],"preferred":false,"id":721569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mondragon, Jeffrey","contributorId":200242,"corporation":false,"usgs":false,"family":"Mondragon","given":"Jeffrey","affiliations":[],"preferred":false,"id":721570,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70195202,"text":"70195202 - 2017 - Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe","interactions":[],"lastModifiedDate":"2018-02-07T12:41:48","indexId":"70195202","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe","docAbstract":"<p><span>Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as occlusion, may be mitigated by scanning target areas from several positions, increasing the chance that any given area will fall within the scanner’s line-of-sight from at least one position. Because TLS collections are often employed in remote regions where the scope of sampling is limited by logistical factors such as time and battery power, it is important to design field protocols which maximize efficiency and support increased quantity and quality of the data collected. This study informs researchers and practitioners seeking to optimize TLS sampling methods for vegetation monitoring in dryland ecosystems through three analyses. First, we quantify the 2D extent of occluded regions based on the range from single scan positions. Second, we measure the efficacy of additional scan positions on the reduction of 2D occluded regions (area) using progressive configurations of scan positions in 1&nbsp;ha plots. Third, we test the reproducibility of 3D sampling yielded by a 5-scan/ha sampling methodology using redundant sets of scans. Analyses were performed using measurements at analysis scales of 5 to 50&nbsp;cm across the 1-ha plots, and we considered plots in grass and shrub-dominated communities separately. In grass-dominated plots, a center-scan configuration and 5&nbsp;cm pixel size sampled at least 90% of the area up to 18&nbsp;m away from the scanner. In shrub-dominated plots, sampling at least 90% of the area was only achieved within a distance of 12&nbsp;m. We found that 3 and 5&nbsp;scans/ha are needed to sample at least ~&nbsp;70% of the total area (1&nbsp;ha) in the grass and shrub-dominated plots, respectively, using 5&nbsp;cm pixels to measure sampling presence-absence. The reproducibility of 3D sampling provided by a 5 position scan layout across 1-ha plots was 50% (shrub) and 70% (grass) using a 5-cm voxel size, whereas at the 50-cm voxel scale, reproducibility of sampling was nearly 100% for all plot types. Future studies applying TLS in similar dryland environments for vegetation monitoring may use our results as a guide to efficiently achieve sampling coverage and reproducibility in datasets.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-6300-0","usgsCitation":"Anderson, K.E., Glenn, N., Spaete, L., Shinneman, D.J., Pilliod, D.S., Arkle, R., McIlroy, S., and Derryberry, D.R., 2017, Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe: Environmental Monitoring and Assessment, v. 189, p. 1-12, https://doi.org/10.1007/s10661-017-6300-0.","productDescription":"Article 578; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-083243","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":351240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Morley Nelson Snake River Birds of Prey National Conservation Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.60064697265625,\n              42.88602714832883\n            ],\n            [\n              -115.78765869140625,\n              42.88602714832883\n            ],\n            [\n              -115.78765869140625,\n              43.46089378008257\n            ],\n            [\n              -116.60064697265625,\n              43.46089378008257\n            ],\n            [\n              -116.60064697265625,\n              42.88602714832883\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"189","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5a7c1e7ae4b00f54eb22933a","contributors":{"authors":[{"text":"Anderson, Kyle E.","contributorId":198237,"corporation":false,"usgs":false,"family":"Anderson","given":"Kyle","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":727416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Nancy","contributorId":181558,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","affiliations":[],"preferred":false,"id":727415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spaete, Lucas","contributorId":169444,"corporation":false,"usgs":false,"family":"Spaete","given":"Lucas","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":727417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":149254,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","email":"dpilliod@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arkle, Robert 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":149893,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","email":"rarkle@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727419,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":169446,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727420,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Derryberry, DeWayne R.","contributorId":198239,"corporation":false,"usgs":false,"family":"Derryberry","given":"DeWayne","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":727421,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193949,"text":"70193949 - 2017 - Detecting spatial patterns of rivermouth processes using a geostatistical framework for near-real-time analysis","interactions":[],"lastModifiedDate":"2017-11-16T14:50:03","indexId":"70193949","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Detecting spatial patterns of rivermouth processes using a geostatistical framework for near-real-time analysis","docAbstract":"<p><span>This paper proposes a geospatial analysis framework and software to interpret water-quality sampling data from towed undulating vehicles in near-real time. The framework includes data quality assurance and quality control processes, automated kriging interpolation along undulating paths, and local hotspot and cluster analyses. These methods are implemented in an interactive Web application developed using the Shiny package in the R programming environment to support near-real time analysis along with 2- and 3-D visualizations. The approach is demonstrated using historical sampling data from an undulating vehicle deployed at three rivermouth sites in Lake Michigan during 2011. The normalized root-mean-square error (NRMSE) of the interpolation averages approximately 10% in 3-fold cross validation. The results show that the framework can be used to track river plume dynamics and provide insights on mixing, which could be related to wind and seiche events.</span></p>","language":"English","publisher":"Elevier","doi":"10.1016/j.envsoft.2017.06.049","usgsCitation":"Collingsworth, P.D., Xu, W., Bailey, B., Carlson Mazur, M.L., Schaeffer, J., and Minsker, B., 2017, Detecting spatial patterns of rivermouth processes using a geostatistical framework for near-real-time analysis: Environmental Modelling and Software, v. 97, p. 72-85, https://doi.org/10.1016/j.envsoft.2017.06.049.","productDescription":"14 p.","startPage":"72","endPage":"85","ipdsId":"IP-071315","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2017.06.049","text":"Publisher Index Page"},{"id":349016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.67364501953124,\n              43.058854606434494\n            ],\n            [\n              -86.27288818359375,\n              43.058854606434494\n            ],\n            [\n              -86.27288818359375,\n              44.10533762552548\n            ],\n            [\n              -87.67364501953124,\n              44.10533762552548\n            ],\n            [\n              -87.67364501953124,\n              43.058854606434494\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"97","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d13","contributors":{"authors":[{"text":"Xu, Wenzhao","contributorId":200526,"corporation":false,"usgs":false,"family":"Xu","given":"Wenzhao","email":"","affiliations":[],"preferred":false,"id":722554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collingsworth, Paris D.","contributorId":145526,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Barbara","contributorId":200527,"corporation":false,"usgs":false,"family":"Bailey","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":722556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson Mazur, Martha L.","contributorId":95377,"corporation":false,"usgs":true,"family":"Carlson Mazur","given":"Martha","email":"","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":722557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaeffer, Jeff 0000-0003-3430-0872 jschaeffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3430-0872","contributorId":2041,"corporation":false,"usgs":true,"family":"Schaeffer","given":"Jeff","email":"jschaeffer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":722558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Minsker, Barbara","contributorId":200528,"corporation":false,"usgs":false,"family":"Minsker","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":722559,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192245,"text":"sir20175128 - 2017 - Simulation of groundwater flow and pumping scenarios for 1900–2050 near Mount Pleasant, South Carolina","interactions":[],"lastModifiedDate":"2020-08-25T16:37:11.720369","indexId":"sir20175128","displayToPublicDate":"2017-10-31T12:15:00","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":"2017-5128","title":"Simulation of groundwater flow and pumping scenarios for 1900–2050 near Mount Pleasant, South Carolina","docAbstract":"<p>Groundwater withdrawals from the Upper Cretaceous-age Middendorf aquifer in South Carolina have created a large, regional cone of depression in the potentiometric surface of the Middendorf aquifer in Charleston and Berkeley Counties, South Carolina. Groundwater-level declines of as much as 249 feet have been observed in wells over the past 125 years and are a result of groundwater use for public water supply, irrigation, and private industry. To address the concerns of users of the Middendorf aquifer, the U.S. Geological Survey, in cooperation with Mount Pleasant Waterworks (MPW), recalibrated an existing groundwater-flow model to incorporate additional groundwater-use and water-level data since 2008. This recalibration process consisted of a technique of parameter estimation that uses regularized inversion and employs “pilot points” for spatial hydraulic property characterization. The groundwater-flow system of the Coastal Plain physiographic province of South Carolina and parts of Georgia and North Carolina was simulated using the U.S. Geological Survey finite-difference computer code MODFLOW-2000.</p><p>After the model recalibration, the following six predictive water-management scenarios were created to simulate potential changes in groundwater flow and groundwater-level conditions in the Mount Pleasant, South Carolina, area: Scenario 1—maximize MPW reverse-osmosis plant capacity by increasing groundwater withdrawals from the Middendorf aquifer from 3.9 million gallons per day (Mgal/d), which was the amount withdrawn in 2015, to 8.58 Mgal/d; Scenario 2—same as Scenario 1, but with the addition of a 0.5 Mgal/d supply well in the Middendorf aquifer near Moncks Corner, South Carolina; Scenario 3—same as Scenario 1, but with the addition of a 1.5 Mgal/d supply well in the Middendorf aquifer near Moncks Corner, South Carolina; Scenario 4—maximize MPW well capacity by increasing withdrawals from the Middendorf aquifer from 3.9 Mgal/d (in 2015) to 10.16 Mgal/d; Scenario 5—minimize MPW surface-water purchase from the Charleston Water System by adding supply wells and increasing withdrawals from the Middendorf aquifer from 3.9 Mgal/d (in 2015) to 12.16 Mgal/d; and Scenario 6—same as Scenario 1, but with he addition of quarterly model stress periods to simulate seasonal variations in the groundwater withdrawals. Results from the simulations indicated further decline of groundwater levels creating cones of depressions near pumping wells in the Middendorf aquifer in the Mount Pleasant, South Carolina, area between 2015 and 2050 for all six scenarios.</p><p>Simulation results from Scenario 1 showed an average decline of about 150 feet in the groundwater levels of the MPW production wells. Simulated hydrographs for two area observation wells illustrate the gradual decline in groundwater levels with overall changes in water-level altitudes of –92 and –33 feet, respectively. Simulated groundwater altitudes at a hypothetical observation well located in the MPW well field declined 121 feet between 2015 and 2050.</p><p>Scenarios 2 and 3 have the same pumping rates as Scenario 1 for the MPW production wells; however, a single hypothetical pumping well was added in the Middendorf aquifer near the town of Moncks Corner, South Carolina. This hypothetical pumping well has a withdrawal rate of 0.5 Mgal/d for Scenario 2 and 1.5 Mgal/d for Scenario 3. A comparison to the 2050 Scenario 1 simulation indicates groundwater altitudes for Scenarios 2 and Scenario 3 are 3 feet and 8 feet lower, respectively, at the MPW production wells.</p><p>Scenario 4 simulates the maximum pumping capacity of 10.16 Mgal/d for the MPW network of production wells. Simulated 2050 groundwater altitudes for this simulation declined to –359 feet. Simulated hydrographs for two observation wells show groundwater-level declines of 116 and 41 feet, respectively. Simulated differences in groundwater altitudes at a hypothetical observation well located in the MPW well field indicate a water-level decline of 164 feet between 2015 and 2050.</p><p>Scenario 5 is a modification of Scenario 4 with the addition of two new MPW production wells. For this scenario, the MPW network of production wells were simulated the same as in Scenario 4, but withdrawals from the two new production wells were added in 2020. Simulated 2050 groundwater altitudes for this simulation declined to – 405 feet. Simulated hydrographs for two observation wells show groundwater-level declines of 143 and 51 feet, respectively. Simulated groundwater altitudes at a hypothetical observation well located in the MPW well field declined 199 feet between 2015 and 2050.</p><p>Scenario 6 is a modification of Scenario 1, in which 140 additional quarterly stress periods were added to simulate MPW seasonal demands. Simulated groundwater altitudes for Scenario 6 declined to –353 feet during 2050. For Scenario 6, simulated hydrographs for two observation wells and the hypothetical observation well show similar groundwater-level declines as seen in Scenario 1, but with seasonal fluctuations of as much as 56 feet in the hypothetical observation well.</p><p>Water budgets for the model area immediately surrounding Mount Pleasant, South Carolina, were calculated for 2015 and for 2050. The water budget for 2015 is equal for all of the scenarios because it represents the year prior to the hypothetical pumping beginning in 2016. The largest flow component in the 2015 water budget for the Mount Pleasant area is discharge to wells at a rate of 4.17 Mgal/d. Additionally, 0.23 Mgal/d flows laterally out of the Middendorf aquifer in this area of the model due to the regional horizontal hydraulic gradient. Flow into this zone consists predominantly of lateral flow within the Middendorf aquifer at 4.08 Mgal/d. Additionally, 0.02 Mgal/d is released into this zone from aquifer storage. Vertically, 0.06 Mgal/d flows down from the Middendorf confining unit located above the Middendorf aquifer, and 0.25 Mgal/d flows up from the Cape Fear confining unit below.</p><p>The largest flow component in the 2050 water budget for all six scenarios is discharge to wells in the Mount Pleasant area at rates between 8.89 and 12.47 Mgal/d. Flow into this zone consists mostly of lateral flow between 8.47 and 11.77 Mgal/d within the Middendorf aquifer. Between 0.003 and 0.46 Mgal/d is released into this zone from aquifer storage. Between 0.004 and 0.15 Mgal/d flows laterally out of this zone into adjacent areas of the Middendorf aquifer due to the regional horizontal hydraulic gradient. Finally, between 0.15 and 0.22 Mgal/d flows vertically into this zone from confining units above and below the Middendorf aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175128","collaboration":"Prepared in cooperation with Mount Pleasant Waterworks","usgsCitation":"Fine, J.M., Petkewich, M.D., and Campbell, B.G., 2017, Simulation of groundwater flow and pumping scenarios for 1900–2050 near Mount Pleasant, South Carolina (ver. 1.1, November 6, 2017): Scientific Investigations Report 2017–5128, 36 p.,  https://doi.org/10.3133/sir20175128.","productDescription":"Report: vi, 36 p.; 3 Data Releases","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088974","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":347690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5128/coverthb2.jpg"},{"id":377650,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FA07XD","text":"USGS data release","description":"USGS data release","linkHelpText":"2020 scenarios archive--MODFLOW-2000 data sets used in two predictive scenarios of groundwater flow and pumping (1900-2050) near Mount Pleasant, South Carolina"},{"id":347691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5128/sir20175128.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5128"},{"id":348296,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5128/versionHist.txt","size":"1.02","linkFileType":{"id":2,"text":"txt"}},{"id":348298,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S181FC","text":"USGS data release","description":"USGS data release","linkHelpText":"Original model archive--MODFLOW-2000 model data sets used in the simulation of Groundwater Flow and Pumping Scenarios for 1900-2050 near Mount Pleasant, South Carolina"},{"id":377837,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GZEE4E","text":"USGS data release","description":"USGS data release","linkHelpText":"2018 scenarios archive--MODFLOW-2000 and MODPATH model data sets used in scenarios of groundwater flow and pumping (1900-2500) near Mount Pleasant, South Carolina"}],"country":"United States","state":"South Carolina","city":"Mount Pleasant","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.892333984375,\n              31.914867503276223\n            ],\n            [\n              -79.134521484375,\n              33.18813395605041\n            ],\n            [\n              -78.5357666015625,\n              33.85673152928873\n            ],\n            [\n              -79.6783447265625,\n              34.80929324176267\n            ],\n            [\n              -80.694580078125,\n              34.82282272723702\n            ],\n            [\n              -82.2052001953125,\n              33.61919376817004\n            ],\n            [\n              -80.892333984375,\n              31.914867503276223\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted October 31, 2017; Version 1.1: November 6, 2017","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/water/southatlantic\" data-mce-href=\"https://www.usgs.gov/water/southatlantic\">South Atlantic Water Science Center</a><br> U.S. Geological Survey <br> 720 Gracern Road <br> Stephenson Center, Suite 129 <br> Columbia, SC 29210</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Simulation of Groundwater Flow</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-10-31","revisedDate":"2017-11-06","noUsgsAuthors":false,"publicationDate":"2017-10-31","publicationStatus":"PW","scienceBaseUri":"59f98ba3e4b0531197af9f89","contributors":{"authors":[{"text":"Fine, Jason M. 0000-0002-6386-256X jmfine@usgs.gov","orcid":"https://orcid.org/0000-0002-6386-256X","contributorId":2238,"corporation":false,"usgs":true,"family":"Fine","given":"Jason","email":"jmfine@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Bruce G. 0000-0003-4800-6674 bcampbel@usgs.gov","orcid":"https://orcid.org/0000-0003-4800-6674","contributorId":995,"corporation":false,"usgs":true,"family":"Campbell","given":"Bruce","email":"bcampbel@usgs.gov","middleInitial":"G.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714978,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193327,"text":"70193327 - 2017 - Deglacial sea level history of the East Siberian Sea and Chukchi Sea margins","interactions":[],"lastModifiedDate":"2017-10-31T15:13:15","indexId":"70193327","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Deglacial sea level history of the East Siberian Sea and Chukchi Sea margins","docAbstract":"<p><span class=\"pb_abstract\">Deglacial (12.8–10.7 ka) sea level history on the East Siberian continental shelf and upper continental slope was reconstructed using new geophysical records and sediment cores taken during Leg 2 of the 2014 SWERUS-C3 expedition. The focus of this study is two cores from Herald Canyon, piston core SWERUS-L2-4-PC1 (4-PC1) and multicore SWERUS-L2-4-MC1 (4-MC1), and a gravity core from an East Siberian Sea transect, SWERUS-L2-20-GC1 (20-GC1). Cores 4-PC1 and 20-GC were taken at 120 and 115 m of modern water depth, respectively, only a few meters above the global last glacial maximum (LGM;  ∼  24 kiloannum or ka) minimum sea level of  ∼  125–130 meters below sea level (m b.s.l.). Using calibrated radiocarbon ages mainly on molluscs for chronology and the ecology of benthic foraminifera and ostracode species to estimate paleodepths, the data reveal a dominance of river-proximal species during the early part of the Younger Dryas event (YD, Greenland Stadial GS-1) followed by a rise in river-intermediate species in the late Younger Dryas or the early Holocene (Preboreal) period. A rapid relative sea level rise beginning at roughly 11.4 to 10.8 ka ( ∼  400 cm of core depth) is indicated by a sharp faunal change and unconformity or condensed zone of sedimentation. Regional sea level at this time was about 108 m b.s.l. at the 4-PC1 site and 102 m b.s.l. at 20-GC1. Regional sea level near the end of the YD was up to 42–47 m lower than predicted by geophysical models corrected for glacio-isostatic adjustment. This discrepancy could be explained by delayed isostatic adjustment caused by a greater volume and/or geographical extent of glacial-age land ice and/or ice shelves in the western Arctic Ocean and adjacent Siberian land areas.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-13-1097-2017","usgsCitation":"Cronin, T.M., O’Regan, M., Pearce, C., Gemery, L., Toomey, M., and Semiletov, I., 2017, Deglacial sea level history of the East Siberian Sea and Chukchi Sea margins: Climate of the Past, v. 13, no. 9, p. 1097-1110, https://doi.org/10.5194/cp-13-1097-2017.","productDescription":"14 p.","startPage":"1097","endPage":"1110","ipdsId":"IP-083404","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":461367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-13-1097-2017","text":"Publisher Index Page"},{"id":347913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Chukchi Sea, East Siberian Sea","volume":"13","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-05","publicationStatus":"PW","scienceBaseUri":"59f98ba4e4b0531197af9f8d","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":718700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":718707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718704,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Semiletov, Igor","contributorId":197134,"corporation":false,"usgs":false,"family":"Semiletov","given":"Igor","email":"","affiliations":[{"id":24563,"text":"Tomsk Polytechnic University","active":true,"usgs":false},{"id":35519,"text":"Russian Academy Sciences, Vladivostok, Russia","active":true,"usgs":false}],"preferred":false,"id":718706,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189312,"text":"ds1061 - 2017 - Geochemistry of mercury and other constituents in subsurface sediment—Analyses from 2011 and 2012 coring campaigns, Cache Creek Settling Basin, Yolo County, California","interactions":[],"lastModifiedDate":"2017-11-01T09:57:23","indexId":"ds1061","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1061","title":"Geochemistry of mercury and other constituents in subsurface sediment—Analyses from 2011 and 2012 coring campaigns, Cache Creek Settling Basin, Yolo County, California","docAbstract":"<p>Cache Creek Settling Basin was constructed in 1937 to trap sediment from Cache Creek before delivery to the Yolo Bypass, a flood conveyance for the Sacramento River system that is tributary to the Sacramento–San Joaquin Delta. Sediment management options being considered by stakeholders in the Cache Creek Settling Basin include sediment excavation; however, that could expose sediments containing elevated mercury concentrations from historical mercury mining in the watershed. In cooperation with the California Department of Water Resources, the U.S. Geological Survey undertook sediment coring campaigns in 2011–12 (1) to describe lateral and vertical distributions of mercury concentrations in deposits of sediment in the Cache Creek Settling Basin and (2) to improve constraint of estimates of the rate of sediment deposition in the basin.</p><p>Sediment cores were collected in the Cache Creek Settling Basin, Yolo County, California, during October 2011 at 10 locations and during August 2012 at 5 other locations. Total core depths ranged from approximately 4.6 to 13.7 meters (15 to 45 feet), with penetration to about 9.1 meters (30 feet) at most locations. Unsplit cores were logged for two geophysical parameters (gamma bulk density and magnetic susceptibility); then, selected cores were split lengthwise. One half of each core was then photographed and archived, and the other half was subsampled. Initial subsamples from the cores (20-centimeter composite samples from five predetermined depths in each profile) were analyzed for total mercury, methylmercury, total reduced sulfur, iron speciation, organic content (as the percentage of weight loss on ignition), and grain-size distribution. Detailed follow-up subsampling (3-centimeter intervals) was done at six locations along an east-west transect in the southern part of the Cache Creek Settling Basin and at one location in the northern part of the basin for analyses of total mercury; organic content; and cesium-137, which was used for dating. This report documents site characteristics; field and laboratory methods; and results of the analyses of each core section and subsample of these sediment cores, including associated quality-assurance and quality-control data.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1061","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Arias, M.R., Alpers, C.N., Marvin-DiPasquale, M.C., Fuller, C.C., Agee, J.L., Sneed, Michelle, Morita, A.Y., and Salas, A.J., 2017, Geochemistry of mercury and other constituents in subsurface sediment—Analyses from 2011 and 2012 coring campaigns, Cache Creek Settling Basin, Yolo County, California: U.S. Geological Survey Data Series 1061, 150 p., https://doi.org/10.3133/ds1061.","productDescription":"vi, 150 p.","numberOfPages":"160","onlineOnly":"Y","ipdsId":"IP-066188","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":347824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1061/coverthb.jpg"},{"id":347825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1061/ds1061.pdf","text":"Report","size":"56.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1061"}],"country":"United States","state":"California","county":"Yolo County","otherGeospatial":"Cache Creek Settling Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.7333,\n              38.65\n            ],\n            [\n              -121.65,\n              38.65\n            ],\n            [\n              -121.65,\n              38.7333\n            ],\n            [\n              -121.7333,\n              38.7333\n            ],\n            [\n              -121.7333,\n              38.65\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, <a href=\"http://ca.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://ca.water.usgs.gov\">California Water Science Center</a><br> U.S. Geological Survey<br> 6000 J Street, Placer Hall<br> Sacramento, California 95819</p><p>http://ca.water.usgs.gov</p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>The 2011 Deep Core Drilling Campaign<br></li><li>The 2012 Deep Core Drilling Campaign<br></li><li>Coring Methods and Equipment<br></li><li>Calculation of Core Depths<br></li><li>Determination of Land-Surface Elevations at Coring Locations<br></li><li>Sediment-Core Processing<br></li><li>Laboratory Analysis<br></li><li>Coring Results<br></li><li>Graphical Core Descriptions<br></li><li>Laboratory Analysis Results<br></li><li>Summary<br></li><li>References<br></li><li>Appendixes 1–2<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2017-10-31","noUsgsAuthors":false,"publicationDate":"2017-10-31","publicationStatus":"PW","scienceBaseUri":"59f98bb3e4b0531197af9fdb","contributors":{"authors":[{"text":"Arias, Michelle R. 0000-0002-3467-6186 mrbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3467-6186","contributorId":199123,"corporation":false,"usgs":true,"family":"Arias","given":"Michelle","email":"mrbeyer@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":704096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":704098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":704099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agee, Jennifer L. 0000-0002-5964-5079 jlagee@usgs.gov","orcid":"https://orcid.org/0000-0002-5964-5079","contributorId":2586,"corporation":false,"usgs":true,"family":"Agee","given":"Jennifer","email":"jlagee@usgs.gov","middleInitial":"L.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":704100,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morita, Andrew Y. 0000-0002-8120-996X amorita@usgs.gov","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":1487,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","email":"amorita@usgs.gov","middleInitial":"Y.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704103,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salas, Antonia 0000-0002-5163-4105 asalas@usgs.gov","orcid":"https://orcid.org/0000-0002-5163-4105","contributorId":194433,"corporation":false,"usgs":true,"family":"Salas","given":"Antonia","email":"asalas@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704105,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193218,"text":"70193218 - 2017 - Origin of discrepancies between crater size-frequency distributions of coeval lunar geologic units via target property contrasts","interactions":[],"lastModifiedDate":"2018-11-01T14:41:00","indexId":"70193218","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Origin of discrepancies between crater size-frequency distributions of coeval lunar geologic units via target property contrasts","docAbstract":"<p><span>Recent work on dating Copernican-aged craters, using Lunar Reconnaissance Orbiter (LRO) Camera data, re-encountered a curious discrepancy in crater size-frequency distribution (CSFD) measurements that was observed, but not understood, during the Apollo era. For example, at Tycho, Copernicus, and Aristarchus craters, CSFDs of impact melt deposits give significantly younger relative and absolute model ages (AMAs) than impact ejecta blankets, although these two units formed during one impact event, and would ideally yield coeval ages at the resolution of the CSFD technique. We investigated the effects of contrasting target properties on CSFDs and their resultant relative and absolute model ages for coeval lunar impact melt and ejecta units. We counted craters with diameters through the transition from strength- to gravity-scaling on two large impact melt deposits at Tycho and King craters, and we used pi-group scaling calculations to model the effects of differing target properties on final crater diameters for five different theoretical lunar targets. The new CSFD for the large King Crater melt pond bridges the gap between the discrepant CSFDs within a single geologic unit. Thus, the observed trends in the impact melt CSFDs support the occurrence of target property effects, rather than self-secondary and/or field secondary contamination. The CSFDs generated from the pi-group scaling calculations show that targets with higher density and effective strength yield smaller crater diameters than weaker targets, such that the relative ages of the former are lower relative to the latter. Consequently, coeval impact melt and ejecta units will have discrepant apparent ages. Target property differences also affect the resulting slope of the CSFD, with stronger targets exhibiting shallower slopes, so that the final crater diameters may differ more greatly at smaller diameters. Besides their application to age dating, the CSFDs may provide additional information about the characteristics of the target. For example, the transition diameter from strength- to gravity-scaling could provide a tool for investigating the relative strengths of different geologic units. The magnitude of the offset between the impact melt and ejecta isochrons may also provide information about the relative target properties and/or exposure/degradation ages of the two units. Robotic or human sampling of coeval units on the Moon could provide a direct test of the importance and magnitude of target property effects on CSFDs.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2016.11.040","usgsCitation":"Van der Bogert, C.H., Hiesinger, H., Dundas, C.M., Kruger, T., McEwen, A.S., Zanetti, M., and Robinson, M.S., 2017, Origin of discrepancies between crater size-frequency distributions of coeval lunar geologic units via target property contrasts: Icarus, v. 298, p. 49-63, https://doi.org/10.1016/j.icarus.2016.11.040.","productDescription":"14 p.","startPage":"49","endPage":"63","ipdsId":"IP-067339","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":347822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"298","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98babe4b0531197af9fb0","contributors":{"authors":[{"text":"Van der Bogert, Carolyn H.","contributorId":199120,"corporation":false,"usgs":false,"family":"Van der Bogert","given":"Carolyn","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":718237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hiesinger, Harald","contributorId":172686,"corporation":false,"usgs":false,"family":"Hiesinger","given":"Harald","email":"","affiliations":[{"id":27080,"text":"Institut für Planetologie, Westfälische Wilhelms-Universität, Münster","active":true,"usgs":false}],"preferred":false,"id":718238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":718236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kruger, T.","contributorId":199121,"corporation":false,"usgs":false,"family":"Kruger","given":"T.","email":"","affiliations":[],"preferred":false,"id":718239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":718241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zanetti, Michael","contributorId":199122,"corporation":false,"usgs":false,"family":"Zanetti","given":"Michael","email":"","affiliations":[],"preferred":false,"id":718240,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, Mark S.","contributorId":167665,"corporation":false,"usgs":false,"family":"Robinson","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":718242,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193123,"text":"70193123 - 2017 - Relative influences of climate change and human activity on the onshore distribution of polar bears","interactions":[],"lastModifiedDate":"2017-10-31T10:08:45","indexId":"70193123","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Relative influences of climate change and human activity on the onshore distribution of polar bears","docAbstract":"Climate change is altering habitat for many species, leading to shifts in distributions that can increase levels of human-wildlife conflict. To develop effective strategies for minimizing human-wildlife conflict, we must understand the relative influences that climate change and other factors have on wildlife distributions. Polar bears (Ursus maritimus) are increasingly using land during summer and autumn due to sea ice loss, leading to higher incidents of conflict and concerns for human safety. We sought to understand the relative influence of sea ice conditions, onshore habitat characteristics, and human-provisioned food attractants on the distribution and abundance of polar bears while on shore. We also wanted to determine how mitigation measures might reduce human-polar bear conflict associated with an anthropogenic food source. We built a Bayesian hierarchical model based on 14 years of aerial survey data to estimate the weekly number and distribution of polar bears on the coast of northern Alaska in autumn. We then used the model to predict how effective two management options for handling subsistence-harvested whale remains in the community of Kaktovik, Alaska might be. The distribution of bears on shore was most strongly influenced by the presence of whale carcasses and to a lesser extent sea ice and onshore habitat conditions. The numbers of bears on shore were related to sea ice conditions. The two management strategies for handling the whale carcasses reduced the estimated number of bears near Kaktovik by > 75%. By considering multiple factors associated with the onshore distribution and abundance of polar bears we discerned what role human activities played in where bears occur and how successful efforts to manage the whale carcasses might be for reducing human-polar bear conflict.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.08.005","usgsCitation":"Wilson, R.H., Regehr, E.V., St. Martin, M., Atwood, T.C., Peacock, E.L., Miller, S., and Divoky, G.J., 2017, Relative influences of climate change and human activity on the onshore distribution of polar bears: Biological Conservation, v. 214, p. 288-294, https://doi.org/10.1016/j.biocon.2017.08.005.","productDescription":"7 p.","startPage":"288","endPage":"294","ipdsId":"IP-081468","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469378,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2017.08.005","text":"Publisher Index Page"},{"id":438172,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74Q7S6Z","text":"USGS data release","linkHelpText":"Polar Bear Fall Coastal Survey Data from the Southern Beaufort Sea of Alaska, 2010-2013"},{"id":347803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.8955078125,\n              69.51914693717981\n            ],\n            [\n              -147.205810546875,\n              69.51914693717981\n            ],\n            [\n              -147.205810546875,\n              71.54926391392517\n            ],\n            [\n              -157.8955078125,\n              71.54926391392517\n            ],\n            [\n              -157.8955078125,\n              69.51914693717981\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"214","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98baee4b0531197af9fc1","contributors":{"authors":[{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":718060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":718061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St. Martin, Michelle","contributorId":150114,"corporation":false,"usgs":false,"family":"St. Martin","given":"Michelle","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":718062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peacock, Elizabeth L. 0000-0001-7279-0329 lpeacock@usgs.gov","orcid":"https://orcid.org/0000-0001-7279-0329","contributorId":3361,"corporation":false,"usgs":true,"family":"Peacock","given":"Elizabeth","email":"lpeacock@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":718063,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Susanne","contributorId":50955,"corporation":false,"usgs":false,"family":"Miller","given":"Susanne","email":"","affiliations":[{"id":13235,"text":"U.S. Fish and Wildlife Service, Marine Mammals Management","active":true,"usgs":false}],"preferred":false,"id":718064,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Divoky, George J.","contributorId":100912,"corporation":false,"usgs":false,"family":"Divoky","given":"George","email":"","middleInitial":"J.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":718065,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70188629,"text":"ds1054 - 2017 - Database for geologic maps of pyroclastic-flow and related deposits of the 1980 eruptions of Mount St. Helens, Washington","interactions":[],"lastModifiedDate":"2018-04-09T09:47:30","indexId":"ds1054","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1054","title":"Database for geologic maps of pyroclastic-flow and related deposits of the 1980 eruptions of Mount St. Helens, Washington","docAbstract":"<p>This publication releases digital versions of the geologic maps in U.S. Geological Survey Miscellaneous Investigations Map 1950 (USGS I-1950), “Geologic maps of pyroclastic-flow and related deposits of the 1980 eruptions of Mount St. Helens, Washington” (Kuntz, Rowley, and MacLeod, 1990) (<a href=\"https://pubs.er.usgs.gov/publication/i1950\" target=\"blank\" data-mce-href=\"../publication/i1950\">https://pubs.er.usgs.gov/publication/i1950</a>). The 1980 Mount St. Helens eruptions on May 18, May 25, June 12, July 22, August 7, and October 16–18 produced pyroclastic-flow and related deposits. The distribution and morphology of these deposits, as determined from extensive field studies and examination of vertical aerial photographs, are shown on four maps in I-1950 (maps A–D) on two map sheets. Map A shows the May 18, May 25, and June 12 deposits; map B shows the July 22 deposits; map C shows the August 7 deposits; and map D shows the October 16–18 deposits. No digital geospatial versions of the geologic data were made available at the time of publication of the original maps. This data release consists of attributed vector features, data tables, and the cropped and georeferenced scans from which the features were digitized, in order to enable visualization and analysis of these data in GIS software. This data release enables users to digitally re-create the maps and description of map units of USGS I-1950; map sheet 1 includes text sections (Introduction, Physiography of Mount St. Helens at the time of the 1980 eruptions, Processes of the 1980 eruptions, Deposits of the 1980 eruptions, Limitations of the maps, Preparation of the maps, and References cited) and associated tables and figures that are not included in this data release.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1054","usgsCitation":"Furze, A.J., Bard, J.A., Robinson, J.E., Ramsey, D.W., Kuntz, M.A., Rowley, P.D., MacLoed, N.S., 2017, Database for Geologic Maps of Pyroclastic-Flow and Related Deposits of the 1980 Eruptions of Mount St. Helens, Washington: U.S. Geological Survey Data Series 1054, https://doi.org/10.3133/ds1054.","productDescription":"Geodatabase; Read Me","onlineOnly":"Y","ipdsId":"IP-081720","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":347931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":347698,"rank":1,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/1054/ds1054.zip","text":"Geodatabase","size":"11.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1054 Geodatabase"},{"id":347699,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/1054/ds1054_readme.txt","size":"11 KB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1054 ReadMe"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.29774475097655,\n              46.13987966342405\n            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J.","contributorId":194403,"corporation":false,"usgs":false,"family":"Furze","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bard, Joseph A. 0000-0003-3143-4007 jbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3143-4007","contributorId":5590,"corporation":false,"usgs":true,"family":"Bard","given":"Joseph","email":"jbard@usgs.gov","middleInitial":"A.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Joel jrobins@usgs.gov","contributorId":194404,"corporation":false,"usgs":true,"family":"Robinson","given":"Joel","email":"jrobins@usgs.gov","affiliations":[],"preferred":true,"id":703916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kuntz, Mel A. 0000-0001-8828-5474","orcid":"https://orcid.org/0000-0001-8828-5474","contributorId":6446,"corporation":false,"usgs":true,"family":"Kuntz","given":"Mel A.","affiliations":[],"preferred":false,"id":703918,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rowley, Peter D.","contributorId":27435,"corporation":false,"usgs":true,"family":"Rowley","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703919,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"MacLeod, Norman 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