{"pageNumber":"687","pageRowStart":"17150","pageSize":"25","recordCount":165855,"records":[{"id":70214521,"text":"70214521 - 2019 - Debris-flow monitoring and warning: Review and examples","interactions":[],"lastModifiedDate":"2020-09-30T14:30:29.965691","indexId":"70214521","displayToPublicDate":"2019-10-21T09:30:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Debris-flow monitoring and warning: Review and examples","docAbstract":"<p><span>Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ∼10</span><span>&nbsp;</span><span>km</span><sup>2</sup><span>&nbsp;and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15</span><span>&nbsp;</span><span>mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2019.102981","usgsCitation":"Hurlimann, M., Coviello, V., Bel, C., Guo, X., Berti, M., Graf, C., Hubl, J., Miyata, S., Smith, J.B., and Yin, H., 2019, Debris-flow monitoring and warning: Review and examples: Earth-Science Reviews, v. 199, 102981, 26 p., https://doi.org/10.1016/j.earscirev.2019.102981.","productDescription":"102981, 26 p.","ipdsId":"IP-112575","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459437,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2117/177770","text":"External Repository"},{"id":378905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"199","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hurlimann, Marcel","contributorId":241626,"corporation":false,"usgs":false,"family":"Hurlimann","given":"Marcel","email":"","affiliations":[{"id":48365,"text":"Department Division of Geotechnical Engineering and Geosciences, Department of Civil and Environmental Engineering UPC BarcelonaTECH, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":799791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coviello, Velio","contributorId":241627,"corporation":false,"usgs":false,"family":"Coviello","given":"Velio","email":"","affiliations":[{"id":48366,"text":"Faculty of Science and Technology, Free University of Bozen-Bolzano, Italy","active":true,"usgs":false}],"preferred":false,"id":799792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bel, Coraline","contributorId":241628,"corporation":false,"usgs":false,"family":"Bel","given":"Coraline","email":"","affiliations":[{"id":48367,"text":"Université Grenoble Alpes, Irstea, UR ETNA, St-Martin-d’Hères, France","active":true,"usgs":false}],"preferred":false,"id":799793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Xiaojun","contributorId":241629,"corporation":false,"usgs":false,"family":"Guo","given":"Xiaojun","email":"","affiliations":[{"id":48368,"text":"Key Laboratory of Mountain Surface Process and Hazards/Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China","active":true,"usgs":false}],"preferred":false,"id":799794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berti, Matteo","contributorId":241630,"corporation":false,"usgs":false,"family":"Berti","given":"Matteo","affiliations":[{"id":48369,"text":"Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Università di Bologna, Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":799795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graf, Christoph","contributorId":241631,"corporation":false,"usgs":false,"family":"Graf","given":"Christoph","email":"","affiliations":[{"id":34058,"text":"Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":799796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hubl, Johannes","contributorId":241632,"corporation":false,"usgs":false,"family":"Hubl","given":"Johannes","email":"","affiliations":[{"id":48370,"text":"Institute of Mountain Risk engineering, Department of Natural Hazards and Civil Engineering, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":799797,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miyata, Shusuke","contributorId":241633,"corporation":false,"usgs":false,"family":"Miyata","given":"Shusuke","email":"","affiliations":[{"id":48371,"text":"Disaster Prevention Research Institute, Kyoto University, Takayama, Japan","active":true,"usgs":false}],"preferred":false,"id":799798,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799799,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yin, Hsiao-Yuan","contributorId":241634,"corporation":false,"usgs":false,"family":"Yin","given":"Hsiao-Yuan","email":"","affiliations":[{"id":48373,"text":"Soil and Water Conservation Bureau, Council of Agriculture, Nantou, Taiwan","active":true,"usgs":false}],"preferred":false,"id":799800,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70211577,"text":"70211577 - 2019 - Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens","interactions":[],"lastModifiedDate":"2020-07-31T14:24:22.240415","indexId":"70211577","displayToPublicDate":"2019-10-21T09:19:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens","docAbstract":"<p><span>Macrophage aggregates (MA s) are focal accumulations of pigmented macrophages in the spleen and other tissues of fish. A central role of MA s is the clearance and destruction of degenerating cells and recycling of some cellular components. Macrophage aggregates also respond to chemical contaminants and infectious agents and may play a role in the adaptive immune response. Tissue damage or physiological stress can result in increased MA accumulation. As a result, MA s may be sensitive biomarkers of environmental stress in fish. Abundance of MA s in tissues has been reported in a variety of ways—most commonly as density, mean size, and relative area—but the utility of these estimates has not been compared. In this study, four different types of splenic MA abundance estimates (abundance score, density, relative area, and total volume) were compared in two fish populations (Striped Bass&nbsp;</span><i>Morone saxatilis<span>&nbsp;</span></i><span>and White Perch&nbsp;</span><i>M.&nbsp;americana<span>&nbsp;</span></i><span>) with a wide range in ages. Stereological estimates of total volume indicated an increase in MA abundance with spleen volume, which generally corresponded to fish age, and with splenic infections (mycobacteria or trematode parasites). Abundance scores were generally limited in the ability to detect changes in MA abundance by these factors, whereas density estimates were greatly influenced by changes in spleen volume. In some instances, densities declined while the total volume of MA s and spleen volume increased. Experimentally induced acute stress resulted in a decrease in spleen volume and an increase in MA density, although the total volume of MA s remained unchanged. Relative area estimates accounted for the size and number of MA s but not for changes in organ volume. Total volume is an absolute measure of MA abundance irrespective of changes in organ volume or patterns of accumulation and may provide an improved means of quantifying MA s in the spleens of fish.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/aah.10086","usgsCitation":"Matsche, M.A., Blazer, V., and Mazik, P.M., 2019, Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens: Journal of Aquatic Animal Health, v. 31, no. 4, p. 328-348, https://doi.org/10.1002/aah.10086.","productDescription":"21 p.","startPage":"328","endPage":"348","ipdsId":"IP-101730","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":376946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Choptank River, Nanticoke River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.2176513671875,\n              38.199338565983844\n            ],\n            [\n              -75.7891845703125,\n              38.199338565983844\n            ],\n            [\n              -75.7891845703125,\n              39.049052206453524\n            ],\n            [\n              -76.2176513671875,\n              39.049052206453524\n            ],\n            [\n              -76.2176513671875,\n              38.199338565983844\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":794675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":794677,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215430,"text":"70215430 - 2019 - Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption","interactions":[],"lastModifiedDate":"2020-10-20T13:12:18.157354","indexId":"70215430","displayToPublicDate":"2019-10-19T15:19:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption","docAbstract":"<p><span>The 1959 eruption of Kīlauea Iki on the Island of Hawai’i is a principal example of powerful Hawaiian fountaining. Over 36&nbsp;days (including repose periods), 16 fountaining episodes created a small cone, a downwind tephra blanket of approximately 0.003&nbsp;km</span><sup>3</sup><span>&nbsp;and a lava lake of about 0.04&nbsp;km</span><sup>3</sup><span>&nbsp;volume. During the explosive activity, the maximum fountain heights reached 600&nbsp;m. Based on a dataset of more than 450 tephra grain size samples, we present both a total grain size distribution (TGSD) of the entire downwind tephra deposit, and also TGSDs for two eruptive subunits (the opening and the closing stages). The opening stage was characterized by persistent fountaining over a period of 8&nbsp;days with fountain heights averaging ∼ 100&nbsp;m; in contrast, the closing stage was characterized by two short (hours-long) but powerful fountaining episodes (up to 600&nbsp;m). The significantly different fountaining intensities are reflected in the characteristics of the TGSDs. For the closing stages, we link bimodality of TGSDs to periods of simultaneous deposition of ballistics and fallout from the convective cloud, both of which are a function of the maximum fountain height. The 1959 Kīlauea Iki case study presents a well-constrained set of TGSD data linked with Hawaiian-style fountaining of two contrasting intensities and can be used as a valuable reference point for eruption source parameters in future modeling of pyroclast dispersal during Hawaiian fountaining eruptions.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1304-y","usgsCitation":"Mueller, S.B., Houghton, B.F., Swanson, D., Poret, M., and Fagents, S.A., 2019, Total grain size distribution of an intense Hawaiian fountaining event: Case study of the1959 Kīlauea Iki eruption: Bulletin of Volcanology, v. 81, 43, 13 p., https://doi.org/10.1007/s00445-019-1304-y.","productDescription":"43, 13 p.","ipdsId":"IP-102777","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.6103515625,\n              19.129599439736836\n            ],\n            [\n              -154.9896240234375,\n              19.129599439736836\n            ],\n            [\n              -154.9896240234375,\n              19.65810729872147\n            ],\n            [\n              -155.6103515625,\n              19.65810729872147\n            ],\n            [\n              -155.6103515625,\n              19.129599439736836\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"81","noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Mueller, Sebastian B","contributorId":243387,"corporation":false,"usgs":false,"family":"Mueller","given":"Sebastian","email":"","middleInitial":"B","affiliations":[{"id":48709,"text":"University of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":802178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":802179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Donald A. 0000-0002-1680-3591","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":229682,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","affiliations":[],"preferred":true,"id":802180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poret, Matthieu","contributorId":243388,"corporation":false,"usgs":false,"family":"Poret","given":"Matthieu","email":"","affiliations":[{"id":33971,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy","active":true,"usgs":false}],"preferred":false,"id":802181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagents, Sarah A.","contributorId":243389,"corporation":false,"usgs":false,"family":"Fagents","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":48709,"text":"University of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":802182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215421,"text":"70215421 - 2019 - Ecosystem size predicts social dynamics in recreational fisheries","interactions":[],"lastModifiedDate":"2020-10-19T20:16:26.631262","indexId":"70215421","displayToPublicDate":"2019-10-19T15:11:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem size predicts social dynamics in recreational fisheries","docAbstract":"Recreational fisheries are complex adaptive systems that are inherently difficult to manage due to a heterogeneous user group (consumptive vs. non-consumptive) that utilize patchily distributed resources on the landscape (lakes, rivers, coastlines).  There is a need to identify which system components can effectively predict and be used to manage nonlinear and cross-scale dynamics within these systems.  We examine how ecosystem size or waterbody size can be used to explain complicated and elusive angler-resource dynamics in recreational fisheries.  Waterbody size determined angler behavior among 48 Nebraska, U.S.A. waterbodies during an 11-year study period.  Angler behavior was often unique and nonlinear across waterbody sizes.  For example, anglers spent more time fishing and harvested more fish at larger waterbodies compared to smaller waterbodies.  Time fished increased across smaller waterbodies but reached a threshold at larger waterbodies.  The number of fish released increased as a function of waterbody size across smaller waterbodies but then plateaued.  Subtle changes in waterbody size caused abrupt changes in angler behavior—that is, waterbody size structures angler-resource dynamics in recreational fisheries.  We believe that including waterbody size, a simple and easily measured metric, in fisheries management will increase effectiveness of cross-scale actions and minimize unintended consequences for recreational fisheries.  Applying uniform management actions (e.g., harvest regulations) across small and large waterbodies may elicit contrasting angler-resource responses.  Waterbody size may also be useful for understanding angler typologies.  Based on our findings, we expect that ecosystem size is a prominent and valuable system component that will determine and explain coupled user-resource dynamics in other complex adaptive systems.","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ES-10961-240217","usgsCitation":"Kaemingk, M., Chizinski, C.J., Allen, C.R., and Pope, K.L., 2019, Ecosystem size predicts social dynamics in recreational fisheries: Ecology and Society, v. 24, no. 2, 17, 12 p., https://doi.org/10.5751/ES-10961-240217.","productDescription":"17, 12 p.","ipdsId":"IP-097509","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-10961-240217","text":"Publisher Index Page"},{"id":379532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kaemingk, M. A.","contributorId":243357,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M. A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":802131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chizinski, C. J.","contributorId":243358,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":802132,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":802134,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215418,"text":"70215418 - 2019 - Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016","interactions":[],"lastModifiedDate":"2023-01-19T16:16:25.05494","indexId":"70215418","displayToPublicDate":"2019-10-19T14:56:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016","docAbstract":"<p><span>Annual bottom trawl surveys were initiated in the 1970s in Laurentian Great Lakes Superior, Huron, Michigan and Ontario and in 1990 in Erie to provide annual assessments of the status and trends of prey fish communities. Native Cisco&nbsp;</span><i>Coregonus artedi</i><span>&nbsp;and Bloater&nbsp;</span><i>C. hoyi</i><span>&nbsp;dominated the prey fish community of Lake Superior. Prey fish communities in lakes Huron and Michigan were dominated by nonnative Rainbow Smelt&nbsp;</span><i>Osmerus mordax</i><span>&nbsp;and Alewife&nbsp;</span><i>Alosa pseudoharengus</i><span>&nbsp;for much of 1978-2016, but Bloater was an important species during the 1980-1990s and more recently has become the dominant prey species in these lakes. Alewife dominated the prey fish community of Lake Ontario during all 1978-2016. While nonnatives dominated the prey fish community in Lake Erie, native Emerald Shiner&nbsp;</span><i>Notropis atherinoides</i><span>&nbsp;was an important species and occasionally the dominant prey fish after the establishment of Round Goby&nbsp;</span><i>Neogobius melanostomus</i><span>&nbsp;in the late 1990s. During the 1980s-1990s&nbsp;</span><i>Bythotrephes cederstroemi, Dreissena polymorpha</i><span>, and&nbsp;</span><i>Dreissena bugensis</i><span>&nbsp;caused profound changes in Laurentian Great Lakes ecosystems and likely contributed to declines in fish community biomass in lakes Michigan and Huron. The impacts of these invaders were more muted in lakes Erie and Ontario. Lake Superior stands out as the Laurentian Great Lakes success story: Lake Trout&nbsp;</span><i>Salvelinus namaycush</i><span>&nbsp;was restored, and native prey fishes dominate and support a viable fishery. Although the abundance of Bloater has increased recently in lakes Huron and Michigan, recovery of native prey fishes remains uncertain. The absence of native species among the principal prey fish in Lake Ontario indicates a lack of progress in native fish recovery. Recovery of native prey fishes remains unclear in Lake Erie. The ever-changing state of the Laurentian Great Lakes caused by the impacts of invasive species and ongoing climate and ecosystem change will continue to challenge restoration of native fish communities in the 21st Century.</span></p>","language":"English","publisher":"Aquatic Ecosystem Health & Management Society","doi":"10.1080/14634988.2019.1674012","usgsCitation":"Gorman, O., 2019, Prey fish communities of the Laurentian Great Lakes: A cross-basin overview of status and trends based on bottom trawl surveys, 1978-2016: Aquatic Ecosystem Health & Management, v. 22, no. 3, p. 263-279, https://doi.org/10.1080/14634988.2019.1674012.","productDescription":"17 p.","startPage":"263","endPage":"279","ipdsId":"IP-107179","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":379531,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.59374999999999,\n              49.03786794532644\n            ],\n            [\n              -92.98828125,\n              46.98025235521883\n            ],\n            [\n              -90.263671875,\n              46.07323062540835\n            ],\n            [\n              -87.62695312499999,\n              46.195042108660154\n            ],\n            [\n              -88.41796875,\n              44.653024159812\n            ],\n            [\n              -88.505859375,\n              41.96765920367816\n            ],\n            [\n              -86.396484375,\n              41.64007838467894\n            ],\n            [\n              -85.95703125,\n              42.68243539838623\n            ],\n            [\n              -86.1328125,\n              45.089035564831036\n            ],\n            [\n              -84.0234375,\n              44.59046718130883\n            ],\n            [\n              -84.287109375,\n              43.26120612479979\n            ],\n            [\n              -83.671875,\n              41.57436130598913\n            ],\n            [\n              -82.177734375,\n              41.11246878918088\n            ],\n            [\n              -78.57421875,\n              42.74701217318067\n            ],\n            [\n              -75.76171875,\n              43.51668853502906\n            ],\n            [\n              -76.81640625,\n              44.465151013519616\n            ],\n            [\n              -79.013671875,\n              44.276671273775186\n            ],\n            [\n              -80.244140625,\n              45.82879925192134\n            ],\n            [\n              -83.49609375,\n              46.437856895024204\n            ],\n            [\n              -84.375,\n              47.517200697839414\n            ],\n            [\n              -83.671875,\n              48.16608541901253\n            ],\n            [\n              -86.923828125,\n              49.15296965617042\n            ],\n            [\n              -88.59374999999999,\n              49.03786794532644\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":802112,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70215417,"text":"70215417 - 2019 - Historical land use and land cover for assessing the northern Colorado Front Range urban landscape","interactions":[],"lastModifiedDate":"2020-10-20T13:15:57.557465","indexId":"70215417","displayToPublicDate":"2019-10-19T14:46:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2375,"text":"Journal of Maps","active":true,"publicationSubtype":{"id":10}},"title":"Historical land use and land cover for assessing the northern Colorado Front Range urban landscape","docAbstract":"We describe historical land-use and land-cover (LULC) maps for the northern Colorado urban Front Range. The Front Range urban landscape is diverse and interspersed with highly productive agriculture as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1 meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 38 detailed LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/17445647.2018.1548383","usgsCitation":"Drummond, M.A., Stier, M.P., and Diffendorfer, J., 2019, Historical land use and land cover for assessing the northern Colorado Front Range urban landscape: Journal of Maps, v. 15, no. 2, p. 89-93, https://doi.org/10.1080/17445647.2018.1548383.","productDescription":"5 p.","startPage":"89","endPage":"93","ipdsId":"IP-093283","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459446,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17445647.2018.1548383","text":"Publisher Index Page"},{"id":437298,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P995RGC9","text":"USGS data release","linkHelpText":"Data release for the Historical land use and land cover for assessing the northern Colorado Front Range urban landscape"},{"id":379530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Northern Colorado Front Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.49072265625,\n              39.317300373271024\n            ],\n            [\n              -104.501953125,\n              39.317300373271024\n            ],\n            [\n              -104.501953125,\n              40.9964840143779\n            ],\n            [\n              -105.49072265625,\n              40.9964840143779\n            ],\n            [\n              -105.49072265625,\n              39.317300373271024\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Drummond, Mark A. 0000-0001-7420-3503 madrummond@usgs.gov","orcid":"https://orcid.org/0000-0001-7420-3503","contributorId":3053,"corporation":false,"usgs":true,"family":"Drummond","given":"Mark","email":"madrummond@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":802109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stier, Michael P. 0000-0002-8518-9855 mpstier@usgs.gov","orcid":"https://orcid.org/0000-0002-8518-9855","contributorId":3121,"corporation":false,"usgs":true,"family":"Stier","given":"Michael","email":"mpstier@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":802110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":802111,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215416,"text":"70215416 - 2019 - Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae","interactions":[],"lastModifiedDate":"2020-10-19T19:40:15.940198","indexId":"70215416","displayToPublicDate":"2019-10-19T14:19:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1905,"text":"Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae","docAbstract":"Proxies that use changes in the composition of ecological communities to reconstruct temporal changes in an environmental covariate are commonly used in paleoclimatology and paleolimnology. Existing methods, such as weighted averaging and modern analog technique,\nrelate compositional data to the covariate in very simple ways, and different methods are seldom compared systematically. We present a new Bayesian model that better represents the underlying data and the complexity in the relationships between species’ abundances and a paleoenvironmental covariate. Using testate amoeba-based reconstructions of water-table depth as a test case, we systematically compare new and existing models in a cross-validation experiment on a large training dataset from North America. We then apply the different\nmodels to a new 7500-year record of testate amoeba assemblages from Caribou Bog in Maine and compare the resulting water-table depth reconstructions. We find that Bayesian models represent an improvement over existing methods in three key ways: more complete use of the underlying compositional data, full and meaningful treatment of uncertainty, and clear paths toward methodological improvements. Furthermore, we highlight how developing and systematically comparing methods leads to an improved understanding of the proxy system.\nThis paper focuses on testate amoebae and water-table depth, but the framework and ideas are widely applicable to other proxies based on compositional data.","language":"English","publisher":"SAGE Publications","doi":"10.1177/0959683619846969","usgsCitation":"Nolan, C., Tipton, J., Booth, R., Hooten, M., and Jackson, S., 2019, Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae: Holocene, v. 29, no. 8, p. 1350-1361, https://doi.org/10.1177/0959683619846969.","productDescription":"12 p.","startPage":"1350","endPage":"1361","ipdsId":"IP-098724","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0959683619846969","text":"Publisher Index 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   ],\n            [\n              -111.796875,\n              46.437856895024204\n            ],\n            [\n              -115.13671875,\n              46.437856895024204\n            ],\n            [\n              -115.13671875,\n              44.08758502824516\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nolan, Connor","contributorId":197051,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","affiliations":[],"preferred":false,"id":802104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":802105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Robert K.","contributorId":243345,"corporation":false,"usgs":false,"family":"Booth","given":"Robert K.","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":802106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":802107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Stephen 0000-0002-1487-4652","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":219995,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":802108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215415,"text":"70215415 - 2019 - Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","interactions":[],"lastModifiedDate":"2020-10-19T19:17:19.843075","indexId":"70215415","displayToPublicDate":"2019-10-19T14:12:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana","docAbstract":"Temperature and salinity and their interaction exert a major control on the life cycle of the eastern oyster (Crassostrea virginica), affecting reproduction, development, growth, and mortality. Quantifying specific temperature and salinity relationships on oyster growth and mortality has however proven difficult, with data suggesting potentially region-specific responses. Legacy and recent data from field tray studies from public oyster grounds in Barataria Bay and Breton Sound were used to estimate growth and mortality rates as a function of temperature and salinity. Previous studies conducted in Barataria Bay and Breton Sound reported differences in growth and mortality between the basins. In the present study, environmental conditions were synchronized to compare growth and mortality between basins at similar combinations of temperature and salinity. Results indicate that when temperature and salinity are the same (synchronized), seasonal oyster growth and mortality rates still differ between Barataria Bay and Breton Sound. Given the same salinity and temperature conditions, differences in growth and mortality rates between estuaries may persist due to differences in other environmental conditions (i.e., food quality and composition, hydrology, site history, salinity variation) or localized genetic adaptations to environmental conditions.","language":"English","publisher":"BioOne","doi":"10.2983/035.038.0212","usgsCitation":"Sehlinger, T., Lowe, M., LaPeyre, M.K., and Soniat, T., 2019, Differential effects of temperature and salinity on growth and mortality of oysters (Crassostrea virginica) in Barataria Bay and Breton Sound, Louisiana: Journal of Shellfish Research, v. 38, no. 2, p. 317-326, https://doi.org/10.2983/035.038.0212.","productDescription":"10 p.","startPage":"317","endPage":"326","ipdsId":"IP-105718","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":379528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Lousianna","otherGeospatial":"Barataria Bay and Brenton Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.8349609375,\n              28.714678586705976\n            ],\n            [\n              -89.033203125,\n              28.714678586705976\n            ],\n            [\n              -89.033203125,\n              30.32547125932808\n            ],\n            [\n              -90.8349609375,\n              30.32547125932808\n            ],\n            [\n              -90.8349609375,\n              28.714678586705976\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sehlinger, T.","contributorId":243342,"corporation":false,"usgs":false,"family":"Sehlinger","given":"T.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":802099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, M.R.","contributorId":243343,"corporation":false,"usgs":false,"family":"Lowe","given":"M.R.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":802100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soniat, T.M.","contributorId":243344,"corporation":false,"usgs":false,"family":"Soniat","given":"T.M.","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":802102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215413,"text":"70215413 - 2019 - A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","interactions":[],"lastModifiedDate":"2020-10-20T13:24:52.488251","indexId":"70215413","displayToPublicDate":"2019-10-19T14:01:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study","docAbstract":"Nutrient-reduction efforts have been undertaken in recent decades to mitigate the impacts of eutrophication in coastal and estuarine systems worldwide. To track progress in response to one of these efforts we use Generalized Additive Models (GAMs) to evaluate a diverse suite of water quality constituents over a 32-year period in the Chesapeake Bay, an estuary on the east coast of the United States. Model development included selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporating hydrologic variability via either river flow or salinity, and using interventions to model method or laboratory changes suspected to impact data. This approach, transferable to other systems, allows for evaluation of water quality data in a statistically rigorous way, while being suitable for application to many sites and variables. This enables consistent generation of annual updates, while providing a tool for developing insights to a range of management- and research-focused questions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.03.027","usgsCitation":"Murphy, R., Perry, E., Harcum, J., and Keisman, J.L., 2019, A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay Case Study: Environmental Modelling & Software, v. 118, 13 p., https://doi.org/10.1016/j.envsoft.2019.03.027.","productDescription":"13 p.","ipdsId":"IP-105288","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":379527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.40966796875,\n              36.756490329505176\n            ],\n            [\n              -75.5419921875,\n              36.756490329505176\n            ],\n            [\n              -75.5419921875,\n              39.57182223734374\n            ],\n            [\n              -77.40966796875,\n              39.57182223734374\n            ],\n            [\n              -77.40966796875,\n              36.756490329505176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Rebecca 0000-0003-3391-1823","orcid":"https://orcid.org/0000-0003-3391-1823","contributorId":199777,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":true,"id":802095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Elgin","contributorId":243340,"corporation":false,"usgs":false,"family":"Perry","given":"Elgin","affiliations":[{"id":48694,"text":"Statistics Consultant","active":true,"usgs":false}],"preferred":false,"id":802096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harcum, Jon","contributorId":243341,"corporation":false,"usgs":false,"family":"Harcum","given":"Jon","email":"","affiliations":[{"id":48695,"text":"Tetra Tech, Inc.","active":true,"usgs":false}],"preferred":false,"id":802097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keisman, Jennifer L. 0000-0001-6808-9193 jkeisman@usgs.gov","orcid":"https://orcid.org/0000-0001-6808-9193","contributorId":198107,"corporation":false,"usgs":true,"family":"Keisman","given":"Jennifer","email":"jkeisman@usgs.gov","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215412,"text":"70215412 - 2019 - Where was the 31 October 1895, Charleston, Missouri Earthquake?","interactions":[],"lastModifiedDate":"2020-10-20T13:27:29.499153","indexId":"70215412","displayToPublicDate":"2019-10-19T13:51:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Where was the 31 October 1895, Charleston, Missouri Earthquake?","docAbstract":"<p>We revisit the magnitude and location of the 31 October 1895 Charleston, Missouri earthquake, which is widely regarded to be the last M<sub>W</sub>6 or greater earthquake in the central United States. Although a recent study (Bakun et al., 2003) concluded that this earthquake was located in southern Illinois, over 100 km north of the traditionally inferred location near Charleston, Missouri, our analysis of exhaustively compiled macroseismic data supports the traditionally inferred location, with a preferred magnitude of M<sub>W</sub> ≈ 5.8, and preferred range of 5.4 to 6.1. Our preferred magnitude is derived from comparisons with intensity distributions from the 1925 M<sub>W</sub> = 6.2 Charlevoix, the 1944 M<sub>W</sub> = 5.8 Massena, and the 1968 M<sub>W</sub> = 5.3 southern Illinois earthquakes, which we also revisited in this study. Based on the distribution of liquefaction, reports of damage, and early aftershocks, we also explore possible rupture scenarios for the 1895 earthquake. Our preferred scenario involves unilateral rupture to the northeast on a (reactivated) northeast-striking fault (or faults) coinciding with structures associated with the western limb of the Reelfoot Rift, with an epicenter south-southeast of Charleston, Missouri. Our results support the conclusion that, within the Reelfoot Rift, elevated seismic hazard is not restricted to the New Madrid Seismic Zone (NMSZ) as conventionally defined but continues into the Charleston region in southeastern Missouri where faults associated with the western edge of the Reelfoot Rift appear favorably oriented for failure in the current stress regime.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180328","usgsCitation":"Martin, S.S., and Hough, S.E., 2019, Where was the 31 October 1895, Charleston, Missouri Earthquake?: Bulletin of the Seismological Society of America, v. 109, no. 4, p. 1479-1497, https://doi.org/10.1785/0120180328.","productDescription":"19 p.","startPage":"1479","endPage":"1497","ipdsId":"IP-107007","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":379526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Charleston","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.637451171875,\n              36.45884507478879\n            ],\n            [\n              -89.07714843749999,\n              36.45884507478879\n            ],\n            [\n              -89.07714843749999,\n              37.142803443716836\n            ],\n            [\n              -89.637451171875,\n              37.142803443716836\n            ],\n            [\n              -89.637451171875,\n              36.45884507478879\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"109","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Stacey S.","contributorId":187758,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":802093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":802094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215411,"text":"70215411 - 2019 - Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","interactions":[],"lastModifiedDate":"2020-10-20T13:30:40.254733","indexId":"70215411","displayToPublicDate":"2019-10-19T13:35:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada","docAbstract":"<p><span>Strike-slip faults commonly include extensional and contractional bends and stepovers, whereas rotational stepovers are less common. The Volcanic Tableland, Black Mountain, and River Spring areas (California and Nevada, USA) (hereafter referred to as the VBR region) straddle the transition from the dominantly NW-striking dextral faults that define the northwestern part of the eastern California shear zone into a rotational stepover characterized by dominantly NE-striking sinistral faults that define the southwestern Mina deflection. New detailed geologic mapping, structural studies, and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar geochronology across the VBR region allow us to calculate Pliocene to Pleistocene fault slip rates and test predictions for the kinematics of fault slip transfer into this rotational stepover. In the VBR, Mesozoic basement is nonconformably overlain by a Miocene sequence of rhyolite, dacite, and andesite volcanic rocks that yield&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages between 22.878 ± 0.051 Ma and 11.399 ± 0.041 Ma. Miocene rocks are unconformably overlain by an extensive sequence of Pliocene basalt and andesite lava flows and cinder cones that yield&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages between 3.606 ± 0.060 Ma and 2.996 ± 0.027 Ma. The Pliocene sequence is, in turn, unconformably overlain by Quaternary tuffs and sedimentary rocks. This sequence of rocks is cut by NS- to NW-striking normal faults across the Volcanic Tableland that transition northward into NS-striking normal faults across the Black Mountain area and that, in turn, transition northward into NW-striking dextral and NE-striking sinistral faults in the River Spring area. A range of geologic markers were used to measure offset across the faults in the VBR, and combined with the age of the markers, yield minimum ∼EW-extension rates of ∼0.5 mm/yr across the Volcanic Tableland and Black Mountain regions, and minimum NW-dextral slip and NE-sinistral slip rates of ∼0.7 and ∼0.3 mm/yr, respectively, across the River Spring region. In the River Spring area, our preferred minimum dextral slip and sinistral slip rates are 0.8–0.9 mm/yr and 0.7–0.9 mm/yr, respectively. We propose three kinematic fault slip models, two irrotational and one rotational, whereby the VBR region transfers a portion of dextral Owens Valley fault slip northwestward into the Mina deflection. In irrotational model 1, Owens Valley fault slip is partitioned into two components, one northeastward onto the White Mountain fault zone and one northwestward into the Volcanic Tableland. Slip from the two zones is then transferred northward into the southwestern Mina deflection. In irrotational model 2, Owens Valley fault slip is partitioned into three components, with the third component partitioned west-northwest onto the Sierra Nevada frontal fault zone. In the rotational model, predicted sinistral slip rates across the southwestern Mina deflection are at least 115% greater than our observed minimum slip rates, implying our minimum observed rates underestimate true sinistral slip rates. A comparison of summed geologic fault slip rates, parallel to motion of the Sierra Nevada block relative to the central Great Basin, from the Sierra Nevada northeastward across the VBR region and into western Nevada are the same as geodetic rates, if our assumptions about the geologic slip rate across the dextral White Mountain fault zone is correct.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01636.1","usgsCitation":"DeLano, K., Lee, J., Roper, R., and Calvert, A.T., 2019, Dextral, normal, and sinistral faulting across the eastern California shear zone-Mina deflection transition, California-Nevada: Geosphere, v. 15, no. 4, p. 1206-1239, https://doi.org/10.1130/GES01636.1.","productDescription":"34 p.","startPage":"1206","endPage":"1239","ipdsId":"IP-097991","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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 \"}}]}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"DeLano, Kevin","contributorId":243338,"corporation":false,"usgs":false,"family":"DeLano","given":"Kevin","email":"","affiliations":[{"id":48692,"text":"CWU student, now at California State Water Resources","active":true,"usgs":false}],"preferred":false,"id":802089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Jeffrey","contributorId":193437,"corporation":false,"usgs":false,"family":"Lee","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":802090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roper, Rachelle","contributorId":243339,"corporation":false,"usgs":false,"family":"Roper","given":"Rachelle","email":"","affiliations":[{"id":48693,"text":"Central Washington University student","active":true,"usgs":false}],"preferred":false,"id":802091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802092,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215420,"text":"70215420 - 2019 - A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene","interactions":[],"lastModifiedDate":"2020-10-19T18:27:55.952556","indexId":"70215420","displayToPublicDate":"2019-10-19T13:23:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene","docAbstract":"An 8-cm-thick black basaltic tephra with nine discrete normally graded beds is present in cores from a lake on Baker Island in southeastern Alaska. The estimated age of the tephra is 13,492 ± 237 cal yr BP. Although similar in age to the MEd tephra from the adjacent Mt. Edgecumbe Volcanic Field, this tephra is geochemically distinct. Black basaltic tephras recovered from two additional sites in southeastern Alaska, Heceta Island and the Gulf of Esquibel, are also geochemically distinct from the MEd tephra. The age of the tephra from Heceta Island is 14,609 ± 343 cal yr BP. Whereas the tephras recovered from Baker Island/Heceta Island/Gulf of Esquibel are geochemically distinct from each other, similarities in the ages of these tephras and the MEd tephra suggest a shared eruptive trigger, possibly crustal unloading caused by retreat of the Cordilleran Ice Sheet. The submerged Addington Volcanic Field on the continental shelf, which may have been subaerially exposed during the late Pleistocene, is a possible source for the southeastern Alaska tephras","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.154","usgsCitation":"Wilcox, P.S., Addison, J.A., Fowell, S.J., Baichtal, J., Severin, K., and Mann, D.H., 2019, A new set of basaltic tephras from southeastern Alaska represent key stratigraphic markers for the late Pleistocene: Quaternary Research, v. 92, no. 1, p. 246-256, https://doi.org/10.1017/qua.2018.154.","productDescription":"11 p.","startPage":"246","endPage":"256","ipdsId":"IP-102481","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Southeastern Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -136.40625,\n              54.87660665410869\n            ],\n            [\n              -130.4736328125,\n              54.87660665410869\n            ],\n            [\n              -130.4736328125,\n              57.75107598132104\n            ],\n            [\n              -136.40625,\n              57.75107598132104\n            ],\n            [\n              -136.40625,\n              54.87660665410869\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilcox, Paul S.","contributorId":243353,"corporation":false,"usgs":false,"family":"Wilcox","given":"Paul","email":"","middleInitial":"S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":802126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowell, Sarah J.","contributorId":243354,"corporation":false,"usgs":false,"family":"Fowell","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baichtal, James F.","contributorId":243355,"corporation":false,"usgs":false,"family":"Baichtal","given":"James F.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":802128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Severin, Ken","contributorId":243356,"corporation":false,"usgs":false,"family":"Severin","given":"Ken","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":802129,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mann, Daniel H.","contributorId":193130,"corporation":false,"usgs":false,"family":"Mann","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":802130,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215410,"text":"70215410 - 2019 - Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring","interactions":[],"lastModifiedDate":"2020-10-20T13:48:08.938633","indexId":"70215410","displayToPublicDate":"2019-10-19T13:03:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring","docAbstract":"<p><span>Along the coastal fringe of the Yukon–Kuskokwim River Delta in southwestern Alaska, geese maintain grazing lawns dominated by a rhizomatous sedge that, when ungrazed, transitions to a taller, less palatable growth form that is taxonomically described as a different species. Nutrients recycled in goose feces, in conjunction with grazing, are critical to the rapid, nutritious growth of grazing lawns, and selective foraging on lawns has positive life‐history consequences for goslings. To examine whether bidirectional vegetation shifts were accompanied by parallel changes in N cycling, we studied how&nbsp;</span><sup>15</sup><span>N‐urea and&nbsp;</span><sup>13</sup><span>C</span><sup>15</sup><span>N‐glycine were processed through soils and plants of native and recently reverted vegetation states. Biomass and plant&nbsp;</span><sup>15</sup><span>N uptake from plots reverted to the tall growth form using exclosures and from those shifted to grazing lawns by experimental clipping and then goose grazing were identical to their native counterparts. Total recovery of&nbsp;</span><sup>15</sup><span>N within the tall vegetation types was significantly greater than within grazing lawns, although when expressed on a per‐gram biomass basis, percentage of&nbsp;</span><sup>15</sup><span>N recovery was significantly higher in grazing lawns compared with the tall vegetation state. Patterns of&nbsp;</span><sup>13</sup><span>C enrichment in CO</span><sub>2</sub><span>&nbsp;soil efflux showed rapid use of&nbsp;</span><sup>13</sup><span>C‐glycine as a respiratory substrate within the first hour following injection, with both the timing and magnitude of efflux occurring at similar time points for all four vegetation types. However, higher soil respiration rates and a shorter half‐life for&nbsp;</span><sup>13</sup><span>C‐glycine in soils from tall meadows resulted in a greater proportional loss of&nbsp;</span><sup>13</sup><span>CO</span><sub>2</sub><span>&nbsp;compared with grazing lawns. Despite daily‐to‐weekly tidal inundation, all of&nbsp;</span><sup>15</sup><span>N from labeled substrates could be accounted for within 1&nbsp;m of the injection grid from soils of both states after 30&nbsp;d, with significant levels of&nbsp;</span><sup>15</sup><span>N in soils and vegetation after one year. Geese have remarkably high fidelity to brood‐rearing areas, returning as adults to the same grazing lawns where they were raised as goslings. Our data suggest that the role fecal‐derived nutrients play in the positive feedback loop between geese and their food resources can provide a long‐term legacy that spans generations.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2850","usgsCitation":"Ruess, R.W., McFarland, J., Person, B.T., and Sedinger, J.S., 2019, Geese mediate vegetation state changes with parallel effects on N cycling that leave nutritional legacies for offspring: Ecosphere, v. 10, no. 8, e02850, 16 p., https://doi.org/10.1002/ecs2.2850.","productDescription":"e02850, 16 p.","ipdsId":"IP-107059","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2850","text":"Publisher Index Page"},{"id":379523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon–Kuskokwim River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -166.31927490234372,\n              60.7672084234438\n            ],\n            [\n              -163.85284423828125,\n              60.7672084234438\n            ],\n            [\n              -163.85284423828125,\n              61.55280114177263\n            ],\n            [\n              -166.31927490234372,\n              61.55280114177263\n            ],\n            [\n              -166.31927490234372,\n              60.7672084234438\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruess, Roger W.","contributorId":45483,"corporation":false,"usgs":false,"family":"Ruess","given":"Roger","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":802085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Person, Brian T.","contributorId":107457,"corporation":false,"usgs":false,"family":"Person","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":802088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sedinger, James S.","contributorId":213694,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":802087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215409,"text":"70215409 - 2019 - Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2020-10-19T18:01:53.210147","indexId":"70215409","displayToPublicDate":"2019-10-19T12:45:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5979,"text":"Ocean Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico","docAbstract":"Meteotsunamis associated with passing squall lines are often observed ahead of cold fronts during winter seasons in Northern Gulf of Mexico. These types of meteotsunamis occur simultaneously with wind speed variations (~5-20 m/s) and sea-level atmospheric pressure oscillations (~1-6 hPa) with periods between 2 hours to several minutes. In order to enhance understanding of meteotsunami generation and propagation mechanisms, a Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system is applied to one of the most intense winter meteotsunamis measured in Northern Gulf of Mexico in the last decade (2009-2018).  The model verification with sea level and atmospheric observations show that the fully-coupled model is able to reproduce the timing and intensity of the 10-m wind and sea level atmospheric pressure fluctuations. The mean bias between observed and measured wind speeds and atmospheric pressure are 1.73 m/s and 0.63 hPa respectively. The maximum meteotsunami elevation and its timing are successfully captured by modeled (with a 7% underestimation of the maximum elevation). The relative effect of atmospheric pressure and wind stress divergence on meteotsunami generation is assessed with different numerical simulations. Results indicate that both wind stress and atmospheric pressure oscillations contributed to the generation of the meteotsunami. Wind stress was the dominant force in shallow waters (<15 m in this application), while the effects of atmospheric pressure disturbances dominated over areas with Froude number close to one (~40 m in this application). During the passage of the squall line, the sea surface became rougher in a sea state characterized by young and steep local ocean waves. Compared to a purely wind-speed-dependent roughness scheme, the application of a wave-dependent roughness parameterization improved in 37% modeled meteotsunami maximum elevation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2019.101408","usgsCitation":"Shi, L., Olabarrieta, M., Valle-Levinson, A., and Warner, J., 2019, Relevance of wind stress and wave-dependent ocean surface roughness on the generation of winter meteotsunamis in Northern Gulf of Mexico: Ocean Modeling, v. 140, 101408,  15 p., https://doi.org/10.1016/j.ocemod.2019.101408.","productDescription":"101408,  15 p.","ipdsId":"IP-099874","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocemod.2019.101408","text":"Publisher Index Page"},{"id":379522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.8671875,\n              27.352252938063845\n            ],\n            [\n              -82.353515625,\n              27.352252938063845\n            ],\n            [\n              -82.353515625,\n              30.92107637538488\n            ],\n            [\n              -93.8671875,\n              30.92107637538488\n            ],\n            [\n              -93.8671875,\n              27.352252938063845\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Lijing","contributorId":192873,"corporation":false,"usgs":false,"family":"Shi","given":"Lijing","email":"","affiliations":[],"preferred":false,"id":802081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":802082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valle-Levinson, Arnoldo","contributorId":243337,"corporation":false,"usgs":false,"family":"Valle-Levinson","given":"Arnoldo","email":"","affiliations":[{"id":48691,"text":"Civil and Coastal Engineering Department, ESSIE, University of Florida 365 Weil Hall, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":802083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802084,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215419,"text":"70215419 - 2019 - Ar-Ar age constraints on the timing of Havre Trough opening and magmatism","interactions":[],"lastModifiedDate":"2020-10-20T13:52:51.36972","indexId":"70215419","displayToPublicDate":"2019-10-19T12:26:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2869,"text":"New Zealand Journal of Geology and Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Ar-Ar age constraints on the timing of Havre Trough opening and magmatism","docAbstract":"<p><span>The age and style of opening of the Havre Trough back-arc system is uncertain due to a lack of geochronologic constraints for the region.&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar dating of 19 volcanic rocks from across the southern Havre Trough and Kermadec Arc was conducted in three laboratories to provide age constraints on the system. The results are integrated and interpreted as suggesting that this subduction system is young (&lt;2 Ma) and coeval with opening of the continental Taupo Volcanic Zone of New Zealand. Arc magmatism was broadly concurrent across the breadth of the Havre Trough.</span></p>","language":"English","publisher":"Royal Society of New Zealand","doi":"10.1080/00288306.2019.1602059","usgsCitation":"Wysoczanski, R., Leonard, G.S., Gill, J.F., Wright, I., Calvert, A.T., McIntosh, W., Jicha, B., Gamble, J.A., Timm, C., Handler, M., Drewes-Todd, E.K., and Zohrab, A., 2019, Ar-Ar age constraints on the timing of Havre Trough opening and magmatism: New Zealand Journal of Geology and Geophysics, v. 62, no. 3, p. 371-377, https://doi.org/10.1080/00288306.2019.1602059.","productDescription":"7 p.","startPage":"371","endPage":"377","ipdsId":"IP-106648","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459463,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":379521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Kermadec Arc–Havre Trough","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              174.990234375,\n              -37.99616267972812\n            ],\n            [\n              178.857421875,\n              -37.99616267972812\n            ],\n            [\n              178.857421875,\n              -34.59704151614416\n            ],\n            [\n              174.990234375,\n              -34.59704151614416\n            ],\n            [\n              174.990234375,\n              -37.99616267972812\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"62","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wysoczanski, Richard","contributorId":243346,"corporation":false,"usgs":false,"family":"Wysoczanski","given":"Richard","email":"","affiliations":[{"id":27642,"text":"National Institute of Water and Atmospheric Research, New Zealand","active":true,"usgs":false}],"preferred":false,"id":802113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Graham S.","contributorId":127469,"corporation":false,"usgs":false,"family":"Leonard","given":"Graham","email":"","middleInitial":"S.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":802114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, James F.","contributorId":196664,"corporation":false,"usgs":false,"family":"Gill","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":802115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Ian 0000-0002-6660-0493","orcid":"https://orcid.org/0000-0002-6660-0493","contributorId":243347,"corporation":false,"usgs":false,"family":"Wright","given":"Ian","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":802116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntosh, William","contributorId":179358,"corporation":false,"usgs":false,"family":"McIntosh","given":"William","affiliations":[],"preferred":false,"id":802118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jicha, Brian","contributorId":213920,"corporation":false,"usgs":false,"family":"Jicha","given":"Brian","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":802119,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gamble, John A","contributorId":243348,"corporation":false,"usgs":false,"family":"Gamble","given":"John","email":"","middleInitial":"A","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802120,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Timm, Christian","contributorId":243349,"corporation":false,"usgs":false,"family":"Timm","given":"Christian","email":"","affiliations":[{"id":48696,"text":"GEOMAR","active":true,"usgs":false}],"preferred":false,"id":802121,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Handler, Monica","contributorId":243350,"corporation":false,"usgs":false,"family":"Handler","given":"Monica","email":"","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802122,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Drewes-Todd, Elizabeth Kathleen 0000-0003-0692-3714","orcid":"https://orcid.org/0000-0003-0692-3714","contributorId":243351,"corporation":false,"usgs":true,"family":"Drewes-Todd","given":"Elizabeth","email":"","middleInitial":"Kathleen","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":802123,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zohrab, Alex","contributorId":243352,"corporation":false,"usgs":false,"family":"Zohrab","given":"Alex","email":"","affiliations":[{"id":27874,"text":"Victoria University","active":true,"usgs":false}],"preferred":false,"id":802124,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70215423,"text":"70215423 - 2019 - Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism","interactions":[],"lastModifiedDate":"2020-10-19T17:07:58.396075","indexId":"70215423","displayToPublicDate":"2019-10-19T12:00:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism","docAbstract":"Monogenetic volcanoes, distributed over large areas, contribute to the growth of monogenetic volcanic fields (MVFs) over thousands to millions of years of activity. It is now accepted that MVFs are also temporally clustered. To reduce uncertainties inherent to this episodic character, it is critical to combine multi-disciplinary studies to improve our knowledge of the temporal evolution of MVFs. The Lassen region, in the southern Cascades, is investigated to compare timing of eruptions at distributed mafic, intermediate, and silicic monogenetic volcanoes considering a new set of 40Ar/39Ar and K-Ar ages, complementing published radiometric ages for the area. Activity over the past 3.5 Ma has been episodic, alternating periods of intense and reduced activity as observed at other MVFs. More specifically, periods of intense regional mafic activity have occurred simultaneously to eruptive sequences at the silicic Lassen Volcanic Center (LVC). The back-arc Caribou Volcanic Field (CVF, ~800 – 15 ka) and forearc volcanoes, active simultaneously with the LVC, are characterized by eruptive sequences that persisted for 20 – 40 kyr, with the most recent eruptions occurring during the last glacial episode. Crater Mountain, a relatively young (282 - 395 ka) shield volcano spatially close to the CVF, confirms the presence of localized higher fluxes of mantle-derived melts that persisted for hundreds of thousand years in the back-arc region. Over the past 3.5 Ma, many small magma batches erupted simultaneously in short-lived episodes within clusters distributed across the Lassen region, including the LVC.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-019-1296-7","usgsCitation":"Germa, A., Perry, C., Quidelleur, X., Calvert, A.T., Clynne, M.A., Connor, C., Connor, L., Malservisi, R., and Charbonnier, S., 2019, Temporal relationship between the Lassen Volcanic Center and mafic regional volcanism: Bulletin of Volcanology, v. 81, 38, 17 p., https://doi.org/10.1007/s00445-019-1296-7.","productDescription":"38, 17 p.","ipdsId":"IP-104676","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Lassen Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.158203125,\n              49.095452162534826\n            ],\n            [\n              -122.78320312499999,\n              48.922499263758255\n            ],\n            [\n              -123.04687499999999,\n              48.16608541901253\n            ],\n            [\n              -124.98046874999999,\n              48.16608541901253\n            ],\n            [\n              -124.18945312500001,\n              45.767522962149876\n            ],\n            [\n              -124.8046875,\n              42.74701217318067\n            ],\n            [\n              -124.541015625,\n              42.16340342422401\n            ],\n            [\n              -124.541015625,\n              40.713955826286046\n            ],\n            [\n              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Florida","active":true,"usgs":false}],"preferred":false,"id":802137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Chris","contributorId":224306,"corporation":false,"usgs":false,"family":"Perry","given":"Chris","email":"","affiliations":[{"id":40853,"text":"UE","active":true,"usgs":false}],"preferred":false,"id":802138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quidelleur, Xavier","contributorId":243360,"corporation":false,"usgs":false,"family":"Quidelleur","given":"Xavier","email":"","affiliations":[{"id":48697,"text":"Universite Paris-Sud","active":true,"usgs":false}],"preferred":false,"id":802139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802141,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connor, Chuck","contributorId":139921,"corporation":false,"usgs":false,"family":"Connor","given":"Chuck","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":802142,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Connor, Laura","contributorId":139922,"corporation":false,"usgs":false,"family":"Connor","given":"Laura","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":802143,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Malservisi, Rocco","contributorId":139923,"corporation":false,"usgs":false,"family":"Malservisi","given":"Rocco","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":802144,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Charbonnier, Sylvain","contributorId":243361,"corporation":false,"usgs":false,"family":"Charbonnier","given":"Sylvain","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":802145,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70215406,"text":"70215406 - 2019 - Identifying salt marsh shorelines from remotely sensed elevation data and imagery","interactions":[],"lastModifiedDate":"2020-10-20T13:58:45.477548","indexId":"70215406","displayToPublicDate":"2019-10-19T11:04:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Identifying salt marsh shorelines from remotely sensed elevation data and imagery","docAbstract":"Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea-level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The Marsh Edge from Elevation Data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between Mean High Water and Mean Tide Level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA.  The other method to calculate the salt marsh shoreline is the Marsh Edge by Image Processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The root-mean-square deviation between the two methods within the test area is 0.6 meter. The two methods were compared to each other using high resolution Unmanned Aircraft Systems (UAS) data and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods and less than 0.43 meters from the digitized shoreline. MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability","language":"English","publisher":"MDPI AG","doi":"10.3390/rs11151795","usgsCitation":"Farris, A.S., Defne, Z., and Ganju, N., 2019, Identifying salt marsh shorelines from remotely sensed elevation data and imagery: Remote Sensing, v. 11, no. 15, 1795, 17 p., https://doi.org/10.3390/rs11151795.","productDescription":"1795, 17 p.","ipdsId":"IP-109869","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11151795","text":"Publisher Index Page"},{"id":379518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Buzzards Bay, Orleans, Quincy","otherGeospatial":"Broad Meadows Marsh, Brant Island Cove, Pleasant Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.092529296875,\n              42.21224516288584\n            ],\n            [\n              -70.81787109374999,\n              42.21224516288584\n            ],\n            [\n              -70.81787109374999,\n              42.391008609205045\n            ],\n            [\n              -71.092529296875,\n              42.391008609205045\n            ],\n            [\n              -71.092529296875,\n              42.21224516288584\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -69.98703002929688,\n              41.66367910784373\n            ],\n            [\n              -69.89639282226562,\n              41.66367910784373\n            ],\n            [\n              -69.89639282226562,\n              41.84501267270689\n            ],\n            [\n              -69.98703002929688,\n              41.84501267270689\n            ],\n            [\n              -69.98703002929688,\n              41.66367910784373\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.95245361328125,\n              41.59285100004952\n            ],\n            [\n              -70.78765869140625,\n              41.59285100004952\n            ],\n            [\n              -70.78765869140625,\n              41.68111756290652\n            ],\n            [\n              -70.95245361328125,\n              41.68111756290652\n            ],\n            [\n              -70.95245361328125,\n              41.59285100004952\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"15","noUsgsAuthors":false,"publicationDate":"2019-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":802067,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228681,"text":"70228681 - 2019 - Intense hurricane activity over the past 1500 years at South Andros Island, The Bahamas","interactions":[],"lastModifiedDate":"2022-02-22T12:48:41.942906","indexId":"70228681","displayToPublicDate":"2019-10-19T09:37:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Intense hurricane activity over the past 1500 years at South Andros Island, The Bahamas","docAbstract":"<p><span>Hurricanes cause substantial loss of life and resources in coastal areas. Unfortunately, historical hurricane records are too short and incomplete to capture hurricane-climate interactions on multi-decadal and longer timescales. Coarse-grained, hurricane-induced deposits preserved in blue holes in the Caribbean can provide records of past hurricane activity extending back thousands of years. Here we present a high resolution record of intense hurricane events over the past 1500 years from a blue hole on South Andros Island on the Great Bahama Bank. This record is corroborated by shorter reconstructions from cores collected at two nearby blue holes. The record contains coarse-grained event deposits attributable to known historical hurricane strikes within age uncertainties. Over the past 1500 years, South Andros shows evidence of four active periods of hurricane activity. None of these active intervals occurred in the past 163 years. We suggest that Intertropical Convergence Zone position modulates hurricane activity on the island based on a correlation with Cariaco Basin titanium concentrations. An anomalous gap in activity on South Andros Island in the early 13th century corresponds to a period of increased volcanism. The patterns of hurricane activity reconstructed from South Andros Island closely match those from the northeastern Gulf of Mexico but are anti-phased with records from New England. We suggest that either changes in local environmental conditions (e.g., SSTs) or a northeastward shift in storm tracks can account for the increased activity in the western North Atlantic when the Gulf of Mexico and southeastern Caribbean are less active.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019PA003665","usgsCitation":"Wallace, E., Donnelly, J.P., van Hengstum, P.J., Winman, C., Sullivan, R., Winkler, T., D'Entremont, N., Toomey, M., and Albury, N.A., 2019, Intense hurricane activity over the past 1500 years at South Andros Island, The Bahamas: Paleoceanography and Paleoclimatology, v. 34, no. 11, p. 1761-1783, https://doi.org/10.1029/2019PA003665.","productDescription":"23 p.","startPage":"1761","endPage":"1783","ipdsId":"IP-112040","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":459468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019pa003665","text":"Publisher Index Page"},{"id":396016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"The Bahamas","otherGeospatial":"South Andros Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.81204223632812,\n              23.626281853879018\n            ],\n            [\n              -77.48313903808594,\n              23.626281853879018\n            ],\n            [\n              -77.48313903808594,\n              23.888976847350275\n            ],\n            [\n              -77.81204223632812,\n              23.888976847350275\n            ],\n            [\n              -77.81204223632812,\n              23.626281853879018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, Elizabeth","contributorId":245340,"corporation":false,"usgs":false,"family":"Wallace","given":"Elizabeth","affiliations":[{"id":49154,"text":"Woods Hole Oceanographic Institution, Woods Hole","active":true,"usgs":false}],"preferred":false,"id":835014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":835015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Hengstum, Peter J.","contributorId":199536,"corporation":false,"usgs":false,"family":"van Hengstum","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":835016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winman, Charlotte","contributorId":279501,"corporation":false,"usgs":false,"family":"Winman","given":"Charlotte","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":835017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Richard","contributorId":211625,"corporation":false,"usgs":false,"family":"Sullivan","given":"Richard","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":835018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winkler, Tyler","contributorId":279503,"corporation":false,"usgs":false,"family":"Winkler","given":"Tyler","email":"","affiliations":[{"id":57261,"text":"Texas A&M, Galveston","active":true,"usgs":false}],"preferred":false,"id":835019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"D'Entremont, Nicole","contributorId":279505,"corporation":false,"usgs":false,"family":"D'Entremont","given":"Nicole","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":835020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":835021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Albury, Nancy A.","contributorId":192785,"corporation":false,"usgs":false,"family":"Albury","given":"Nancy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":835022,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70206507,"text":"70206507 - 2019 - Review of indicators for comparing environmental effects across energy sources","interactions":[],"lastModifiedDate":"2019-11-07T13:58:45","indexId":"70206507","displayToPublicDate":"2019-10-18T13:57:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Review of indicators for comparing environmental effects across energy sources","docAbstract":"Robust, quantitative comparisons of environmental effects across energy sources can support development of energy planning strategies that meet growing demand while managing and minimizing undesirable effects on environmental resources. Multicriteria analyses of energy systems often use a suite of indicators to make such comparisons, but those indicators and their units of measure vary among studies. We reviewed 179 papers that described or applied energy indicators to compare environmental effects of different primary energy sources to answer four questions: (1) what environmental indicators have been used in multicriteria energy-source comparisons? (2) across studies, how consistently are these indicators used to quantify effects? (3) to what degree are different effects accounted for across energy sources and locations? and (4) how comprehensive are indicators in terms of assessing known environmental effects? For reviewed studies, we quantified the number of unique indicators and the diversity of indicators used to measure different effects. We also recorded the specific measurement units applied to quantify each indicator, the energy sources evaluated, and the continent where each study was conducted. While we found that many environmental effects of energy development have been analyzed across multiple sources, indicators were frequently measured, interpreted, and applied in ways that are not directly comparable, and some known environmental effects were infrequently assessed. We also found an emphasis on applying indicators to renewable energy sources; assessing current and potential energy sources, both renewable and nonrenewable, would greatly clarify the full suite of tradeoffs among sources and can inform energy development strategies that minimize adverse environmental effects. Overall, our review indicated that making comprehensive comparisons of the effects of energy development across sources may require efforts to standardize how effects are measured, synthesize effects literature into an open-source database, expand the range of environmental effects analyzed, and establish consistent frameworks for comparison.","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab402d","usgsCitation":"Dorning, M., Diffendorfer, J., Loss, S.R., and Bagstad, K.J., 2019, Review of indicators for comparing environmental effects across energy sources: Environmental Research Letters, v. 14, no. 10, 103002, 15 p., https://doi.org/10.1088/1748-9326/ab402d.","productDescription":"103002, 15 p.","ipdsId":"IP-103123","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab402d","text":"Publisher Index Page"},{"id":369053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Dorning, Monica 0000-0002-7576-1256 mdorning@usgs.gov","orcid":"https://orcid.org/0000-0002-7576-1256","contributorId":191772,"corporation":false,"usgs":true,"family":"Dorning","given":"Monica","email":"mdorning@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loss, Scott R","contributorId":220356,"corporation":false,"usgs":false,"family":"Loss","given":"Scott","email":"","middleInitial":"R","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":774837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774838,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206180,"text":"70206180 - 2019 - Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations","interactions":[],"lastModifiedDate":"2019-10-25T06:22:34","indexId":"70206180","displayToPublicDate":"2019-10-18T13:48:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Life cycle of the trout cecal nematode, <i>Truttaedacnitis truttae</i> (Nematoda: Cucullanidae): Experimental and field observations","title":"Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations","docAbstract":"<p><i>Truttaedacnitis truttae</i><span>&nbsp;is a cucullanid nematode of primarily salmonine fishes. Brown trout (</span><i>Salmo trutta</i><span>) in Europe reportedly become parasitized by ingesting lampreys (</span><i>Lampetra planeri</i><span>) carrying infective larvae. However, our field and laboratory observations suggested that North American specimens of&nbsp;</span><i>T. truttae</i><span>&nbsp;have an alternative life cycle. High abundances and potential impact of&nbsp;</span><i>T. truttae</i><span>&nbsp;in rainbow trout,&nbsp;</span><i>Oncorhynchus mykiss</i><span>, in the Colorado River drainage in Grand Canyon, where there are no lampreys, prompted a study on the transmission dynamics of this nematode. Eggs of&nbsp;</span><i>T. truttae</i><span>, collected from live gravid females, were incubated in the laboratory. Snails,&nbsp;</span><i>Physa gyrina</i><span>&nbsp;and&nbsp;</span><i>Lymnaea</i><span>&nbsp;sp., were exposed to&nbsp;</span><i>T. truttae</i><span>&nbsp;larvae 3–4 wk later. Active larvae of&nbsp;</span><i>T. truttae</i><span>&nbsp;were observed penetrating the intestinal wall of exposed snails, and worm larvae were found in the visceral tissues when examined 1 wk after exposure. Larvae in snails showed little growth and development 2 wk later and corresponded to L3 larvae. Infected snails were fed to hatchery-reared juvenile rainbow trout. Developing stages were subsequently found in the mucosal lining and lumen of trout intestines. Adult male and female (gravid) worms were found in the ceca of trout examined 5–6 mo after consuming infected snails. Larvae found in pepsin/trypsin digests and mucosal scrapings from wild, naturally infected, trout corroborate laboratory findings. Screening of&nbsp;</span><i>Physa</i><span>&nbsp;sp. and gammarids collected from Colorado River, Grand Canyon, for natural infections with&nbsp;</span><i>T. truttae</i><span>&nbsp;using the&nbsp;</span><i>ITS1 rDNA</i><span>&nbsp;marker gave positive results.&nbsp;</span><i>Truttaedacnitis truttae</i><span>&nbsp;is the second species, after&nbsp;</span><i>Truttaedacnitis clitellarius</i><span>&nbsp;of lake sturgeon, capable of using a snail first intermediate/paratenic host and is similar to several other cucullanids in having a histotropic phase of development in the definitive fish host.</span></p>","language":"English","publisher":"BioOne","doi":"10.1645/18-22","usgsCitation":"Choudhury, A., and Cole, R.A., 2019, Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations: Journal of Parasitology, v. 105, no. 5, p. 769-782, https://doi.org/10.1645/18-22.","productDescription":"14 p.","startPage":"769","endPage":"782","ipdsId":"IP-092857","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":368560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lees Ferry Reach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.57835006713867,\n              36.85668612175977\n            ],\n            [\n              -111.57354354858397,\n              36.86190535174327\n            ],\n            [\n              -111.58607482910156,\n              36.869733528373395\n            ],\n            [\n              -111.62212371826172,\n              36.851878620917546\n            ],\n            [\n              -111.63602828979491,\n              36.82659992957925\n            ],\n            [\n              -111.65782928466797,\n              36.79581459490302\n            ],\n            [\n              -111.66658401489256,\n              36.769829841046075\n            ],\n            [\n              -111.6712188720703,\n              36.75745305234459\n            ],\n            [\n              -111.6598892211914,\n              36.75098882435508\n            ],\n            [\n              -111.63362503051758,\n              36.794439960959835\n            ],\n            [\n              -111.63516998291016,\n              36.80323719192363\n            ],\n            [\n              -111.60152435302734,\n              36.84610922079688\n            ],\n            [\n              -111.57835006713867,\n              36.85668612175977\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"105","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choudhury, Anindo 0000-0001-7553-4179","orcid":"https://orcid.org/0000-0001-7553-4179","contributorId":220015,"corporation":false,"usgs":false,"family":"Choudhury","given":"Anindo","email":"","affiliations":[{"id":40120,"text":"St. Norbert College, DePere WI","active":true,"usgs":false}],"preferred":false,"id":773786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Rebecca A. 0000-0003-2923-1622 rcole@usgs.gov","orcid":"https://orcid.org/0000-0003-2923-1622","contributorId":2873,"corporation":false,"usgs":true,"family":"Cole","given":"Rebecca","email":"rcole@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":773785,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227713,"text":"70227713 - 2019 - Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification","interactions":[],"lastModifiedDate":"2022-01-27T16:17:18.542828","indexId":"70227713","displayToPublicDate":"2019-10-18T10:08:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification","docAbstract":"<p><span>Visual identification of fish eggs is difficult and unreliable due to a lack of information on the morphological egg characteristics of many species. We used random forests machine learning to predict the identity of genetically identified Bighead Carp&nbsp;</span><i>Hypophthalmichthys nobilis</i><span>, Grass Carp&nbsp;</span><i>Ctenopharyngodon idella</i><span>, and Silver Carp&nbsp;</span><i>H.&nbsp;molitrix</i><span>&nbsp;eggs based on egg morphometric and environmental characteristics. Family, genus, and species taxonomic-level random forests models were explored to assess the performance and accuracy of the predictor variables. The egg characteristics of Bighead Carp, Grass Carp, and Silver Carp were similar, and they were difficult to distinguish from one another. When combined into a single invasive carp class, the random forests models were&nbsp;≥&nbsp;97% accurate at identifying invasive carp eggs, with a ≤5% false positive rate. Egg membrane diameter was the most important predictive variable, but the addition of ten other variables resulted in a 98% success rate for identifying invasive carp eggs from 26 other upper Mississippi River basin species. Our results revealed that a combination of morphometric and environmental measurements can be used to identify invasive carp eggs. Similar machine learning approaches could be used to identify the eggs of other fishes. These results will help managers more easily and quickly assess invasive carp reproduction.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10380","usgsCitation":"Camacho, C., Sullivan, C., Weber, M., and Pierce, C., 2019, Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification: North American Journal of Fisheries Management, v. 39, no. 6, p. 1373-1384, https://doi.org/10.1002/nafm.10380.","productDescription":"12 p.","startPage":"1373","endPage":"1384","ipdsId":"IP-080766","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459471,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/327","text":"External Repository"},{"id":394976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Cedar River, Des Moines River, Iowa river, Mississippi River, Skunk River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.5,\n              40.32141999593439\n            ],\n            [\n              -90.120849609375,\n              40.32141999593439\n            ],\n            [\n              -90.120849609375,\n              42\n            ],\n            [\n              -93.5,\n              42\n            ],\n            [\n              -93.5,\n              40.32141999593439\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Camacho, Carlos A.","contributorId":272254,"corporation":false,"usgs":false,"family":"Camacho","given":"Carlos A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Christopher J.","contributorId":272255,"corporation":false,"usgs":false,"family":"Sullivan","given":"Christopher J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Michael J.","contributorId":272256,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831866,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210789,"text":"70210789 - 2019 - Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (<i>Haliaeetus leucocephalus</i>), the national bird of the USA","interactions":[],"lastModifiedDate":"2020-06-25T14:58:18.19717","indexId":"70210789","displayToPublicDate":"2019-10-18T09:41:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (<i>Haliaeetus leucocephalus</i>), the national bird of the USA","docAbstract":"The bald eagle (Haliaeetus leucocephalus) once experienced near-extinction but has since rebounded. For decades, bald eagles near the Wisconsin River, USA, have experienced a lethal syndrome with characteristic clinical and pathological features but unknown etiology. Here, we describe a novel hepacivirus-like virus (Flaviviridae: Hepacivirus) identified during an investigation of Wisconsin River eagle syndrome (WRES). Bald eagle hepacivirus (BeHV) belongs to a divergent clade of avian viruses that share features with members of the genera Hepacivirus and Pegivirus. BeHV infected 31.9% of eagles spanning 4,254 km of the coterminous USA, with negative strand viral RNA demonstrating active replication in liver tissues. Eagles from Wisconsin were approximately 10-fold more likely to be infected than eagles from elsewhere. Eagle mitochondrial DNA sequences were homogeneous and geographically unstructured, likely reflecting a recent population bottleneck, whereas BeHV envelope gene sequences showed strong population genetic substructure and isolation by distance, suggesting localized transmission. Cophylogenetic analyses showed no congruity between eagles and their viruses, supporting horizontal rather than vertical transmission. These results expand our knowledge of the Flaviviridae, reveal a striking pattern of decoupled host/virus coevolution on a continental scale, and highlight knowledge gaps about health and conservation in even the most iconic of wildlife species.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-50580-8","usgsCitation":"Golberg, T.L., Sibley, S.D., Pinkerton, M., Dunn, C.D., Long, L., White, C.L., and Strom, S., 2019, Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (<i>Haliaeetus leucocephalus</i>), the national bird of the USA: Scientific Reports, v. 9, 14953, 12 p., https://doi.org/10.1038/s41598-019-50580-8.","productDescription":"14953, 12 p.","ipdsId":"IP-111425","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":459474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-50580-8","text":"Publisher Index Page"},{"id":375916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                48.27\n              ],\n              [\n          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       -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                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              46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Golberg, Tony L.","contributorId":225518,"corporation":false,"usgs":false,"family":"Golberg","given":"Tony","email":"","middleInitial":"L.","affiliations":[{"id":41155,"text":"Department of Pathobiological Sciences, University of Wisconsin-Madison,","active":true,"usgs":false}],"preferred":false,"id":791426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sibley, Samuel D.","contributorId":225519,"corporation":false,"usgs":false,"family":"Sibley","given":"Samuel","email":"","middleInitial":"D.","affiliations":[{"id":41155,"text":"Department of Pathobiological Sciences, University of Wisconsin-Madison,","active":true,"usgs":false}],"preferred":false,"id":791427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinkerton, Marie E.","contributorId":225520,"corporation":false,"usgs":false,"family":"Pinkerton","given":"Marie E.","affiliations":[{"id":41155,"text":"Department of Pathobiological Sciences, University of Wisconsin-Madison,","active":true,"usgs":false}],"preferred":false,"id":791428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Christopher D.","contributorId":225521,"corporation":false,"usgs":false,"family":"Dunn","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":41155,"text":"Department of Pathobiological Sciences, University of Wisconsin-Madison,","active":true,"usgs":false}],"preferred":false,"id":791429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Long, Lindsey","contributorId":225522,"corporation":false,"usgs":false,"family":"Long","given":"Lindsey","affiliations":[{"id":41156,"text":"Global Health Institute, University of Wisconsin-Madison, 1300 University Avenue","active":true,"usgs":false}],"preferred":false,"id":791430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":791431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strom, Sean M.","contributorId":127354,"corporation":false,"usgs":false,"family":"Strom","given":"Sean M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":791432,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206048,"text":"sir20175013V3 - 2019 - The HayWired earthquake scenario—Societal consequences","interactions":[{"subject":{"id":70206048,"text":"sir20175013V3 - 2019 - The HayWired earthquake scenario—Societal consequences","indexId":"sir20175013V3","publicationYear":"2019","noYear":false,"chapter":"R–W","displayTitle":"The HayWired Earthquake Scenario—Societal Consequences","title":"The HayWired earthquake scenario—Societal consequences"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":1}],"isPartOf":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"lastModifiedDate":"2021-12-14T23:04:24.607411","indexId":"sir20175013V3","displayToPublicDate":"2019-10-18T07:11:04","publicationYear":"2019","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":"2017-5013","chapter":"R–W","displayTitle":"The HayWired Earthquake Scenario—Societal Consequences","title":"The HayWired earthquake scenario—Societal consequences","docAbstract":"<p>The HayWired Earthquake Scenario—Societal Consequences is the third volume of U.S. Geological Survey (USGS) Scientific Investigations Report 2017–5013, which describes the HayWired scenario, developed by USGS and its partners. The scenario is a hypothetical yet scientifically realistic earthquake sequence that is being used to better understand hazards for the San Francisco Bay region during and after a magnitude-7 earthquake (mainshock) on the Hayward Fault and its aftershocks.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The HayWired earthquake scenario","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175013V3","usgsCitation":"Detweiler, S.T., and Wein, A.M., eds., The HayWired earthquake scenario—Societal consequences (ver. 1.1, October 2021): U.S. Geological Survey Scientific Investigations Report 2017–5013–R–W, https://doi.org/10.3133/sir20175013v3.","productDescription":"Chapter R: v, 17 p.; Chapter S: xii, 94 p.; Chapter T: v, 104 p.; Chapter U: v, 139 p.; Chapter V2: v, 39 p.; Chapter V3: vi, 58 p.; Chapter V4: iv, 68 p.; Chapter V5: v, 57 p.; Chapter W: iv, 21 p.","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":368407,"rank":2,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/s/sir20175013s.pdf","text":"Chapter S","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- The HayWired Scenario—Telecommunications and Information Communication Technology"},{"id":388368,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v1","text":"Scientific Investigations Report 2017-5013 Volume 1","linkHelpText":"- The HayWired Earthquake Scenario—Earthquake Hazards"},{"id":368404,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/t/sir20175013t_ver1.1.pdf","text":"Chapter T","size":"31 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Lifeline Infrastructure and Collocation Exposure to the HayWired Earthquake Scenario—A Summary of Hazards and Potential Service Disruptions"},{"id":368408,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v2","text":"Scientific Investigations Report 2017-5013 Volume 2","linkHelpText":"- The HayWired Earthquake Scenario—Engineering Implications"},{"id":388371,"rank":15,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94HDTD8","text":"Data Release for Chapter T","linkHelpText":"Results of individual and collocated lifeline exposure to hazards (and associated hazard and multi-hazard exposure surface data) resulting from the HayWired scenario earthquake sequence for counties and cities in the San Francisco Bay area, California"},{"id":388369,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HKJU90","text":"Data Release for Chapter S","linkHelpText":"Voice and data telecommunications restoration curves for 17 counties affected by the April 18, 2018, M7.0 HayWired earthquake scenario mainshock"},{"id":375639,"rank":11,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/v/sir20175013v4.pdf","text":"Chapter V4","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Characteristics of Businesses Disrupted by Building Damages from the HayWired Scenario Mainshock"},{"id":392907,"rank":21,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20213054","text":"Fact Sheet 2021-3054","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":392906,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183016","text":"Fact Sheet 2018-3016","linkHelpText":"– The HayWired Earthquake Scenario—We Can Outsmart Disaster"},{"id":390714,"rank":19,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5013/sir20175013_rw.pdf","text":"Report","size":"150 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contains chapters R to W in one volume"},{"id":390682,"rank":18,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/t/versionHist.rtf"},{"id":388373,"rank":17,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CLW518","text":"Data Release for Chapter V5","linkHelpText":"Economic subareas of interest data for areas containing concentrated damage resulting from the April 18, 2018, HayWired earthquake scenario in the San Francisco Bay region, California"},{"id":388372,"rank":16,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94Z8BOZ","text":"Data Release for Chapter U","linkHelpText":"Estimated geospatial and tabular damages and vulnerable population distributions resulting from exposure to multiple hazards by the M7.0 HayWired scenario on April 18, 2018, for 17 counties in the San Francisco Bay region, California"},{"id":368464,"rank":13,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/w/sir20175013w.pdf","text":"Chapter W","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- The HayWired Scenario—Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions"},{"id":375640,"rank":12,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/v/sir20175013v5.pdf","text":"Chapter V5","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Spatial Analysis of Industries, Employment, and Commute Flows in Areas of Concentrated Damage from the HayWired Earthquake Scenario"},{"id":375638,"rank":10,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/v/sir20175013v3.pdf","text":"Chapter V3","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- The Economic Effects of the HayWired Scenario Using the Association of Bay Area Governments Regional Growth Forecast"},{"id":383109,"rank":9,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/v/sir20175013v2.pdf","text":"Chapter V2","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Economic Consequences of the HayWired Scenario—Digital and Utility Network Linkages and Resilience"},{"id":379375,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/v/sir20175013v1.pdf","text":"Chapter V1","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Summary of Economic Impact Analyses and Policy Implications of the HayWired Scenario"},{"id":381193,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/u/sir20175013u.pdf","text":"Chapter U","size":"75 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Analysis of Communities at Risk in the HayWired Scenario"},{"id":390307,"rank":1,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/sir/2017/5013/vol3/r/sir20175013r.pdf","text":"Chapter R","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Overview of the HayWired Scenario Societal-Consequences Volume"},{"id":368410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5013/covrthb_rw.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.59619140625001,\n              37.23032838760387\n            ],\n            [\n              -121.17919921875001,\n              37.23032838760387\n            ],\n            [\n              -121.17919921875001,\n              38.38472766885085\n            ],\n            [\n              -123.59619140625001,\n              38.38472766885085\n            ],\n            [\n              -123.59619140625001,\n              37.23032838760387\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: October 2019; Version 1.1: October 2021","contact":"<p><a href=\"https://www.usgs.gov/natural-hazards/earthquake-hazards/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/natural-hazards/earthquake-hazards/connect\">Contact Information</a>, Menlo Park, Calif.<br><a data-mce-href=\"https://earthquake.usgs.gov/\" href=\"https://earthquake.usgs.gov/\" target=\"_blank\" rel=\"noopener\">Office—Earthquake Science Center</a><br><a data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>345 Middlefield Road, MS 977<br>Menlo Park, CA 94025<br></p>","publishedDate":"2019-10-18","revisedDate":"2021-10-20","noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"editors":[{"text":"Detweiler, Shane T. 0000-0001-5699-011X shane@usgs.gov","orcid":"https://orcid.org/0000-0001-5699-011X","contributorId":680,"corporation":false,"usgs":true,"family":"Detweiler","given":"Shane","email":"shane@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":773471,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wein, Anne M. 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":192951,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":773472,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}}
,{"id":70208579,"text":"70208579 - 2019 - Annual winter site fidelity of Barrow's goldeneyes in the Pacific","interactions":[],"lastModifiedDate":"2020-02-19T20:14:06","indexId":"70208579","displayToPublicDate":"2019-10-17T20:09:48","publicationYear":"2019","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":"Annual winter site fidelity of Barrow's goldeneyes in the Pacific","docAbstract":"Coastal regions on the Pacific north coast of North America provide important wintering habitat for many species of sea ducks. Although winter range and habitat preferences are well described for most species, fidelity to coastal wintering sites is generally undocumented. Fidelity is an important factor necessary for understanding interactions with coastal developments and activities and corresponding management strategies. We used data from Barrow's goldeneyes (Bucephala islandica), a sea duck that winters predominantly in nearshore habitats along the Pacific north coast, to investigate inter‐annual fidelity to, and intra‐annual fidelity within, coastal wintering sites. Between 2006 and 2015, we marked goldeneyes on breeding, molting, and wintering sites with satellite transmitters. We retained 4,931 locations in coastal habitats from 221 goldeneyes across 4 coastal regions for our analyses. These birds demonstrated high inter‐annual fidelity to coastal wintering sites; 75% of selected wintering sites were within 29 km of sites used the previous winter. Inter‐annual fidelity to wintering sites was similar between sex and age classes but differed by coastal region. Goldeneyes from southcentral Alaska, USA, expressed greater inter‐annual fidelity relative to birds from northern or southern British Columbia, Canada, and southeast Alaska. Goldeneyes also expressed high intra‐annual fidelity within wintering sites, with 75% of individuals averaging within‐season movements of ≤9 km. Intra‐annual fidelity was lesser for female than male goldeneyes but did not differ between hatch‐year and after‐hatch‐year birds. We found regional variation in intra‐annual fidelity, with goldeneyes from southcentral Alaska expressing greater intra‐annual fidelity compared to birds from other regions. High inter‐ and intra‐annual winter site fidelity by Barrow's goldeneyes suggests that, at a population level, habitat use is predictable and can be used to inform risk assessment or to evaluate factors affecting habitat choice. Also, low dispersal among wintering sites suggests that recovery from population perturbations, whether caused by natural or anthropogenic events, will be protracted.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21767","usgsCitation":"Willie, M., Esler, D., Boyd, W.S., Bowman, T.D., Schamber, J., and Thompson, J., 2019, Annual winter site fidelity of Barrow's goldeneyes in the Pacific: Journal of Wildlife Management, v. 84, no. 1, p. 161-171, https://doi.org/10.1002/jwmg.21767.","productDescription":"11 p.","startPage":"161","endPage":"171","ipdsId":"IP-106368","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Pacific north coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -126.2548828125,\n              38.89103282648846\n            ],\n            [\n              -119.970703125,\n              38.89103282648846\n            ],\n            [\n              -119.970703125,\n              48.777912755501845\n            ],\n            [\n              -126.2548828125,\n              48.777912755501845\n            ],\n            [\n              -126.2548828125,\n              38.89103282648846\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Willie, Megan","contributorId":199404,"corporation":false,"usgs":false,"family":"Willie","given":"Megan","email":"","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":782582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"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":782581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, W. Sean","contributorId":199405,"corporation":false,"usgs":false,"family":"Boyd","given":"W.","email":"","middleInitial":"Sean","affiliations":[{"id":35539,"text":"Science and Technology Branch, Environment and Climate Change Canada, Delta, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":782583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowman, Timothy D.","contributorId":80779,"corporation":false,"usgs":false,"family":"Bowman","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":782584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schamber, Jason","contributorId":190328,"corporation":false,"usgs":false,"family":"Schamber","given":"Jason","affiliations":[],"preferred":false,"id":782585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Jonathan","contributorId":222570,"corporation":false,"usgs":false,"family":"Thompson","given":"Jonathan","affiliations":[{"id":40562,"text":"Golder Associates","active":true,"usgs":false}],"preferred":false,"id":782586,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204610,"text":"ofr20191086 - 2019 - Estimated use of water in Georgia for 2015 and water-use trends, 1985–2015","interactions":[],"lastModifiedDate":"2019-10-17T14:32:56","indexId":"ofr20191086","displayToPublicDate":"2019-10-17T15:50:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1086","displayTitle":"Estimated Use of Water in Georgia for 2015 and Water-Use Trends, 1985–2015","title":"Estimated use of water in Georgia for 2015 and water-use trends, 1985–2015","docAbstract":"<p>Water-withdrawal, water-use, and water-return information have been collected and compiled for each county in Georgia every 5 years since 1980 using data obtained from various Federal, State, and private agencies, as well as additional online sources. For 2015, water use, water withdrawal, and water returns were estimated for each county, water-planning region, major river basin, and principal aquifer in Georgia. Offstream water use in 2015 is estimated for the categories of domestic, commercial, industrial processing, mining, irrigation (subdivided into crop and golf course irrigation), livestock, aquaculture, and thermoelectric power cooling.</p><p>According to the U.S. Census Bureau, approximately 10.2 million people in Georgia needed water resources to meet their personal, commercial, and recreational needs in 2015. Public water suppliers provided water to about 85 percent of the population of Georgia. Estimated total water withdrawals from both surface-water and groundwater sources were about 3,384 million gallons per day (Mgal/d) in 2015, which is a 27-percent reduction from 2010, a 48.1-percent reduction from 2000, and a 49.7-percent reduction from 1980. In 2015, surface-water withdrawals were greatest for thermoelectric power cooling (839.8 Mgal/d), and groundwater withdrawals were greatest for irrigating crops (547.9 Mgal/d). Water needs in northern Georgia are typically met by withdrawing a larger percentage of water from surface-water than groundwater sources; conversely, counties in southern Georgia withdraw more water from groundwater sources. About 1,571 Mgal/d of water were returned to Georgia streams and lakes in 2015, which represents about 46 percent of the total water withdrawn from all sources in 2015.</p><p>Water users in the Apalachicola River Basin, in 2015, withdrew the highest percentage of water (35 percent) and returned the highest percentage of water to surface-water bodies (almost 40 percent) compared to other major river basins in Georgia. Withdrawals in the Apalachicola River Basin are primarily extracted by public-supply systems (43 percent) and irrigation (34 percent). The aquifer from which 68 percent of statewide groundwater withdrawals were extracted was the Floridan aquifer system, and the majority of the water was used for irrigation (57 percent).</p><p>Historically, statewide water use in Georgia was highest in 1980 (6,735 Mgal/d), decreased to 5,353 Mgal/d in 1990, peaked at 6,531 Mgal/d in 2000, and has been declining since that time. The reduction in water use between 2000 and 2015 came primarily from surface-water withdrawals (90 percent of total reduction) and thermoelectric power cooling use (78 percent of total reduction). Water use for livestock and aquaculture increased between 1985 and 2015, and this increase correlates with the growth of agriculture in Georgia during that period. The driving forces behind the observed water-use changes include (1) shifts in population numbers and locations, (2) five periods of major drought, (3) water conservation efforts and education programs initiated by State and local governments and water utilities, and (4) changing water needs for thermoelectric power cooling, industry, and agricultural activities.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191086","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Painter, J.A., 2019, Estimated use of water in Georgia for 2015 and water-use trends, 1985–2015: U.S. Geological Survey Open-File Report 2019–1086, 216 p., https://doi.org/10.3133/ofr20191086.","productDescription":"vi, 216 p.","numberOfPages":"226","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-096369","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":437300,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2F373","text":"USGS data release","linkHelpText":"Georgia Water Use Mapper"},{"id":368396,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1086/ofr20191086.pdf","text":"Report","size":"27.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1086"},{"id":367811,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1086/coverthb.jpg"},{"id":367813,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T6P5SM","text":"USGS data release","linkHelpText":"Georgia water-use information by county and water-use trends by water-planning region"}],"country":"United States ","state":"Georgia 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 \"}}]}","contact":"<p><a href=\"mailto:dc_ga@usgs.gov\" data-mce-href=\"mailto:dc_ga@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>1770 Corporate Drive<br>Suite 500<br>Norcross, GA 30093</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Information Sources and Methodology</li><li>Water Withdrawals, Estimated Water Use, and Surface-Water Returns</li><li>Water-Use Trends, 1985–2015</li><li>Discussion and Conclusions</li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. North American Industrial Classification System Codes</li><li>Appendix 2. Population, Water Withdrawals, and Water Use by Source of Water for Each County in Georgia, 2015</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-09-30","noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767759,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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