{"pageNumber":"1124","pageRowStart":"28075","pageSize":"25","recordCount":184769,"records":[{"id":70186267,"text":"70186267 - 2016 - Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","interactions":[],"lastModifiedDate":"2017-04-03T12:50:32","indexId":"70186267","displayToPublicDate":"2016-05-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5361,"text":"California Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","docAbstract":"<p><span>Archaeological investigations at prehistoric site CA-MRN-254 at the Dominican University of California in Marin County, California, revealed evidence of Native American occupation spanning the past 1,800 years. A dominant source of food for the inhabitants in the San Francisco Bay area was the intertidal, quiet-water dwelling blue mussel (</span><i>Mytilus trossulus</i><span>), although rare occurrences of the open coast-dwelling California mussel (</span><i>Mytilus californianus</i><span>) suggest that this species was also utilized sporadically. On rare occasions, cultural horizons at this site contain abundant sediment-filled casts of the smaller mussel </span><i>Modiolus</i><span> sp. These casts were formed soon after death when the shells filled with sediment and were roasted along with living bivalve shellfish for consumption. Thin sections of these mussel casts display sedimentological and microbiological constituents that shed light on the paleoenvironmental conditions when they were alive. Fine-grained sediment and pelletal muds comprising these casts suggest that the mussels were collected in a low energy, inner bay environment. The rare presence of the diatoms </span><i>Triceratium dubium</i><span> and </span><i>Thalassionema nitzschioides</i><span> indicate more normal marine (35 psu) and possibly warmer conditions than presently exist in San Francisco Bay. Radiocarbon dating of charcoal associated with the mussel casts containing these diatoms correlates with a 600-year period of warming from ca. A.D. 700–1300, known as the Medieval Climatic Anomaly. Results of this mussel cast study demonstrate that they have great potential for providing paleoenvironmental information at this and other archaeological sites.</span></p>","language":"English","publisher":"Society for California Archaeology","publisherLocation":"Chico, CA","doi":"10.1080/1947461X.2016.1176367","usgsCitation":"McGann, M., Starratt, S.W., Powell, C.L., and Bieling, D.G., 2016, Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California: California Archaeology, v. 8, no. 1, p. 63-90, https://doi.org/10.1080/1947461X.2016.1176367.","productDescription":"28 p.","startPage":"63","endPage":"90","ipdsId":"IP-079316","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Rafael","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.51884460449217,\n              37.97786403627176\n            ],\n            [\n              -122.51609802246092,\n              37.97786403627176\n            ],\n            [\n              -122.51609802246092,\n              37.979555414681506\n            ],\n            [\n              -122.51884460449217,\n              37.979555414681506\n            ],\n            [\n              -122.51884460449217,\n              37.97786403627176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"58e35f7fe4b09da67997ecad","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":688076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","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":688077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Charles L. II 0000-0002-1913-555X cpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-1913-555X","contributorId":3243,"corporation":false,"usgs":true,"family":"Powell","given":"Charles","suffix":"II","email":"cpowell@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":688078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bieling, David G","contributorId":190292,"corporation":false,"usgs":false,"family":"Bieling","given":"David","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":688079,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170988,"text":"70170988 - 2016 - Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species","interactions":[],"lastModifiedDate":"2016-11-09T10:33:17","indexId":"70170988","displayToPublicDate":"2016-05-07T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":982,"text":"Behavioral Ecology and Sociobiology","active":true,"publicationSubtype":{"id":10}},"title":"Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species","docAbstract":"<p><span>For several species, refuges (such as burrows, dens, roosts, nests) are an essential resource for protection from predators and extreme environmental conditions. Refuges also serve as focal sites for social interactions, including mating, courtship, and aggression. Knowledge of refuge use patterns can therefore provide information about social structure, mating, and foraging success, as well as the robustness and health of wildlife populations, especially for species considered to be relatively solitary. In this study, we construct networks of burrow use to infer social associations in a threatened wildlife species typically considered solitary—the desert tortoise. We show that tortoise social networks are significantly different than null networks of random associations, and have moderate spatial constraints. We next use statistical models to identify major mechanisms behind individual-level variation in tortoise burrow use, popularity of burrows in desert tortoise habitat, and test for stressor-driven changes in refuge use patterns. We show that seasonal variation has a strong impact on tortoise burrow switching behavior. On the other hand, burrow age and topographical condition influence the number of tortoises visiting a burrow in desert tortoise habitat. Of three major population stressors affecting this species (translocation, drought, disease), translocation alters tortoise burrow switching behavior, with translocated animals visiting fewer unique burrows than residents. In a species that is not social, our study highlights the importance of leveraging refuge use behavior to study the presence of and mechanisms behind non-random social structure and individual-level variation. Our analysis of the impact of stressors on refuge-based social structure further emphasizes the potential of this method to detect environmental or anthropogenic disturbances.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00265-016-2136-9","usgsCitation":"Sah, P., Nussear, K.E., Esque, T., Aiello, C.M., Hudson, P., and Bansal, S., 2016, Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species: Behavioral Ecology and Sociobiology, v. 70, no. 8, p. 1277-1289, https://doi.org/10.1007/s00265-016-2136-9.","productDescription":"13 p.","startPage":"1277","endPage":"1289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068721","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471017,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/025494","text":"External Repository"},{"id":321446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-27","publicationStatus":"PW","scienceBaseUri":"5740354ae4b07e28b65e9657","contributors":{"authors":[{"text":"Sah, Pratha","contributorId":127768,"corporation":false,"usgs":false,"family":"Sah","given":"Pratha","email":"","affiliations":[{"id":7145,"text":"Department of Biology, Georgetown University, Washington DC","active":true,"usgs":false}],"preferred":false,"id":629345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":127766,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":629344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiello, Christina M. 0000-0002-2399-5464 caiello@usgs.gov","orcid":"https://orcid.org/0000-0002-2399-5464","contributorId":5617,"corporation":false,"usgs":true,"family":"Aiello","given":"Christina","email":"caiello@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":629348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bansal, Shweta","contributorId":168595,"corporation":false,"usgs":false,"family":"Bansal","given":"Shweta","email":"","affiliations":[{"id":25339,"text":"Dep't of Biology, Georgetown U., Washington D.C., NIH, Bethesda, MD","active":true,"usgs":false}],"preferred":false,"id":629349,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70169357,"text":"sir20165036 - 2016 - Flood-inundation maps for the East Fork White River at Shoals, Indiana","interactions":[],"lastModifiedDate":"2016-05-18T09:55:41","indexId":"sir20165036","displayToPublicDate":"2016-05-06T14:00:00","publicationYear":"2016","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":"2016-5036","title":"Flood-inundation maps for the East Fork White River at Shoals, Indiana","docAbstract":"<p>Digital flood-inundation maps for a 5.9-mile reach of the East Fork White River at Shoals, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" data-mce-href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a> depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the East Fork White River at Shoals, Ind. (USGS station number 03373500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at <a href=\"http://waterdata.usgs.gov/\" data-mce-href=\"http://waterdata.usgs.gov/\">http://waterdata.usgs.gov/</a> or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at <a href=\"http://water.weather.gov/ahps/\" data-mce-href=\"http://water.weather.gov/ahps/\">http://water.weather.gov/ahps/</a>, which also forecasts flood hydrographs at this site (NWS AHPS site SHLI3). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.</p><p>Flood profiles were computed for the East Fork White River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 43.0) at USGS streamgage 03373500, East Fork White River at Shoals, Ind. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (10 ft) to the highest stage of the current stage-discharge rating curve (35 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM), derived from light detection and ranging (lidar) data, to delineate the area flooded at each water level. The areal extent of the 24-ft flood-inundation map was verified with photographs from a flood event on July 20, 2015.</p><p>The availability of these maps, along with information on the Internet regarding current stage from the USGS streamgage at East Fork White River at Shoals, Ind., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165036","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Boldt, J.A., 2016, Flood-inundation maps for the East Fork White River at Shoals, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5036, 22 p., 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Library</li>\n<li>Summary</li>\n<li>References Cited</li>\n<li>Appendix 1.&nbsp;Supplemental Data and Photographs</li>\n</ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-05-06","noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"572db219e4b0dae0d5d83fa7","contributors":{"authors":[{"text":"Boldt, Justin A. jboldt@usgs.gov","contributorId":167903,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin A.","email":"jboldt@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":623941,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70169102,"text":"sir20155187 - 2016 - Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio","interactions":[],"lastModifiedDate":"2016-06-24T13:27:24","indexId":"sir20155187","displayToPublicDate":"2016-05-06T08:15:00","publicationYear":"2016","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":"2015-5187","title":"Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio","docAbstract":"<p>Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155187","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Huitger, C.A, Ostheimer, C.J., and Koltun, G.F., 2016, Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5187, 39 p., 2 appendixes, https://dx.doi.org/10.3133/sir20155187.","productDescription":"Report: vi, 39 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060945","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":320916,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-1.csv","text":"Appendix 1 - Table 1-1","size":"84.1 KB csv","description":"SIR 2015-5187"},{"id":320915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5187/sir20155187.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5187"},{"id":320917,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-2.csv","text":"Appendix 1 - Table 1-2","size":"62 KB csv","description":"SIR 2015-5187"},{"id":320914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5187/coverthb.jpg"},{"id":320919,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-4.csv","text":"Appendix 1 - Table 1-4","size":"50 KB csv","description":"SIR 2015-5187"},{"id":320918,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-3.csv","text":"Appendix 1 - Table 1-3","size":"19 KB csv","description":"SIR 2015-5187"},{"id":320920,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-5.csv","text":"Appendix 1 - Table 1-5","size":"22 KB csv","description":"SIR 2015-5187"}],"country":"United States","state":"Ohio","city":"Shelby","otherGeospatial":"Black Fork Mohican River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.70902633666992,\n              40.83563216247778\n            ],\n            [\n              -82.70902633666992,\n              40.91934991356069\n            ],\n            [\n              -82.61959075927734,\n              40.91934991356069\n            ],\n            [\n              -82.61959075927734,\n              40.83563216247778\n            ],\n            [\n              -82.70902633666992,\n              40.83563216247778\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Ohio Water Science Center<br> 6480 Doubletree Ave<br> Columbus, OH 43229<br> <a href=\"http://oh.water.usgs.gov/\" data-mce-href=\"http://oh.water.usgs.gov/\">http://oh.water.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Abstract&nbsp;</li>\n<li>Introduction</li>\n<li>Study Approach</li>\n<li>Step-backwater Analyses</li>\n<li>Summary</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-05-06","noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"572db21ae4b0dae0d5d83fb0","contributors":{"authors":[{"text":"Huitger, Carrie A. chuitger@usgs.gov","contributorId":1851,"corporation":false,"usgs":true,"family":"Huitger","given":"Carrie","email":"chuitger@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostheimer, Chad J. ostheime@usgs.gov","contributorId":140119,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad J.","email":"ostheime@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":1852,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","email":"gfkoltun@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70171120,"text":"70171120 - 2016 - Sediment chemistry and toxicity in Barnegat Bay, New Jersey: Pre- and post-Hurricane Sandy, 2012–13","interactions":[],"lastModifiedDate":"2018-08-08T10:29:24","indexId":"70171120","displayToPublicDate":"2016-05-06T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Sediment chemistry and toxicity in Barnegat Bay, New Jersey: Pre- and post-Hurricane Sandy, 2012–13","docAbstract":"<p>Hurricane<span>&nbsp;Sandy made landfall in Barnegat Bay, October, 29, 2012, damaging shorelines and infrastructure. Estuarine&nbsp;sediment chemistry&nbsp;and toxicity were investigated before and after to evaluate potential&nbsp;environmental health&nbsp;impacts and to establish post-event baseline sediment-quality conditions.&nbsp;Trace element&nbsp;concentrations increased throughout Barnegat Bay up to two orders of magnitude, especially north of Barnegat Inlet, consistent with northward redistribution of silt. Loss of organic compounds, clay, and&nbsp;organic carbon&nbsp;is consistent with sediment winnowing and transport through the inlets and&nbsp;sediment transportmodeling results. The number of sites exceeding sediment quality guidance levels for trace elements tripled post-Sandy. Sediment toxicity post-Sandy was mostly unaffected relative to pre-Sandy conditions, but at the site with the greatest relative increase for trace elements, survival rate of the test&nbsp;amphipod&nbsp;decreased (indicating degradation). This study would not have been possible without comprehensive baseline data enabling the evaluation of storm-derived changes in sediment quality.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.018","usgsCitation":"Romanok, K., Szabo, Z., Reilly, T.J., Defne, Z., and Ganju, N., 2016, Sediment chemistry and toxicity in Barnegat Bay, New Jersey: Pre- and post-Hurricane Sandy, 2012–13: Marine Pollution Bulletin, v. 107, no. 2, p. 472-488, https://doi.org/10.1016/j.marpolbul.2016.04.018.","productDescription":"17 p.","startPage":"472","endPage":"488","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068252","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":321463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.97894287109375,\n              39.14710270770074\n            ],\n            [\n              -74.97894287109375,\n              40.41349604970198\n            ],\n            [\n              -74.00390625,\n              40.41349604970198\n            ],\n            [\n              -74.00390625,\n              39.14710270770074\n            ],\n            [\n              -74.97894287109375,\n              39.14710270770074\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57403559e4b07e28b65e9705","contributors":{"authors":[{"text":"Romanok, Kristin M.  0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"preferred":true,"id":629967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":629968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":629969,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170609,"text":"sir20165056 - 2016 - Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-10-24T13:54:47","indexId":"sir20165056","displayToPublicDate":"2016-05-05T18:00:00","publicationYear":"2016","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":"2016-5056","title":"Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","docAbstract":"<p>The U.S. Geological Survey and Idaho Department of Environmental Quality Idaho National Laboratory (INL) Oversight Program in cooperation with the U.S. Department of Energy determined background concentrations of selected chemical and radiochemical constituents in the eastern Snake River Plain aquifer to aid with ongoing cleanup efforts at the INL. Chemical and radiochemical constituents including calcium, magnesium, sodium, potassium, silica, chloride, sulfate, fluoride, bicarbonate, chromium, nitrate, tritium, strontium-90, chlorine-36, iodine-129, plutonium-238, plutonium-239, -240 (undivided), americium-241, technetium-99, uranium-234, uranium-235, and uranium-238 were selected for the background study because they were either not analyzed in earlier studies or new data became available to give a more recent determination of background concentrations. Samples of water collected from wells and springs at and near the INL that were not believed to be influenced by wastewater disposal were used to identify background concentrations. Groundwater in the eastern Snake River Plain aquifer at and near the INL was divided into two major water types (western tributary and eastern regional) based on concentrations of lithium less than and greater than 5 micrograms per liter (&mu;g/L). Median concentrations for each constituent were used to define the upper limit of background.</p>\n<p>The upper limit of background concentrations for inorganic chemicals for western tributary water was 40.7 milligrams per liter (mg/L) for calcium, 15.3 mg/L for magnesium, 8.30 mg/L for sodium, 2.32 mg/L for potassium, 23.1 mg/L for silica, 11.8 mg/L for chloride, 21.4 mg/L for sulfate, 0.20 mg/L for fluoride, 176 mg/L for bicarbonate, 4.00 &mu;g/L for chromium, and 0.655 mg/L for nitrate.</p>\n<p>The upper limit of background concentrations for inorganic chemicals for eastern regional water was 34.05 mg/L for calcium, 13.85 mg/L for magnesium, 14.85 mg/L for sodium, 3.22 mg/L for potassium, 31.0 mg/L for silica, 14.15 mg/L for chloride, 20.2 mg/L for sulfate, 0.4675 mg/L for fluoride, 165 mg/L for bicarbonate, 3.00 &mu;g/L for chromium, and 0.995 mg/L for nitrate.</p>\n<p>The upper limit of background concentrations for radiochemical constituents for western tributary water&nbsp;was 34.15 &plusmn;2.35 picocuries per liter (pCi/L) for tritium, 0.00098 &plusmn;0.00006 pCi/L for chlorine-36, 0.000011 &plusmn;0.000005 pCi/L for iodine-129, &lt;0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.36 pCi/L with undetermined uncertainty for uranium-234, 0.025 &plusmn;0.001 pCi/L for uranium-235, and 0.541 &plusmn;0.001 pCi/L for uranium-238.</p>\n<p>The upper limit of background concentrations for radiochemical constituents for eastern regional water was 5.43 &plusmn;0.574 pCi/L for tritium, 0.0002048 &plusmn;0.0000054 pCi/L for chlorine-36, 0.000000865 &plusmn;0.000000015 pCi/L for iodine-129, &lt;0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.32 &plusmn;0.77 pCi/L for uranium-234, 0.016 &plusmn;0.012 pCi/L for uranium-235, and 0.477 &plusmn;0.044 pCi/L for uranium-238.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165056","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Bartholomay, R.C., and Hall, L.F., 2016, Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2016–5056, (DOE/ID-22237), 19 p.,\nhttps://dx.doi.org/10.3133/sir20165056.","productDescription":"Report: v, 19 p.; Appendixes A-C","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065188","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":321010,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5056 Report PDF"},{"id":321011,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixa.xlsx","text":"Appendix A","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix A"},{"id":321009,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5056/coverthb.jpg"},{"id":321012,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixb.xlsx","text":"Appendix B","size":"75 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix B"},{"id":321013,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixc.xlsx","text":"Appendix C","size":"81 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix C"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.75,\n              44.25\n            ],\n            [\n              -113.75,\n              43.30\n            ],\n            [\n              -112.25,\n              43.30\n            ],\n            [\n              -112.25,\n              44.25\n            ],\n            [\n              -113.75,\n              44.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, Idaho Water Science Center<br>U.S. Geological Survey<br>230 Collins Road<br>Boise, Idaho 83702<br><a href=\"http://id.water.usgs.gov\" data-mce-href=\"http://id.water.usgs.gov\">http://id.water.usgs.gov</a><br></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods of Data Analyses</li>\n<li>Background Concentrations of Selected Chemical Constituents</li>\n<li>Background Concentrations of Selected Radiochemical Constituents</li>\n<li>Summary</li>\n<li>References Cited</li>\n<li>Appendixes</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-05-05","noUsgsAuthors":false,"publicationDate":"2016-05-05","publicationStatus":"PW","scienceBaseUri":"572c609be4b09acee752ef88","contributors":{"authors":[{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, L. Flint","contributorId":168956,"corporation":false,"usgs":false,"family":"Hall","given":"L.","email":"","middleInitial":"Flint","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":627834,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70169129,"text":"ofr20161047 - 2016 - An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models","interactions":[],"lastModifiedDate":"2018-03-23T14:15:49","indexId":"ofr20161047","displayToPublicDate":"2016-05-05T16:00:00","publicationYear":"2016","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":"2016-1047","title":"An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models","docAbstract":"<p>The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161047","usgsCitation":"Rupp, D.E., 2016, An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models: U.S. Geological Survey Open-File Report 2016–1047, 32 p., https://dx.doi.org/10.3133/ofr20161047.","productDescription":"iv, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072786","costCenters":[{"id":565,"text":"Southeast Climate Science 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Introduction</li>\n<li>2. Data and Methods</li>\n<li>3. Results and Discussion of Model Ranking</li>\n<li>4. Model Performance by Metric</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-05-05","noUsgsAuthors":false,"publicationDate":"2016-05-05","publicationStatus":"PW","scienceBaseUri":"572c609ae4b09acee752ef7e","contributors":{"authors":[{"text":"David E. Rupp","contributorId":167687,"corporation":false,"usgs":false,"family":"David E. Rupp","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":623130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170272,"text":"sir20165052 - 2016 - Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington","interactions":[],"lastModifiedDate":"2024-12-04T19:23:30.813809","indexId":"sir20165052","displayToPublicDate":"2016-05-05T15:00:00","publicationYear":"2016","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":"2016-5052","title":"Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington","docAbstract":"<p>A groundwater-flow model was developed to improve understanding of water resources on the Kitsap Peninsula. The Kitsap Peninsula is in the Puget Sound lowland of west-central Washington, is bounded by Puget Sound on the east and by Hood Canal on the west, and covers an area of about 575 square miles. The peninsula encompasses all of Kitsap County, Mason County north of Hood Canal, and part of Pierce County west of Puget Sound. The peninsula is surrounded by saltwater, and the hydrologic setting is similar to that of an island. The study area is underlain by a thick sequence of unconsolidated glacial and interglacial deposits that overlie sedimentary and volcanic bedrock units that crop out in the central part of the study area. Twelve hydrogeologic units consisting of aquifers, confining units, and an underlying bedrock unit form the basis of the groundwater-flow model.</p><p>Groundwater flow on the Kitsap Peninsula was simulated using the groundwater-flow model, MODFLOW‑NWT. The finite difference model grid comprises 536 rows, 362 columns, and 14 layers. Each model cell has a horizontal dimension of 500 by 500 feet, and the model contains a total of 1,227,772 active cells. Groundwater flow was simulated for transient conditions. Transient conditions were simulated for January 1985–December 2012 using annual stress periods for 1985–2004 and monthly stress periods for 2005–2012. During model calibration, variables were adjusted within probable ranges to minimize differences between measured and simulated groundwater levels and stream baseflows. As calibrated to transient conditions, the model has a standard deviation for heads and flows of 47.04 feet and 2.46 cubic feet per second, respectively.</p><p>Simulated inflow to the model area for the 2005–2012 period from precipitation and secondary recharge was 585,323 acre-feet per year (acre-ft/yr) (93 percent of total simulated inflow ignoring changes in storage), and simulated inflow from stream and lake leakage was 43,905 acre-ft/yr (7 percent of total simulated inflow). Simulated outflow from the model primarily was through discharge to streams, lakes, springs, seeps, and Puget Sound (594,595 acre-ft/yr; 95 percent of total simulated outflow excluding changes in storage) and through withdrawals from wells (30,761 acre-ft/yr; 5 percent of total simulated outflow excluding changes in storage).</p><p>Six scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effects on water levels and stream baseflows of potential changes in groundwater withdrawals, in consumptive use, and in recharge. These included simulations of a steady-state system, no-pumping and return flows, 15-percent increase in current withdrawals in all wells, 80-percent decrease in outdoor water to simulate effects of conservation efforts, 15-percent decrease in recharge from precipitation to simulate a drought, and particle tracking to determine flow paths.</p><p>Changes in water-level altitudes and baseflow amounts vary depending on the stress applied to the system in these various scenarios. Reducing recharge by 15 percent between 2005 and 2012 had the largest effect, with water-level altitudes declining throughout the model domain and baseflow amounts decreasing by as much as 18 percent compared to baseline conditions. Changes in pumping volumes had a smaller effect on the model. Removing all pumping and resulting return flows caused increased water-level altitudes in many areas and increased baseflow amounts of between 1 and 3 percent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165052","collaboration":"Prepared in cooperation with Public Utility District No. 1 of Kitsap County","usgsCitation":"Frans, L.M. and Olsen, T.D., 2016, Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington (ver. 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5052, 63 p., https://dx.doi.org/10.3133/sir20165052.","productDescription":"vi, 63 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071099","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329281,"rank":3,"type":{"id":25,"text":"Version 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Cited</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-05-05","revisedDate":"2016-10-04","noUsgsAuthors":false,"publicationDate":"2016-05-05","publicationStatus":"PW","scienceBaseUri":"572c609be4b09acee752ef8e","contributors":{"authors":[{"text":"Frans, Lonna M. 0000-0002-3217-1862 lmfrans@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-1862","contributorId":1493,"corporation":false,"usgs":true,"family":"Frans","given":"Lonna","email":"lmfrans@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington 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,{"id":70170847,"text":"70170847 - 2016 - Holocene vegetation and fire history of the mountains of northern Sicily (Italy)","interactions":[],"lastModifiedDate":"2016-08-24T09:16:54","indexId":"70170847","displayToPublicDate":"2016-05-05T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5076,"text":"Vegetation History and Archaeobotany","active":true,"publicationSubtype":{"id":10}},"title":"Holocene vegetation and fire history of the mountains of northern Sicily (Italy)","docAbstract":"<p><span>Knowledge about vegetation and fire history of the mountains of Northern Sicily is scanty. We analysed five sites to fill this gap and used terrestrial plant macrofossils to establish robust radiocarbon chronologies. Palynological records from Gorgo Tondo, Gorgo Lungo, Marcato Cix&eacute;, Urgo Pietra Giordano and Gorgo Pollicino show that under natural or near natural conditions, deciduous forests (</span><i class=\"EmphasisTypeItalic \">Quercus pubescens</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Q. cerris</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Fraxinus ornus</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Ulmus</i><span>), that included a substantial portion of evergreen broadleaved species (</span><i class=\"EmphasisTypeItalic \">Q. suber</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Q. ilex</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Hedera helix</i><span>), prevailed in the upper meso-mediterranean belt. Mesophilous deciduous and evergreen broadleaved trees (</span><i class=\"EmphasisTypeItalic \">Fagus sylvatica</i><span>,&nbsp;</span><i class=\"EmphasisTypeItalic \">Ilex aquifolium</i><span>) dominated in the natural or quasi-natural forests of the oro-mediterranean belt. Forests were repeatedly opened for agricultural purposes. Fire activity was closely associated with farming, providing evidence that burning was a primary land use tool since Neolithic times. Land use and fire activity intensified during the Early Neolithic at 5000&nbsp;</span><span class=\"EmphasisTypeSmallCaps \">bc</span><span>, at the onset of the Bronze Age at 2500&nbsp;</span><span class=\"EmphasisTypeSmallCaps \">bc</span><span>&nbsp;and at the onset of the Iron Age at 800&nbsp;</span><span class=\"EmphasisTypeSmallCaps \">bc</span><span>. Our data and previous studies suggest that the large majority of open land communities in Sicily, from the coastal lowlands to the mountain areas below the thorny-cushion&nbsp;</span><i class=\"EmphasisTypeItalic \">Astragalus</i><span>&nbsp;belt (ca. 1,800&nbsp;m a.s.l.), would rapidly develop into forests if land use ceased. Mesophilous&nbsp;</span><i class=\"EmphasisTypeItalic \">Fagus</i><span>-</span><i class=\"EmphasisTypeItalic \">Ilex</i><span>&nbsp;forests developed under warm mid Holocene conditions and were resilient to the combined impacts of humans and climate. The past ecology suggests a resilience of these summer-drought adapted communities to climate warming of about 2&nbsp;&deg;C. Hence, they may be particularly suited to provide heat and drought-adapted</span><i class=\"EmphasisTypeItalic \">Fagus sylvatica</i><span>&nbsp;ecotypes for maintaining drought-sensitive Central European beech forests under global warming conditions.</span></p>","language":"English","publisher":"International Work Group for Palaeoethnobotany","publisherLocation":"Berlin","doi":"10.1007/s00334-016-0569-8","usgsCitation":"Tinner, W., Vescovi, E., Van Leeuwen, J., Colombaroli, D., Henne, P., Kaltenrieder, P., Morales-Molino, C., Beffa, G., Gnaegi, B., Van der Knaap, P.W., La Mantia, T., and Pasta, S., 2016, Holocene vegetation and fire history of the mountains of northern Sicily (Italy): Vegetation History and Archaeobotany, v. 25, no. 5, p. 499-519, https://doi.org/10.1007/s00334-016-0569-8.","productDescription":"21 p.","startPage":"499","endPage":"519","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071709","costCenters":[{"id":318,"text":"Geosciences and Environmental 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,{"id":70170856,"text":"70170856 - 2016 - Resource subsidies between stream and terrestrial ecosystems under global change","interactions":[],"lastModifiedDate":"2016-06-16T11:04:01","indexId":"70170856","displayToPublicDate":"2016-05-05T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Resource subsidies between stream and terrestrial ecosystems under global change","docAbstract":"<p><span>Streams and adjacent terrestrial ecosystems are characterized by permeable boundaries that are crossed by resource subsidies. Although the importance of these subsidies for riverine ecosystems is increasingly recognized, little is known about how they may be influenced by global environmental change. Drawing from available evidence, in this review we propose a conceptual framework to evaluate the effects of global change on the quality and spatiotemporal dynamics of stream&ndash;terrestrial subsidies. We illustrate how changes to hydrological and temperature regimes, atmospheric CO</span><span>2</span><span>&nbsp;concentration, land use and the distribution of nonindigenous species can influence subsidy fluxes by affecting the biology and ecology of donor and recipient systems and the physical characteristics of stream&ndash;riparian boundaries. Climate-driven changes in the physiology and phenology of organisms with complex life cycles will influence their development time, body size and emergence patterns, with consequences for adjacent terrestrial consumers. Also, novel species interactions can modify subsidy dynamics via complex bottom-up and top-down effects. Given the seasonality and pulsed nature of subsidies, alterations of the temporal and spatial synchrony of resource availability to consumers across ecosystems are likely to result in ecological mismatches that can scale up from individual responses, to communities, to ecosystems. Similarly, altered hydrology, temperature, CO</span><span>2</span><span>&nbsp;concentration and land use will modify the recruitment and quality of riparian vegetation, the timing of leaf abscission and the establishment of invasive riparian species. Along with morphological changes to stream&ndash;terrestrial boundaries, these will alter the use and fluxes of allochthonous subsidies associated with stream ecosystems. Future research should aim to understand how subsidy dynamics will be affected by key drivers of global change, including agricultural intensification, increasing water use and biotic homogenization. Our conceptual framework based on the match&ndash;mismatch between donor and recipient organisms may facilitate understanding of the multiple effects of global change and aid in the development of future research questions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13182","usgsCitation":"Larsen, S., Muehlbauer, J.D., and Marti Roca, M.E., 2016, Resource subsidies between stream and terrestrial ecosystems under global change: Global Change Biology, v. 22, no. 7, p. 2489-2504, https://doi.org/10.1111/gcb.13182.","productDescription":"16 p.","startPage":"2489","endPage":"2504","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067749","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-25","publicationStatus":"PW","scienceBaseUri":"572c609ce4b09acee752ef96","contributors":{"authors":[{"text":"Larsen, Stefano","contributorId":169188,"corporation":false,"usgs":false,"family":"Larsen","given":"Stefano","email":"","affiliations":[{"id":13099,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":628833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marti Roca, Maria Eugenia","contributorId":169189,"corporation":false,"usgs":false,"family":"Marti Roca","given":"Maria","email":"","middleInitial":"Eugenia","affiliations":[{"id":25434,"text":"Centre d'Estudis Avancats de Blanes","active":true,"usgs":false}],"preferred":false,"id":628834,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170857,"text":"70170857 - 2016 - Reconstruction of far-field tsunami amplitude distributions from earthquake sources","interactions":[],"lastModifiedDate":"2020-10-16T16:33:23.199279","indexId":"70170857","displayToPublicDate":"2016-05-05T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Reconstruction of far-field tsunami amplitude distributions from earthquake sources","docAbstract":"<p><span>The probability distribution of far-field tsunami amplitudes is explained in relation to the distribution of seismic moment at subduction zones. Tsunami amplitude distributions at tide gauge stations follow a similar functional form, well described by a tapered Pareto distribution that is parameterized by a power-law exponent and a&nbsp;corner amplitude. Distribution parameters are first established for eight tide gauge stations in the Pacific, using maximum likelihood estimation. A procedure is then developed to reconstruct the tsunami amplitude distribution that consists of four steps: (1) define the distribution of seismic moment at subduction zones; (2) establish a source-station scaling relation from regression analysis; (3) transform the seismic moment distribution to a tsunami amplitude distribution for each subduction zone; and (4) mix the transformed distribution for all subduction zones to an aggregate tsunami amplitude distribution specific to the tide gauge station. The tsunami amplitude distribution is adequately reconstructed for four tide gauge stations using globally constant seismic moment distribution parameters established in previous studies. In comparisons to empirical tsunami amplitude distributions from maximum likelihood estimation, the reconstructed distributions consistently exhibit higher corner amplitude values, implying that in most cases, the empirical catalogs are too short to include the largest amplitudes. Because the reconstructed distribution is based on a catalog of earthquakes that is much larger than the tsunami catalog, it is less susceptible to the effects of record-breaking events and more indicative of the actual distribution of tsunami amplitudes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-016-1288-x","usgsCitation":"Geist, E.L., and Parsons, T.E., 2016, Reconstruction of far-field tsunami amplitude distributions from earthquake sources: Pure and Applied Geophysics, v. 173, no. 12, p. 3703-3717, https://doi.org/10.1007/s00024-016-1288-x.","productDescription":"15 p.","startPage":"3703","endPage":"3717","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072794","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, United States","state":"Hawaii","city":"Crescent City, Hilo, Kahului, Kushimoto, Mera, Nawiliwili, San Diego, San Francisco","volume":"173","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572c609ce4b09acee752ef92","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":628835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":628836,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170799,"text":"70170799 - 2016 - Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","interactions":[],"lastModifiedDate":"2018-09-12T17:04:25","indexId":"70170799","displayToPublicDate":"2016-05-05T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","docAbstract":"<p><span>Animal waste, stream water, and streambed sediment from 19 small (&lt;&nbsp;32&nbsp;km</span><sup>2</sup><span>) watersheds in 12&nbsp;U.S. states having either no major animal agriculture (control, </span><i>n</i><span>&nbsp;=&nbsp;4), or predominantly beef (</span><i>n</i><span>&nbsp;=&nbsp;4), dairy (</span><i>n</i><span>&nbsp;=&nbsp;3), swine (</span><i>n</i><span>&nbsp;=&nbsp;5), or poultry (</span><i>n</i><span>&nbsp;=&nbsp;3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic </span><i>Escherichia coli</i><span>, </span><i>Salmonella</i><span>, </span><i>Campylobacter</i><span>, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (</span><i>stx1</i><span>) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic </span><i>E. coli</i><span>, </span><i>Salmonella</i><span>, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.04.087","usgsCitation":"Haack, S.K., Duris, J., Kolpin, D.W., Focazio, M.J., Meyer, M.T., Johnson, H., Oster, R.J., and Foreman, W., 2016, Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture: Science of the Total Environment, v. 563-564, p. 340-350, https://doi.org/10.1016/j.scitotenv.2016.04.087.","productDescription":"11 p.","startPage":"340","endPage":"350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059123","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology 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,{"id":70170860,"text":"70170860 - 2016 - Avian fatalities at wind energy facilities in North America: A comparison of recent approaches","interactions":[],"lastModifiedDate":"2020-12-21T15:15:50.70427","indexId":"70170860","displayToPublicDate":"2016-05-05T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Avian fatalities at wind energy facilities in North America: A comparison of recent approaches","docAbstract":"<p>Three recent publications have estimated the number of birds killed each year by wind energy facilities at 2012 build-out levels in the United States. The 3 publications differ in scope, methodology, and resulting estimates. We compare and contrast characteristics of the approaches used in the publications. In addition, we describe decisions made in obtaining the estimates that were produced. Despite variation in the 3 approaches, resulting estimates were reasonably similar; about a quarter- to a half-million birds are killed per year by colliding with wind turbines.</p>","language":"English","publisher":"Jack H. Berryman Institute","publisherLocation":"Logan, UT","doi":"10.26077/a4ec-ed37","usgsCitation":"Johnson, D.H., Loss, S., Smallwood, K.S., and Erickson, W.P., 2016, Avian fatalities at wind energy facilities in North America: A comparison of recent approaches: Human-Wildlife Interactions, v. 10, no. 1, p. 7-18, https://doi.org/10.26077/a4ec-ed37.","productDescription":"12 p.","startPage":"7","endPage":"18","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064122","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":321023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North 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Shawn","contributorId":25899,"corporation":false,"usgs":true,"family":"Smallwood","given":"K.","email":"","middleInitial":"Shawn","affiliations":[],"preferred":false,"id":628845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Wallace P.","contributorId":78627,"corporation":false,"usgs":true,"family":"Erickson","given":"Wallace","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":628846,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70170861,"text":"70170861 - 2016 - Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters","interactions":[],"lastModifiedDate":"2016-07-07T10:09:23","indexId":"70170861","displayToPublicDate":"2016-05-05T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters","docAbstract":"<div data-canvas-width=\"572.1859499999999\">\n<p>We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish <i>Pterois volitans </i>(Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities &lt;30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.</p>\n</div>","language":"English","publisher":"REABIC","doi":"10.3391/ai.2016.11.3.09","usgsCitation":"Evangelista, P.H., Young, N.E., Schofield, P., and Jarnevich, C.S., 2016, Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters: Aquatic Invasions, v. 11, no. 3, p. 313-326, https://doi.org/10.3391/ai.2016.11.3.09.","productDescription":"14 p.","startPage":"313","endPage":"326","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064408","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471019,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2016.11.3.09","text":"Publisher Index 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,{"id":70170867,"text":"70170867 - 2016 - Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas","interactions":[],"lastModifiedDate":"2016-06-24T11:26:38","indexId":"70170867","displayToPublicDate":"2016-05-05T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas","docAbstract":"<p><span>Likelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1-year period of earthquake data and use of 10&ndash;20-km smoothing distances produced the greatest likelihood. The likelihood that the locations of January&ndash;June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple-fold benefit from smoothed seismicity models in developing short-term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.</span></p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL068948","usgsCitation":"Moschetti, M.P., Hoover, S.M., and Mueller, C., 2016, Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas: Geophysical Research Letters, v. 43, no. 10, p. 4913-4921, https://doi.org/10.1002/2016GL068948.","productDescription":"9 p.","startPage":"4913","endPage":"4921","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075465","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068948","text":"Publisher Index Page"},{"id":321014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.537109375,\n              33.58716733904656\n            ],\n            [\n              -97.679443359375,\n              33.61461929233378\n            ],\n            [\n              -99.38232421875,\n              36.53612263184686\n            ],\n            [\n              -99.51416015625,\n              37.00255267215955\n            ],\n            [\n              -98.41552734375,\n              37.413800350662875\n            ],\n            [\n              -97.3828125,\n              37.54457732085582\n            ],\n            [\n              -95.592041015625,\n              35.16482750605027\n            ],\n            [\n              -95.537109375,\n              33.58716733904656\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"43","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"572dc04ee4b0dae0d5d8f207","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70176578,"text":"70176578 - 2016 - Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A. ","interactions":[],"lastModifiedDate":"2016-09-21T16:15:13","indexId":"70176578","displayToPublicDate":"2016-05-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A. ","docAbstract":"<div data-canvas-width=\"323.1421199999999\">Early detection of invasive species is critical to increasing the probability of successful management. At the primary stage of an invasion, invasive species are easier to control as the population is likely represented by just a few individuals. Detection of these first few individuals can be challenging, particularly if they are cryptic or otherwise characterized by low detectability. The engagement of members of the public may be critical to early detection as there are far more citizen s on the landscape than trained biologists. However, it can be difficult to assess the credibility of public reporting, especially when a diagnostic digital image or a physical specimen in good condition are lacking. DNA barcoding can be used for verification when morphological identification of a specimen is not possible or uncertain (i.e., degraded or partial specimen). DNA barcoding relies on obtaining a DNA sequence from a relatively small fragment of mitochondrial DNA and comparing it to a database of sequences containing a variety of expertly identified species. He rein we report the successful identification of a degraded specimen of a non-native, potentially invasive reptile species (<i>Varanus niloticus</i>) via DNA barcoding, after discovery and reporting by a member of the public.</div>","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/mbi.2016.7.2.07","usgsCitation":"Reed, R., Hopken, M.W., Steen, D.A., Falk, B.G., and Piaggio, A.J., 2016, Integrating early detection with DNA barcoding: species identification of a non-native monitor lizard (Squamata: Varanidae) carcass in Mississippi, U.S.A. : Management of Biological Invasions, v. 7, no. 2, p. 193-197, https://doi.org/10.3391/mbi.2016.7.2.07.","productDescription":"5 p.","startPage":"193","endPage":"197","ipdsId":"IP-074386","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2016.7.2.07","text":"Publisher Index Page"},{"id":328836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","county":"Jackson County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.42140197753906,\n              30.636139632397274\n            ],\n            [\n              -88.42140197753906,\n              30.64854572202601\n            ],\n            [\n              -88.40835571289062,\n              30.64854572202601\n            ],\n            [\n              -88.40835571289062,\n              30.636139632397274\n            ],\n            [\n              -88.42140197753906,\n              30.636139632397274\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c6bce4b0bc0bec09cb10","contributors":{"authors":[{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":141036,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":649258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopken, Matthew W.","contributorId":174772,"corporation":false,"usgs":false,"family":"Hopken","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":649259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steen, David A.","contributorId":92961,"corporation":false,"usgs":true,"family":"Steen","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":649260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falk, Bryan G. bfalk@usgs.gov","contributorId":141179,"corporation":false,"usgs":true,"family":"Falk","given":"Bryan","email":"bfalk@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":649261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piaggio, Antoinette J.","contributorId":174782,"corporation":false,"usgs":false,"family":"Piaggio","given":"Antoinette","email":"","middleInitial":"J.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":649262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170226,"text":"pp1823 - 2016 - Long-term continuous acoustical suspended-sediment measurements in rivers - Theory, application, bias, and error","interactions":[],"lastModifiedDate":"2016-07-18T10:20:32","indexId":"pp1823","displayToPublicDate":"2016-05-04T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1823","title":"Long-term continuous acoustical suspended-sediment measurements in rivers - Theory, application, bias, and error","docAbstract":"<p>It is commonly recognized that suspended-sediment concentrations in rivers can change rapidly in time and independently of water discharge during important sediment‑transporting events (for example, during floods); thus, suspended-sediment measurements at closely spaced time intervals are necessary to characterize suspended‑sediment loads. Because the manual collection of sufficient numbers of suspended-sediment samples required to characterize this variability is often time and cost prohibitive, several “surrogate” techniques have been developed for in situ measurements of properties related to suspended-sediment characteristics (for example, turbidity, laser-diffraction, acoustics). Herein, we present a new physically based method for the simultaneous measurement of suspended-silt-and-clay concentration, suspended-sand concentration, and suspended‑sand median grain size in rivers, using multi‑frequency arrays of single-frequency side‑looking acoustic-Doppler profilers. The method is strongly grounded in the extensive scientific literature on the incoherent scattering of sound by random suspensions of small particles. In particular, the method takes advantage of theory that relates acoustic frequency, acoustic attenuation, acoustic backscatter, suspended-sediment concentration, and suspended-sediment grain-size distribution. We develop the theory and methods, and demonstrate the application of the method at six study sites on the Colorado River and Rio Grande, where large numbers of suspended-sediment samples have been collected concurrently with acoustic attenuation and backscatter measurements over many years. The method produces acoustical measurements of suspended-silt-and-clay and suspended-sand concentration (in units of mg/L), and acoustical measurements of suspended-sand median grain size (in units of mm) that are generally in good to excellent agreement with concurrent physical measurements of these quantities in the river cross sections at these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.</p><p>Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1823","usgsCitation":"Topping, D.J., and Wright, S.A., 2016, Long-term continuous acoustical suspended-sediment measurements in rivers—Theory, application, bias, and error: U.S. Geological Survey Professional Paper 1823, 98 p.,\nhttps://dx.doi.org/10.3133/pp1823.","productDescription":"xii, 97 p.","numberOfPages":"114","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062803","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1823/coverthb.jpg"},{"id":320827,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1823/pp1823.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1823 Report PDF"}],"country":"United States","state":"Arizona, Texas","otherGeospatial":"Colorado River, Grand Canyon National Park; Rio Grande, Big Bend National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.5384521484375,\n              36.01578220325809\n            ],\n            [\n              -112.5384521484375,\n              36.41907231092499\n            ],\n            [\n              -111.86553955078124,\n              36.41907231092499\n            ],\n            [\n              -111.86553955078124,\n              36.01578220325809\n            ],\n            [\n              -112.5384521484375,\n              36.01578220325809\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.76174926757812,\n              28.96489485992114\n            ],\n            [\n              -103.76174926757812,\n              29.410890376109\n            ],\n            [\n              -102.82241821289062,\n              29.410890376109\n            ],\n            [\n              -102.82241821289062,\n              28.96489485992114\n            ],\n            [\n              -103.76174926757812,\n              28.96489485992114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://sbsc.wr.usgs.gov/about/contact/personnel.aspx\" data-mce-href=\"http://sbsc.wr.usgs.gov/about/contact/personnel.aspx\">SBSC staff</a>, Southwest Biological Science Center<br>U.S. Geological Survey<br>2255 N. Gemini Drive<br>Flagstaff, AZ 86001<br><a href=\"http://sbsc.wr.usgs.gov/\" data-mce-href=\"http://sbsc.wr.usgs.gov/\">http://sbsc.wr.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Instruments, Study Sites, and Field Methods</li>\n<li>Theoretical Framework</li>\n<li>Procedure for Applying Method</li>\n<li>Results</li>\n<li>Introduction to the Analyses of Bias and Error</li>\n<li>Error Analysis</li>\n<li>Conclusions</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n<li>Appendixes 1-9</li>\n</ul>\n<p>&nbsp;</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f7","contributors":{"authors":[{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":626542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626543,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70169399,"text":"ofr20161054 - 2016 - Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","interactions":[],"lastModifiedDate":"2016-05-04T15:49:10","indexId":"ofr20161054","displayToPublicDate":"2016-05-04T15:15:00","publicationYear":"2016","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":"2016-1054","title":"Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","docAbstract":"<p>The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of &minus;40 to 60 degrees Celsius (&deg;C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer&rsquo;s specifications with bench tests, for recording data over the device&rsquo;s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.</p>\n<p>The procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer&rsquo;s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer&rsquo;s specifications. It was also observed that enabling WiFi doubles the Storm 3&rsquo;s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p.,  https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"<p>Chief, Hydrologic Instrumentation Facility<br /> U.S. Geological Survey<br /> Building 2101<br /> Stennis Space Center, MS 39529<br /> <a href=\"http://water.usgs.gov/hif/\">http://water.usgs.gov/hif/</a></p>","tableOfContents":"<ul>\n<li>Abstract&nbsp;</li>\n<li>Introduction</li>\n<li>Description of the Storm 3 Data Logger&nbsp;</li>\n<li>Methods</li>\n<li>Results</li>\n<li>Summary</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f1","contributors":{"authors":[{"text":"Kunkle, Gerald A. gkunkle@usgs.gov","contributorId":167907,"corporation":false,"usgs":true,"family":"Kunkle","given":"Gerald A.","email":"gkunkle@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":624025,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170844,"text":"70170844 - 2016 - Hydrothermal vents and methane seeps: Rethinking the sphere of influence","interactions":[],"lastModifiedDate":"2016-05-19T10:47:06","indexId":"70170844","displayToPublicDate":"2016-05-04T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal vents and methane seeps: Rethinking the sphere of influence","docAbstract":"<p><span>Although initially viewed as oases within a barren deep ocean, hydrothermal vent and methane seep communities are now recognized to interact with surrounding ecosystems on the sea floor and in the water column, and to affect global geochemical cycles. The importance of understanding these interactions is growing as the potential rises for disturbance from oil and gas extraction, seabed mining and bottom trawling. Here we synthesize current knowledge of the nature, extent and time and space scales of vent and seep interactions with background systems. We document an expanded footprint beyond the site of local venting or seepage with respect to elemental cycling and energy flux, habitat use, trophic interactions, and connectivity. Heat and energy are released, global biogeochemical and elemental cycles are modified, and particulates are transported widely in plumes. Hard and biotic substrates produced at vents and seeps are used by &ldquo;benthic background&rdquo; fauna for attachment substrata, shelter, and access to food via grazing or through position in the current, while particulates and fluid fluxes modify planktonic microbial communities. Chemosynthetic production provides nutrition to a host of benthic and planktonic heterotrophic background species through multiple horizontal and vertical transfer pathways assisted by flow, gamete release, animal movements, and succession, but these pathways remain poorly known. Shared species, genera and families indicate that ecological and evolutionary connectivity exists among vents, seeps, organic falls and background communities in the deep sea; the genetic linkages with inactive vents and seeps and background assemblages however, are practically unstudied. The waning of venting or seepage activity generates major transitions in space and time that create links to surrounding ecosystems, often with identifiable ecotones or successional stages. The nature of all these interactions is dependent on water depth, as well as regional oceanography and biodiversity. Many ecosystem services are associated with the interactions and transitions between chemosynthetic and background ecosystems, for example carbon cycling and sequestration, fisheries production, and a host of non-market and cultural services. The quantification of the sphere of influence of vents and seeps could be beneficial to better management of deep-sea environments in the face of growing industrialization.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2016.00072","usgsCitation":"Levin, L.A., Baco, A., Bowden, D., Colaco, A., Cordes, E.E., Cunha, M., Demopoulos, A.W., Gobin, J., Grupe, B., Le, J., Metaxas, A., Netburn, A., Rouse, G., Thurber, A., Tunnicliffe, V., Van Dover, C., Vanreusel, A., and Watling, L., 2016, Hydrothermal vents and methane seeps: Rethinking the sphere of influence: Frontiers in Marine Science, v. 3, art72: 23 p., https://doi.org/10.3389/fmars.2016.00072.","productDescription":"art72: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00072","text":"Publisher Index Page"},{"id":320952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f4","contributors":{"authors":[{"text":"Levin, Lisa A.","contributorId":12372,"corporation":false,"usgs":true,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baco, Amy","contributorId":120023,"corporation":false,"usgs":true,"family":"Baco","given":"Amy","email":"","affiliations":[],"preferred":false,"id":628685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, David","contributorId":10864,"corporation":false,"usgs":true,"family":"Bowden","given":"David","email":"","affiliations":[],"preferred":false,"id":628686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colaco, Ana","contributorId":169152,"corporation":false,"usgs":false,"family":"Colaco","given":"Ana","email":"","affiliations":[{"id":25423,"text":"Univ. of the Azores","active":true,"usgs":false}],"preferred":false,"id":628687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":628688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunha, Marina","contributorId":169153,"corporation":false,"usgs":false,"family":"Cunha","given":"Marina","email":"","affiliations":[{"id":25424,"text":"Univ. de Aveiro","active":true,"usgs":false}],"preferred":false,"id":628689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gobin, Judith","contributorId":169154,"corporation":false,"usgs":false,"family":"Gobin","given":"Judith","email":"","affiliations":[{"id":25425,"text":"Univ. West Indies","active":true,"usgs":false}],"preferred":false,"id":628690,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grupe, Ben","contributorId":169155,"corporation":false,"usgs":false,"family":"Grupe","given":"Ben","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628691,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Le, Jennifer","contributorId":169163,"corporation":false,"usgs":false,"family":"Le","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":628692,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metaxas, Anna","contributorId":169156,"corporation":false,"usgs":false,"family":"Metaxas","given":"Anna","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":628693,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Netburn, Amanda","contributorId":169157,"corporation":false,"usgs":false,"family":"Netburn","given":"Amanda","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628694,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rouse, Greg","contributorId":169158,"corporation":false,"usgs":false,"family":"Rouse","given":"Greg","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628695,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":628696,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tunnicliffe, Verena","contributorId":169160,"corporation":false,"usgs":false,"family":"Tunnicliffe","given":"Verena","email":"","affiliations":[{"id":25427,"text":"Univ. of Victoria","active":true,"usgs":false}],"preferred":false,"id":628697,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Dover, Cindy L.","contributorId":95341,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy L.","affiliations":[],"preferred":false,"id":628698,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vanreusel, Ann","contributorId":169161,"corporation":false,"usgs":false,"family":"Vanreusel","given":"Ann","email":"","affiliations":[{"id":25428,"text":"Ghent Univ.","active":true,"usgs":false}],"preferred":false,"id":628699,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":628714,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70170821,"text":"70170821 - 2016 - Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","interactions":[],"lastModifiedDate":"2016-07-28T10:53:13","indexId":"70170821","displayToPublicDate":"2016-05-04T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","docAbstract":"<p><span>Dune destabilization and increased mobility is a worldwide issue causing ecological, economic, and health problems for the inhabitants of areas with extensive dune fields. Dunes cover nearly a third of the Navajo Nation within the Colorado Plateau of southwestern USA. There, higher temperatures and prolonged drought beginning in 1996 have produced significant increases in dune mobility. Vegetation plays an important role in dune stabilization, but there are few studies of the plants of the aeolian surfaces of this region. We examined plant species and their attributes within a moderately vegetated dune field of the Navajo Nation to understand the types and characteristics of plants that stabilize rangeland dunes. These dunes supported a low cover of mixed grass-scrubland with fifty-two perennial and annual species including extensive occurrence of non-native annual&nbsp;</span><i>Salsola</i><span>&nbsp;spp. Perennial grass richness and shrub cover were positively associated with increased soil sand composition. Taprooted shrubs were more common on sandier substrates. Most dominant grasses had C4 photosynthesis, suggestive of higher water-use efficiencies and growth advantage in warm arid environments. Plant cover was commonly below the threshold of dune stabilization. Increasing sand movement with continued aridity will select for plants adapted to burial, deflation, and abrasion. The study indicates plants tolerant of increased sand mobility and burial but more investigation is needed to identify the plants adapted to establish and regenerate under these conditions. In addition, the role of&nbsp;</span><i>Salsola</i><span>&nbsp;spp. in promoting decline of perennial grasses and shrubs needs clarification.</span></p>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1138157","usgsCitation":"Thomas, K.A., and Redsteer, M.H., 2016, Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA: Arid Land Research and Management, v. 30, no. 4, p. 400-411, https://doi.org/10.1080/15324982.2016.1138157.","productDescription":"12 p.","startPage":"400","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063167","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502595,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":320950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Navajo Nation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.3134765625,\n              34.56085936708387\n            ],\n            [\n              -111.3134765625,\n              38.22091976683121\n            ],\n            [\n              -107.29248046875,\n              38.22091976683121\n            ],\n            [\n              -107.29248046875,\n              34.56085936708387\n            ],\n            [\n              -111.3134765625,\n              34.56085936708387\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"572b0f1ce4b0b13d391a8407","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redsteer, Margaret H.","contributorId":9123,"corporation":false,"usgs":true,"family":"Redsteer","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":628555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170814,"text":"70170814 - 2016 - Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","interactions":[],"lastModifiedDate":"2016-05-04T10:03:24","indexId":"70170814","displayToPublicDate":"2016-05-04T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","docAbstract":"<p><span>Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel&rsquo;s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w8050184","usgsCitation":"Snedden, G., 2016, Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain: Water, v. 8, no. 5, Article 184: 15 p., https://doi.org/10.3390/w8050184.","productDescription":"Article 184: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8050184","text":"Publisher Index Page"},{"id":320948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Houma Navigation Canal","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.74844360351562,\n              29.216904948184734\n            ],\n            [\n              -90.74844360351562,\n              29.58898286696141\n            ],\n            [\n              -90.604248046875,\n              29.58898286696141\n            ],\n            [\n              -90.604248046875,\n              29.216904948184734\n            ],\n            [\n              -90.74844360351562,\n              29.216904948184734\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572b0f19e4b0b13d391a83ec","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170954,"text":"70170954 - 2016 - Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","interactions":[],"lastModifiedDate":"2016-05-13T09:18:39","indexId":"70170954","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","docAbstract":"<p><span>Most research on the effects of wildfires on stream water quality has focused on suspended sediment and nutrients in streams and water bodies, and relatively little research has examined the effects of wildfires on trace elements. The purpose of this study was two-fold: 1) to determine the effect of the 2009 Station Fire in the Angeles National Forest northeast of Los Angeles, CA on trace element concentrations in streams, and 2) compare trace elements in post-fire stormflow water quality to criteria for aquatic life to determine if trace elements reached concentrations that can harm aquatic life. Pre-storm and stormflow water-quality samples were collected in streams located inside and outside of the burn area of the Station Fire. Ash and burned soil samples were collected from several locations within the perimeter of the Station Fire. Filtered concentrations of Fe, Mn, and Hg and total concentrations of most trace elements in storm samples were elevated as a result of the Station Fire. In contrast, filtered concentrations of Cu, Pb, Ni, and Se and total concentrations of Cu were elevated primarily due to storms and not the Station Fire. Total concentrations of Se and Zn were elevated as a result of both storms and the Station Fire. Suspended sediment in stormflows following the Station Fire was an important transport mechanism for trace elements. Cu, Pb, and Zn primarily originate from ash in the suspended sediment. Fe primarily originates from burned soil in the suspended sediment. As, Mn, and Ni originate from both ash and burned soil. Filtered concentrations of trace elements in stormwater samples affected by the Station Fire did not reach levels that were greater than criteria established for aquatic life. Total concentrations for Fe, Pb, Ni, and Zn were detected at concentrations above criteria established for aquatic life.</span></p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0153372","collaboration":"Amphibian Research and Monitoring Initiative (BRD) Mineral Resources Program (USGS)","usgsCitation":"Burton, C.A., Hoefen, T.M., Plumlee, G.S., Baumberger, K., Backlin, A.R., Gallegos, E., and Fisher, R.N., 2016, Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California: PLoS ONE, v. 11, no. 5, https://doi.org/10.1371/journal.pone.0153372.","productDescription":"26 p.","startPage":"e0153372","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0153372","text":"Publisher Index Page"},{"id":321203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321176,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1371/journal.pone.0153372."}],"country":"United States","state":"California","otherGeospatial":"Angeles National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.466667,\n              34.625\n            ],\n            [\n              -118.466667,\n              34.125\n            ],\n            [\n              -117.6875,\n              34.125\n            ],\n            [\n              -117.6875,\n              34.625\n            ],\n            [\n              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thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":629207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumberger, Katherine L. kbaumberger@usgs.gov","contributorId":5870,"corporation":false,"usgs":true,"family":"Baumberger","given":"Katherine L.","email":"kbaumberger@usgs.gov","affiliations":[],"preferred":true,"id":629208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research 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,{"id":70174006,"text":"70174006 - 2016 - Spatially explicit control of invasive species using a reaction-diffusion model","interactions":[],"lastModifiedDate":"2016-09-02T09:35:37","indexId":"70174006","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit control of invasive species using a reaction-diffusion model","docAbstract":"<p>Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction&ndash;diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction&ndash;diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction&ndash;diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.</p>","language":"English","publisher":"Elsevier : ScienceDirect","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2016.05.013","usgsCitation":"Bonneau, M., Johnson, F.A., and Romagosa, C., 2016, Spatially explicit control of invasive species using a reaction-diffusion model: Ecological Modelling, v. 337, p. 15-24, https://doi.org/10.1016/j.ecolmodel.2016.05.013.","productDescription":"10 p.","startPage":"15","endPage":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061162","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"337","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6bce4b07657d1a22959","contributors":{"authors":[{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":640258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":640257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":640259,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170139,"text":"sir20165046 - 2016 - Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","interactions":[],"lastModifiedDate":"2021-10-12T17:00:16.258141","indexId":"sir20165046","displayToPublicDate":"2016-05-04T10:00:00","publicationYear":"2016","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":"2016-5046","title":"Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","docAbstract":"<p>The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model <i>air2water</i> was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.</p><p>The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.</p><p>The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165046","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wood, T.M., Wherry, S.A., Piccolroaz, S., and Girdner, S.F., 2016, Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099: U.S. Geological Survey Scientific Investigations Report 2016–5046, 43 p. https://doi.org/10.3133/sir20165046","productDescription":"vii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066051","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":320860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-5046 Report PDF"},{"id":320859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5046/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.18616485595703,\n              42.892567248047285\n            ],\n            [\n              -122.18616485595703,\n              42.986065036562955\n            ],\n            [\n              -122.03922271728514,\n              42.986065036562955\n            ],\n            [\n              -122.03922271728514,\n              42.892567248047285\n            ],\n            [\n              -122.18616485595703,\n              42.892567248047285\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: February 2020; Version 1.0: October 2016","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, Oregon Water Science Center<br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201<br><a href=\"http://or.water.usgs.gov\" data-mce-href=\"http://or.water.usgs.gov\">http://or.water.usgs.gov</a><br></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods</li>\n<li>One-Dimensional Lake Temperature Modeling</li>\n<li>Results of Future Climate Scenarios</li>\n<li>Comparisons to Future-Climate Studies of Other Lakes</li>\n<li>Conclusions</li>\n<li>Summary</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1be4b0b13d391a8403","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":626264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piccolroaz, Sebastiano","contributorId":168525,"corporation":false,"usgs":false,"family":"Piccolroaz","given":"Sebastiano","email":"","affiliations":[{"id":25322,"text":"University of Trento","active":true,"usgs":false}],"preferred":false,"id":626265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Girdner, Scott F","contributorId":168526,"corporation":false,"usgs":false,"family":"Girdner","given":"Scott","email":"","middleInitial":"F","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":626266,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178255,"text":"70178255 - 2016 - Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","interactions":[],"lastModifiedDate":"2016-11-09T15:29:43","indexId":"70178255","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","docAbstract":"<p>The goal of this study was to map rainfed and irrigated <i>rice-fallow</i> cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. <i>Rice-fallow</i> cropland areas are those areas where rice is grown during the <i>kharif</i> growing season (June–October), followed by a fallow during the <i>rabi</i> season (November–February). These cropland areas are not suitable for growing <i>rabi</i>-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (<i>Cicer arietinum</i> L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated <i>rice-fallow</i> croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (<i>kharif</i>) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left <i>fallow</i> during the second (<i>rabi</i>) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during <i>rabi</i> season. Existing irrigated or rainfed crops such as rice or wheat that were grown during <i>kharif</i> were not considered suitable for growing during the <i>rabi</i> season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable <i>rice-fallow</i> areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.</p>","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              83.97949218750001,\n              15.284185114076433\n            ],\n            [\n              82.3095703125,\n              11.996338401936226\n            ],\n            [\n              83.32031250000001,\n              7.754537346539373\n            ],\n            [\n              81.78222656250001,\n              5.266007882805485\n            ],\n            [\n              79.365234375,\n              5.747174076651375\n            ],\n            [\n              76.81640625,\n              7.406047717076271\n            ],\n            [\n              72.59765625,\n              12.382928338487396\n            ],\n            [\n              66.4013671875,\n              25.64152637306577\n            ],\n            [\n              80.4638671875,\n              29.11377539511439\n            ],\n            [\n              95.61523437500003,\n              30.34192736497245\n            ],\n            [\n              91.62597656250001,\n              20.67390526467282\n            ],\n            [\n              83.97949218750001,\n              15.284185114076433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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