{"pageNumber":"315","pageRowStart":"7850","pageSize":"25","recordCount":41075,"records":[{"id":70208927,"text":"70208927 - 2019 - Morphodynamic modelling of the wilderness breach, Fire Island, New York. Part I: Model set-up and validation","interactions":[],"lastModifiedDate":"2020-03-06T06:43:53","indexId":"70208927","displayToPublicDate":"2019-12-11T06:42:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Morphodynamic modelling of the wilderness breach, Fire Island, New York. Part I: Model set-up and validation","docAbstract":"On October 29, 2012, storm surge and large waves produced by Hurricane 13 Sandy resulted in the formation of a breach in eastern Fire Island, NY. The goals of this study 14 are to gain a better understanding of the physical processes that govern breach behavior and 15 to assess whether process-based models can be used to forecast the evolution of future 16 breaches. The Wilderness Breach grew rapidly in size during the first winter following 17 formation. Growth of the breach was accompanied by the formation of a complex of flood 18 shoals inside Great South Bay, a primary channel that flowed through the eastern part of the 19 flood shoals, and an ebb shoal on the ocean side of the breach. From the summer of 2013 20 through late 2015, the breach continued to change and evolve, albeit at a much slower pace 21 than in the first year after formation. A hybrid combination of Delft3D and XBeach models is 22 used to hindcast the morphodynamic evolution of the Wilderness Breach over the first three 23 years after formation. The formation of the breach during Hurricane Sandy is not part of the 24 simulations. Model simulations are initiated with a post-storm topography in which the 25 breach is already present. The models are capable of hindcasting the main morphodynamic 26 changes of the Wilderness Breach. The spatial patterns, as well as the bulk statistics, such as 27\n2\nbreach geometry and sediment volume changes, are reasonably 28 well reproduced by the model.\n29 The model sheds light on previously unknown processes of breach evolution, especially\n30 regarding sediment transport and flow regimes within the breach complex.","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2019.103621","usgsCitation":"van Ormondt, M., Nelson, T., Hapke, C., and Roelvink, D., 2019, Morphodynamic modelling of the wilderness breach, Fire Island, New York. Part I: Model set-up and validation: Coastal Engineering, v. 157, 103621, https://doi.org/10.1016/j.coastaleng.2019.103621.","productDescription":"103621","ipdsId":"IP-092135","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":458984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2019.103621","text":"Publisher Index Page"},{"id":372984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.27880859375,\n              40.61186744303007\n            ],\n            [\n              -72.82699584960938,\n              40.7202010588415\n            ],\n            [\n              -72.49465942382812,\n              40.82731951134558\n            ],\n            [\n              -72.55233764648438,\n              40.83563216247778\n            ],\n            [\n              -72.89016723632812,\n              40.74413568925235\n            ],\n            [\n              -73.21151733398436,\n              40.65147128144057\n            ],\n            [\n              -73.32138061523438,\n              40.62646106367355\n            ],\n            [\n              -73.27880859375,\n              40.61186744303007\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"157","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"van Ormondt, Maarten","contributorId":200365,"corporation":false,"usgs":false,"family":"van Ormondt","given":"Maarten","email":"","affiliations":[],"preferred":false,"id":784059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Timothy 0000-0002-5005-7617 trnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-5005-7617","contributorId":191933,"corporation":false,"usgs":true,"family":"Nelson","given":"Timothy","email":"trnelson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":784058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl","contributorId":223086,"corporation":false,"usgs":false,"family":"Hapke","given":"Cheryl","affiliations":[{"id":40668,"text":"formerly with USGS SPCMSC","active":true,"usgs":false}],"preferred":false,"id":784057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":784060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208034,"text":"70208034 - 2019 - Species recovery and recolonization of past habitats: Lessons for science and conservation from sea otters in estuaries","interactions":[],"lastModifiedDate":"2020-01-24T17:33:55","indexId":"70208034","displayToPublicDate":"2019-12-10T17:16:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Species recovery and recolonization of past habitats: Lessons for science and conservation from sea otters in estuaries","docAbstract":"<p><span>Recovering species are often limited to much smaller areas than they historically occupied. Conservation planning for the recovering species is often based on this limited range, which may simply be an artifact of where the surviving population persisted. Southern sea otters (</span><i>Enhydra lutris nereis</i><span>) were hunted nearly to extinction but recovered from a small remnant population on a remote stretch of the California outer coast, where most of their recovery has occurred. However, studies of recently-recolonized estuaries have revealed that estuaries can provide southern sea otters with high quality habitats featuring shallow waters, high production and ample food, limited predators, and protected haul-out opportunities. Moreover, sea otters can have strong effects on estuarine ecosystems, fostering seagrass resilience through their consumption of invertebrate prey. Using a combination of literature reviews, population modeling, and prey surveys we explored the former estuarine habitats outside the current southern sea otter range to determine if these estuarine habitats can support healthy sea otter populations. We found the majority of studies and conservation efforts have focused on populations in exposed, rocky coastal habitats. Yet historical evidence indicates that sea otters were also formerly ubiquitous in estuaries. Our habitat-specific population growth model for California’s largest estuary—San Francisco Bay—determined that it alone can support about 6,600 sea otters, more than double the 2018 California population. Prey surveys in estuaries currently with (Elkhorn Slough and Morro Bay) and without (San Francisco Bay and Drakes Estero) sea otters indicated that the availability of prey, especially crabs, is sufficient to support healthy sea otter populations. Combining historical evidence with our results, we show that conservation practitioners could consider former estuarine habitats as targets for sea otter and ecosystem restoration. This study reveals the importance of understanding how recovering species interact with all the ecosystems they historically occupied, both for improved conservation of the recovering species and for successful restoration of ecosystem functions and processes.</span></p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.8100","usgsCitation":"Hughes, B.B., Wasson, K., Tinker, M., Williams, S.L., Carswell, L., Boyer, K.E., Beck, M.W., Eby, R., Scoles, R., Staedler, M.M., Espinosa, S., Hessing-Lewis, M., Foster, E.U., Beheshti, K., Grimes, T.M., Becker, B.H., Needles, L., Tomoleoni, J.A., Rudebusch, J., Hines, E.M., and Silliman, B.R., 2019, Species recovery and recolonization of past habitats: Lessons for science and conservation from sea otters in estuaries: PeerJ, v. 7, e8100, 30 p., https://doi.org/10.7717/peerj.8100.","productDescription":"e8100, 30 p.","ipdsId":"IP-098446","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.8100","text":"Publisher Index Page"},{"id":371544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Elkhorn Slough, Morro Bay, San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.62390136718749,\n              37.38325280195101\n            ],\n            [\n              -121.8878173828125,\n              37.38325280195101\n            ],\n            [\n              -121.8878173828125,\n              38.229550455326134\n            ],\n            [\n              -122.62390136718749,\n              38.229550455326134\n            ],\n            [\n              -122.62390136718749,\n              37.38325280195101\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.8170928955078,\n              36.79993834872292\n            ],\n            [\n              -121.73057556152344,\n              36.79993834872292\n            ],\n            [\n              -121.73057556152344,\n              36.87110680999585\n            ],\n            [\n              -121.8170928955078,\n              36.87110680999585\n            ],\n            [\n              -121.8170928955078,\n              36.79993834872292\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.97869873046875,\n              35.25907654252574\n            ],\n            [\n              -120.76171875,\n              35.25907654252574\n            ],\n            [\n              -120.76171875,\n              35.458432791026304\n            ],\n            [\n              -120.97869873046875,\n              35.458432791026304\n            ],\n            [\n              -120.97869873046875,\n              35.25907654252574\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hughes, Brent B.","contributorId":201240,"corporation":false,"usgs":false,"family":"Hughes","given":"Brent","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":780221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wasson, Kerstin","contributorId":221786,"corporation":false,"usgs":false,"family":"Wasson","given":"Kerstin","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":780222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":221787,"corporation":false,"usgs":false,"family":"Tinker","given":"M. Tim","affiliations":[{"id":40428,"text":"University of California, Santa Cruz; former USGS PI","active":true,"usgs":false}],"preferred":false,"id":780223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Susan L","contributorId":221788,"corporation":false,"usgs":false,"family":"Williams","given":"Susan","email":"","middleInitial":"L","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":780224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carswell, Lilian P.","contributorId":221789,"corporation":false,"usgs":false,"family":"Carswell","given":"Lilian P.","affiliations":[{"id":40429,"text":"USFWS - Ventura FWO","active":true,"usgs":false}],"preferred":false,"id":780225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyer, Katharyn E.","contributorId":177069,"corporation":false,"usgs":false,"family":"Boyer","given":"Katharyn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":780226,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beck, Michael W.","contributorId":214199,"corporation":false,"usgs":false,"family":"Beck","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":780227,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eby, Ron","contributorId":221790,"corporation":false,"usgs":false,"family":"Eby","given":"Ron","email":"","affiliations":[{"id":40430,"text":"Elkhorn Slough National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":780228,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scoles, Robert","contributorId":221791,"corporation":false,"usgs":false,"family":"Scoles","given":"Robert","email":"","affiliations":[{"id":40430,"text":"Elkhorn Slough National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":780229,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":213742,"corporation":false,"usgs":false,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":false,"id":780230,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Espinosa, Sarah","contributorId":221792,"corporation":false,"usgs":false,"family":"Espinosa","given":"Sarah","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":780231,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hessing-Lewis, Margot","contributorId":201238,"corporation":false,"usgs":false,"family":"Hessing-Lewis","given":"Margot","email":"","affiliations":[],"preferred":false,"id":780232,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Foster, Erin U.","contributorId":221803,"corporation":false,"usgs":false,"family":"Foster","given":"Erin","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":780233,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Beheshti, Kathryn","contributorId":221793,"corporation":false,"usgs":false,"family":"Beheshti","given":"Kathryn","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":780234,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Grimes, Tracy M","contributorId":221794,"corporation":false,"usgs":false,"family":"Grimes","given":"Tracy","email":"","middleInitial":"M","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":780235,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Becker, Benjamin H.","contributorId":207275,"corporation":false,"usgs":false,"family":"Becker","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[{"id":37509,"text":"Point Reyes National Seashore, Point Reyes Station, CA","active":true,"usgs":false}],"preferred":true,"id":780236,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Needles, Lisa","contributorId":221795,"corporation":false,"usgs":false,"family":"Needles","given":"Lisa","affiliations":[{"id":40431,"text":"California Polytechnic State University - San Luis Obispo","active":true,"usgs":false}],"preferred":false,"id":780237,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780220,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Rudebusch, Jane","contributorId":221796,"corporation":false,"usgs":false,"family":"Rudebusch","given":"Jane","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":780238,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Hines, Ellen Marie","contributorId":147831,"corporation":false,"usgs":false,"family":"Hines","given":"Ellen","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":780239,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Silliman, Brian R","contributorId":221797,"corporation":false,"usgs":false,"family":"Silliman","given":"Brian","email":"","middleInitial":"R","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":780240,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70206085,"text":"sir20195119 - 2019 - Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","interactions":[],"lastModifiedDate":"2022-04-25T18:47:12.543093","indexId":"sir20195119","displayToPublicDate":"2019-12-10T16:08:12","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5119","displayTitle":"Trends in Streamflow and Concentrations and Flux of Nutrients and Total Suspended Solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","title":"Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","docAbstract":"<p>The U.S.&nbsp;Geological Survey (USGS), in cooperation with The Nature Conservancy, completed a study to estimate and assess trends in streamflow and annual mean concentrations and flux of nutrients (nitrate plus nitrite, total Kjeldahl nitrogen, and total phosphorus) and total suspended solids at three USGS streamgages (hereafter referred to as “study gages”) on the Upper White River at Muncie (USGS&nbsp;station&nbsp;03347000), near Nora (USGS station&nbsp;03351000), and near Centerton (USGS&nbsp;station&nbsp;03354000), Indiana. Water-quality data used in the analyses were collected by several agencies between calendar years 1991 and 2017, and streamflow (discharge) data were collected by the USGS. For most of the water-quality constituents, there were suitable data to facilitate an analysis of the 26-year period extending from calendar years 1991 to 2017 (water years 1992 to 2017); however, shorter analytical periods were necessary for total Kjeldahl nitrogen for the study gages at Muncie and near Centerton and for total suspended solids for the study gage near Centerton.</p><p>Temporal trends in streamflows at the study gages for the period extending from water years 1978 to 2017 were assessed using Exploration and Graphics for RivEr Trends (EGRET) and Mann-Kendall and Pettitt tests. With just one exception, the annual maximum and mean daily streamflows and the annual minimum 7-day mean streamflows at the study gages demonstrated upward trends (increasing streamflows) in the EGRET analyses. The exception was the annual 7-day minimum streamflow at the study gage near Nora, which indicated no trend. Mann-Kendall tests also indicated that the average trend for the annual maximum daily, annual mean daily, and annual 7-day minimum streamflow statistics between water years 1978 and 2017 was upward at each of the study gages; however, only the trends in the annual mean daily streamflows at the study gage at Muncie and the annual maximum daily streamflows at the study gages near Nora and near Centerton were statistically significant at a 0.05&nbsp;probability level. The Pettitt tests indicated that a statistically significant step trend (abrupt change) in annual mean daily streamflows occurred at each of the study gages around water year 2001.</p><p>The seasonal distributions of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentrations at the study gages were evaluated to identify patterns and other distinguishing characteristics by examining boxplots of concentrations as a function of month of the year. Seasonal distributions of nitrate plus nitrite concentrations and total suspended solids concentrations differed from each other but were generally similar among the three study gages for a given constituent. Median concentrations of nitrate plus nitrite were highest during the January–June months, whereas median concentrations of total suspended solids were highest during June and July. Seasonal distributions of total phosphorus concentrations were similar at the study gages near Nora and near Centerton, but the seasonal distribution was noticeably different at the study gage at Muncie, which had monthly median concentrations that were substantially lower than at the two downstream study gages (near Nora and near Centerton). The seasonal distribution of total Kjeldahl nitrogen concentrations differed in pattern among the three study gages; however, in general, some of the higher monthly median total Kjeldahl nitrogen concentrations at each study gage were associated with the late spring and summer periods.</p><p>The Weighted Regressions on Time, Discharge, and Season (WRTDS) method implemented in EGRET was used to estimate water-year annual mean daily concentrations and flux of nutrients and total suspended solids, as well as estimates of concentrations and flux that were “normalized” to remove the effect of year-to-year variation in streamflow. The approximate coefficients of determination for the WRTDS regression models ranged from a high of 0.82 for total phosphorus for the study gage near Centerton to a low of 0.19 for nitrate plus nitrite for the study gage near Nora.</p><p>Loads and yields of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated for analytical periods consisting of the longest periods of concurrent record at the three study gages. Loads of each of the constituents increased sequentially from the most upstream study gage to the most downstream study gage; however, the same was not true for yields. The highest yields of total suspended solids, total phosphorus, and total Kjeldahl nitrogen occurred at the most upstream study gage (at Muncie); however, the highest yield of nitrate plus nitrite occurred at the most downstream study gage (near Centerton).</p><p>WRTDS bootstrap tests were used to assess the magnitude, direction, and likelihood of changes in annual flow-normalized mean daily concentrations and flux of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen at the study gages between water years 1997 and 2017. Changes in flow-normalized concentrations and flux of the constituents between water years 1997 and 2017 were mostly downward (decreasing). The exceptions were likely to highly likely upward (increasing) changes in (1)&nbsp;flow-normalized annual mean daily concentration and annual flux for total suspended solids and total phosphorus at the study gage at Muncie, (2)&nbsp;flow-normalized annual mean daily total phosphorus concentration at the study gage near Centerton, (3)&nbsp;flow-normalized annual flux of total phosphorus at the study gage near Centerton, and (4)&nbsp;flow-normalized annual mean daily nitrate plus nitrite concentration at the study gage near Centerton. Although an upward change in flow-normalized nitrate plus nitrite concentrations was likely at the study gage near Centerton, flow-normalized annual flux of nitrate plus nitrite at that study gage was determined to have a highly likely downward change.</p><p>EGRET and Exploration and Graphics for RivEr Trends Confidence Intervals (EGRETci) analyses can be used to improve our understanding of how concentrations and flux change as functions of time and streamflow, as well as provide information on how the relations between streamflow and constituent concentrations have changed within the calendar year between any 2&nbsp;years included in the analyses. Examples of those uses, illustrating changes between calendar years 1992 and 2017, were given for total suspended solids concentrations at the study gage near Nora and for nitrate plus nitrite concentrations at the study gage near Centerton.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195119","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Koltun, G.F., 2019, Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana: U.S. Geological Survey Scientific Investigations Report 2019–5119, 34 p., https://doi.org/10.3133/sir20195119.","productDescription":"Report: viii, 34 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-109722","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399602,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109513.htm"},{"id":370134,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VN5RKV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentration data for the White River at Muncie, near Nora, and near Centerton, Indiana, 1991–2017"},{"id":370133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5119/sir20195119.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5119"},{"id":370132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5119/coverthb.jpg"}],"country":"United States","state":"Indiana","county":"Morgan County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.8311,\n              39.2633\n            ],\n            [\n              -84.9667,\n              39.2633\n            ],\n            [\n              -84.9667,\n              40.3608\n            ],\n            [\n              -86.8311,\n              40.3608\n            ],\n            [\n              -86.8311,\n              39.2633\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/oki-water\" href=\"https://www.usgs.gov/centers/oki-water\">Ohio-Kentucky-Indiana Water Science Center</a> <br>U.S. Geological Survey <br>6460 Busch Boulevard Ste 100 <br>Columbus, OH 43229–1737</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Trends in Streamflow and Concentrations and Flux of Nutrients and Total Suspended Solids</li><li>Summary</li><li>References</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2019-12-10","noUsgsAuthors":false,"publicationDate":"2019-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773515,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208517,"text":"70208517 - 2019 - Neotectonic and paleoseismic analysis of the northwest extent of Holocene surface deformation along the Meers Fault, Oklahoma","interactions":[],"lastModifiedDate":"2020-02-14T06:29:08","indexId":"70208517","displayToPublicDate":"2019-12-10T07:58:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Neotectonic and paleoseismic analysis of the northwest extent of Holocene surface deformation along the Meers Fault, Oklahoma","docAbstract":"TheMeers fault (Oklahoma) is one of fewseismogenic structures with evidence for Holocene\nsurface rupture in the stable continental region of North America. The 37-kilometer-long\nsoutheast section of the full 54-kilometer-long Meers fault is interpreted to be Holocene\nactive. The 17-kilometer-long northwest section is considered Quaternary active, but not\nHolocene active.We reevaluate surface expression and earthquake timing of the northwest\nMeers fault to improve seismic source characterization.We use airborne light detection and\nranging and historical stereopaired aerial photos to evaluate the fault scarp and local faultzone\ngeomorphology. In the northwest, complex surface deformation includes fault splays,\nsubtle monoclinal warping, and a minor change in fault strike. We interpret that the alongstrike\ntransition from surface faulting on the southeastMeers fault to surface folding on the\nnorthwest Meers fault occurs at the lithologic contact between Permian Post Oak conglomerate\nand Hennessey shale. We excavated a paleoseismic trench to evaluate the timing\nof surface-deforming earthquakes on the northwest section of the fault. The excavation\nrevealed weathered Permian Hennessey shale and an ∼1–2-meter-thick veneer of Holocene\nalluvial deposits that were progressively deformed during two surface-folding earthquakes\nlikely related to blind fault rupture beneath the site. Repeated onlapping to overlapping\nstratigraphic sequences and associated unconformities are intimately related to folding\nevents along the monocline. OxCal paleoearthquake age modeling indicates that earthquakes\noccurred 4704–3109 yr B.P. and 5955–4744 yr B.P., and that part of the northwest\nsection of the Meers fault is Holocene active. We find the Holocene-active section of the\nMeers fault should be lengthened 6.1 km to the northwest, to a total Holocene-active fault\nlength of 43 km. Empirical scaling relationships between surface rupture length and magnitude\nreveal that the fault could generate an Mw 7.0 earthquake.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180148","usgsCitation":"Hornsby, K.T., Streig, A.R., Bennett, S., Chang, J.C., and Mahan, S.A., 2019, Neotectonic and paleoseismic analysis of the northwest extent of Holocene surface deformation along the Meers Fault, Oklahoma: Bulletin of the Seismological Society of America, v. 110, p. 49-66, https://doi.org/10.1785/0120180148.","productDescription":"18 p.","startPage":"49","endPage":"66","ipdsId":"IP-098303","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":372297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma ","county":"Kiowa County, Comanche County","otherGeospatial":"Meers Fault","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.0906,34.8581],[-98.0883,34.8581],[-98.0884,34.8572],[-98.0889,34.8091],[-98.0893,34.6837],[-98.1413,34.6828],[-98.1422,34.596],[-98.1421,34.5079],[-98.2442,34.5081],[-98.244,34.4659],[-98.2959,34.4653],[-98.296,34.4512],[-98.3996,34.4513],[-98.5033,34.4523],[-98.504,34.4219],[-98.6082,34.4204],[-98.6083,34.4091],[-98.6612,34.4083],[-98.6607,34.511],[-98.818,34.51],[-98.8252,34.5095],[-98.8245,34.5954],[-99.0009,34.5943],[-99.0006,34.6383],[-99.1033,34.638],[-99.0976,34.6473],[-99.0993,34.6559],[-99.0987,34.6636],[-99.0937,34.6722],[-99.0859,34.6786],[-99.0719,34.6736],[-99.0663,34.6768],[-99.0479,34.6764],[-99.0406,34.68],[-99.0406,34.6846],[-99.0417,34.6932],[-99.0479,34.6977],[-99.0552,34.7045],[-99.0736,34.7018],[-99.0959,34.6959],[-99.115,34.7018],[-99.1384,34.7013],[-99.1485,34.7031],[-99.1569,34.7081],[-99.158,34.7131],[-99.1541,34.7258],[-99.1625,34.7339],[-99.1643,34.7444],[-99.1682,34.7462],[-99.1732,34.7498],[-99.1727,34.7548],[-99.1603,34.7548],[-99.1576,34.7598],[-99.1621,34.7662],[-99.1643,34.7698],[-99.1666,34.7862],[-99.1655,34.793],[-99.1621,34.7957],[-99.156,34.7925],[-99.1498,34.7925],[-99.1515,34.8039],[-99.1515,34.8184],[-99.1549,34.8266],[-99.1532,34.8339],[-99.1532,34.8361],[-99.1465,34.8457],[-99.146,34.8498],[-99.1482,34.8543],[-99.151,34.8543],[-99.1606,34.8498],[-99.1718,34.8493],[-99.1729,34.8565],[-99.1757,34.8593],[-99.1847,34.8592],[-99.1925,34.857],[-99.1947,34.8488],[-99.2031,34.8388],[-99.2121,34.8401],[-99.2137,34.837],[-99.2132,34.8338],[-99.212,34.8288],[-99.2154,34.826],[-99.2215,34.8288],[-99.226,34.8274],[-99.2288,34.821],[-99.2321,34.8165],[-99.2394,34.816],[-99.2445,34.8187],[-99.2473,34.8224],[-99.2529,34.8328],[-99.2591,34.8378],[-99.2742,34.8396],[-99.2787,34.8414],[-99.2832,34.8495],[-99.2849,34.8509],[-99.2961,34.8508],[-99.3017,34.8526],[-99.3124,34.8662],[-99.3164,34.874],[-99.3181,34.8799],[-99.3147,34.8871],[-99.3091,34.8894],[-99.3013,34.8876],[-99.2985,34.8849],[-99.2951,34.8804],[-99.2912,34.8804],[-99.2889,34.8831],[-99.2952,34.9122],[-99.3003,34.9208],[-99.3121,34.9321],[-99.3206,34.9425],[-99.3324,34.952],[-99.3352,34.9629],[-99.3343,34.9961],[-99.3365,35.0029],[-99.3282,35.0156],[-99.3287,35.0188],[-99.3338,35.0228],[-99.3344,35.0274],[-99.3266,35.0338],[-99.326,35.0401],[-99.3317,35.0428],[-99.3412,35.0405],[-99.3491,35.0437],[-99.3525,35.0527],[-99.3564,35.0541],[-99.3643,35.05],[-99.3727,35.0559],[-99.3733,35.06],[-99.3683,35.0668],[-99.3683,35.0713],[-99.3711,35.0759],[-99.3706,35.0845],[-99.3706,35.0868],[-99.3791,35.0881],[-99.3836,35.0935],[-99.3926,35.0917],[-99.3982,35.0935],[-99.3988,35.1021],[-99.4022,35.1098],[-99.4067,35.1161],[-99.3595,35.1163],[-99.2555,35.1161],[-99.0425,35.1168],[-98.9807,35.1173],[-98.9312,35.1168],[-98.8244,35.1176],[-98.748,35.1166],[-98.7401,35.107],[-98.7379,35.102],[-98.7351,35.1029],[-98.7317,35.1129],[-98.7255,35.1115],[-98.721,35.1138],[-98.7132,35.1065],[-98.7109,35.1065],[-98.7042,35.111],[-98.6985,35.1115],[-98.6856,35.1078],[-98.6822,35.1101],[-98.6778,35.1082],[-98.6738,35.1187],[-98.6665,35.1209],[-98.6575,35.1236],[-98.6513,35.125],[-98.6485,35.1231],[-98.6485,35.1213],[-98.649,35.1195],[-98.6513,35.1177],[-98.6496,35.1141],[-98.6451,35.1113],[-98.6429,35.1145],[-98.6406,35.1231],[-98.6355,35.1231],[-98.6294,35.1167],[-98.6255,35.1035],[-98.621,35.0981],[-98.6177,35.0994],[-98.6206,34.8565],[-98.5091,34.8557],[-98.1937,34.8571],[-98.0906,34.8581]]]},\"properties\":{\"name\":\"Comanche\",\"state\":\"OK\"}}]}","volume":"110","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hornsby, Kristofer T.","contributorId":222477,"corporation":false,"usgs":false,"family":"Hornsby","given":"Kristofer","email":"","middleInitial":"T.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":782250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Streig, Ashley R. 0000-0002-9310-6132","orcid":"https://orcid.org/0000-0002-9310-6132","contributorId":222478,"corporation":false,"usgs":false,"family":"Streig","given":"Ashley","email":"","middleInitial":"R.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":782251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, S. 0000-0002-9772-4122","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":29230,"corporation":false,"usgs":true,"family":"Bennett","given":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":782249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chang, Jefferson C. 0000-0002-1258-589X","orcid":"https://orcid.org/0000-0002-1258-589X","contributorId":222479,"corporation":false,"usgs":false,"family":"Chang","given":"Jefferson","email":"","middleInitial":"C.","affiliations":[{"id":13170,"text":"Oklahoma Geological Survey","active":true,"usgs":false}],"preferred":false,"id":782252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":782253,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208594,"text":"70208594 - 2019 - Alkalinity in tidal tributaries of the Chesapeake Bay","interactions":[],"lastModifiedDate":"2020-02-20T06:42:19","indexId":"70208594","displayToPublicDate":"2019-12-10T06:40:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Alkalinity in tidal tributaries of the Chesapeake Bay","docAbstract":"Despite the important role of alkalinity in estuarine carbon cycling, the seasonal and decadal variability of alkalinity, particularly within multiple tidal tributaries of the same estuary, is poorly understood. Here we analyze more than 26,000 alkalinity measurements, mostly from the 1980s and 1990s, in the major tidal tributaries of the Chesapeake Bay, a large, coastal-plain estuary of eastern North America. The long-term means of alkalinity in tidal-fresh waters vary by a factor of 6 among seven tidal tributaries, reflecting the alkalinity of non-tidal rivers draining to these estuaries. At 25 stations, mostly in the Potomac River Estuary, we find significant long-term increasing trends that exceed the trends in the non-tidal rivers upstream of those stations. Box model calculations in the Potomac River Estuary indicate that the main cause of the estuarine trends is a declining alkalinity sink. The magnitude of this sink is consistent with a simple model of calcification by the invasive bivalve Corbicula fluminea. More generally, in tidal tributaries fed by high-alkalinity non-tidal rivers, alkalinity is consumed, with sinks ranging from 8 to 27% of the upstream input. In contrast, tidal tributaries that are fed by low-alkalinity non-tidal rivers have sources of alkalinity amounting to 34 to 171% of the upstream input. For a single estuarine system, the Chesapeake Bay has diverse alkalinity dynamics and can thus serve as a laboratory for studying the numerous processes influencing alkalinity among the world’s estuaries.","language":"English","publisher":"Wiley","doi":"10.1029/2019JC015597","usgsCitation":"Najjar, R., Herrmann, M., Friedman, J.R., Friedrichs, M.A., Harris, L.A., Shadwick, E.H., Stets, E.G., and Woodland, R.J., 2019, Alkalinity in tidal tributaries of the Chesapeake Bay: Journal of Geophysical Research C: Oceans, v. 125, no. 1, e2019JC015597, 24 p., https://doi.org/10.1029/2019JC015597.","productDescription":"e2019JC015597, 24 p.","ipdsId":"IP-114234","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jc015597","text":"Publisher Index Page"},{"id":372439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.882568359375,\n              39.487084981687495\n            ],\n            [\n              -75.9375,\n              39.52099229357195\n            ],\n            [\n              -75.83862304687499,\n              39.45316112807394\n            ],\n            [\n              -75.970458984375,\n              39.64799732373418\n            ],\n            [\n              -76.48681640625,\n              39.64799732373418\n            ],\n            [\n              -76.827392578125,\n              39.036252959636606\n            ],\n            [\n              -76.81640625,\n              38.13455657705411\n            ],\n            [\n              -76.541748046875,\n              37.09023980307208\n            ],\n            [\n              -76.09130859375,\n              36.70365959719456\n            ],\n            [\n              -75.684814453125,\n              37.10776507118514\n            ],\n            [\n              -75.618896484375,\n              37.93553306183642\n            ],\n            [\n              -76.04736328125,\n              38.522384090200845\n            ],\n            [\n              -75.882568359375,\n              39.487084981687495\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Najjar, Raymond G.","contributorId":198520,"corporation":false,"usgs":false,"family":"Najjar","given":"Raymond G.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":782649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herrmann, Maria","contributorId":198519,"corporation":false,"usgs":false,"family":"Herrmann","given":"Maria","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":782650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jaclyn R. 0000-0001-8120-2541","orcid":"https://orcid.org/0000-0001-8120-2541","contributorId":222587,"corporation":false,"usgs":false,"family":"Friedman","given":"Jaclyn","email":"","middleInitial":"R.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":782651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedrichs, Marjorie A. M. 0000-0003-2828-7595","orcid":"https://orcid.org/0000-0003-2828-7595","contributorId":222588,"corporation":false,"usgs":false,"family":"Friedrichs","given":"Marjorie","email":"","middleInitial":"A. M.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":782652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Lora A.","contributorId":202883,"corporation":false,"usgs":false,"family":"Harris","given":"Lora","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":782653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shadwick, Elizabeth H. 0000-0003-4008-3333","orcid":"https://orcid.org/0000-0003-4008-3333","contributorId":222589,"corporation":false,"usgs":false,"family":"Shadwick","given":"Elizabeth","email":"","middleInitial":"H.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":782654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":782648,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woodland, Ryan J.","contributorId":197043,"corporation":false,"usgs":false,"family":"Woodland","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782655,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70212557,"text":"70212557 - 2019 - Using incidental mark-encounter data to improve survival estimation","interactions":[],"lastModifiedDate":"2020-08-20T13:31:25.026173","indexId":"70212557","displayToPublicDate":"2019-12-08T08:26:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using incidental mark-encounter data to improve survival estimation","docAbstract":"<ol class=\"\"><li>Obtaining robust survival estimates is critical, but sample size limitations often result in imprecise estimates or the failure to obtain estimates for population subgroups. Concurrently, data are often recorded on incidental reencounters of marked individuals, but these incidental data are often unused in survival analyses.</li><li>We evaluated the utility of supplementing a traditional survival dataset with incidental data on marked individuals that were collected ad hoc. We used a continuous time‐to‐event exponential survival model to leverage the matching information contained in both datasets and assessed differences in survival among adult and juvenile and resident and translocated Mojave desert tortoises (<i>Gopherus agassizii</i>).</li><li>Incorporation of the incidental mark‐encounter data improved precision of all annual survival point estimates, with a 3.4%–37.5% reduction in the spread of the 95% Bayesian credible intervals. We were able to estimate annual survival for three subgroup combinations that were previously inestimable. Point estimates between the radiotelemetry and combined datasets were within |0.029| percentage points of each other, suggesting minimal to no bias induced by the incidental data.</li><li>Annual survival rates were high (&gt;0.89) for resident adult and juvenile tortoises in both study sites and for translocated adults in the southern site. Annual survival rates for translocated juveniles at both sites and translocated adults in the northern site were between 0.73 and 0.76. At both sites, translocated adults and juveniles had significantly lower survival than resident adults. High mortality in the northern site was driven primarily by a single pulse in mortalities.</li><li>Using exponential survival models to leverage matching information across traditional survival studies and incidental data on marked individuals may serve as a useful tool to improve the precision and estimability of survival rates. This can improve the efficacy of understanding basic population ecology and population monitoring for imperiled species.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5900","usgsCitation":"Harju, S.M., Cambrin, S., Averill-Murray, R., Nafus, M.G., Field, K.J., and Allison, L.J., 2019, Using incidental mark-encounter data to improve survival estimation: Ecology and Evolution, v. 10, no. 1, p. 360-370, https://doi.org/10.1002/ece3.5900.","productDescription":"11 p.","startPage":"360","endPage":"370","ipdsId":"IP-104143","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459004,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5900","text":"Publisher Index Page"},{"id":377681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Eldorado Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.0380859375,\n              37.85750715625203\n            ],\n            [\n              -116.817626953125,\n              36.70365959719456\n            ],\n            [\n              -114.60937499999999,\n              34.985003130171066\n            ],\n            [\n              -114.59838867187499,\n              35.67514743608467\n            ],\n            [\n              -114.64233398437499,\n              36.075742215627\n            ],\n            [\n              -114.378662109375,\n              36.19109202182454\n            ],\n            [\n              -114.04907226562499,\n              36.09349937380574\n            ],\n            [\n              -114.027099609375,\n              37.82280243352756\n            ],\n            [\n              -114.0380859375,\n              37.85750715625203\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Harju, Seth M. 0000-0003-0444-7881","orcid":"https://orcid.org/0000-0003-0444-7881","contributorId":238889,"corporation":false,"usgs":false,"family":"Harju","given":"Seth","email":"","middleInitial":"M.","affiliations":[{"id":47817,"text":"Heron Ecological","active":true,"usgs":false}],"preferred":false,"id":796856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cambrin, SM","contributorId":238890,"corporation":false,"usgs":false,"family":"Cambrin","given":"SM","email":"","affiliations":[{"id":47819,"text":"Clark County Desert Conservation Program","active":true,"usgs":false}],"preferred":false,"id":796857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Averill-Murray, R.C. 0000-0002-4424-2269","orcid":"https://orcid.org/0000-0002-4424-2269","contributorId":238891,"corporation":false,"usgs":false,"family":"Averill-Murray","given":"R.C.","email":"","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Field, Kimberleigh J 0000-0003-2373-0367","orcid":"https://orcid.org/0000-0003-2373-0367","contributorId":238892,"corporation":false,"usgs":false,"family":"Field","given":"Kimberleigh","email":"","middleInitial":"J","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796860,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allison, Linda J. 0000-0003-1983-901X","orcid":"https://orcid.org/0000-0003-1983-901X","contributorId":229706,"corporation":false,"usgs":false,"family":"Allison","given":"Linda","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796861,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70207497,"text":"70207497 - 2019 - The August 2018 Kaktovik earthquakes: Active tectonics in northeastern Alaska revealed With InSAR and seismology","interactions":[],"lastModifiedDate":"2020-02-06T11:21:44","indexId":"70207497","displayToPublicDate":"2019-12-05T16:30:04","publicationYear":"2019","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":"The August 2018 Kaktovik earthquakes: Active tectonics in northeastern Alaska revealed With InSAR and seismology","docAbstract":"<p>The largest earthquakes recorded in northern Alaska (M<sub>w</sub> 6.4 and M<sub>w</sub> 6.0) occurred ~6 hours apart on August 12, 2018 in the northeastern Brooks Range. The earthquakes were captured by Sentinel-1 InSAR satellites and Earthscope Transportable Array seismic data, giving insight into the little-known active tectonic processes of Arctic Alaska, obscured until recently by sparse data availability. In this study, InSAR modelling, teleseismic back projections, calibrated hypocentral relocations and regional moment tensor solutions resolve two previously unknown, SSW-dipping right-lateral fault segments. These are the first active faults identified as conjugate to the NE-trending sinistral Canning Displacement Zone directly to the west, which is therefore a more complex zone of diffuse faulting than previously thought. The northeastern Brooks Range has been characterized as an area of low to moderate seismic hazard, but these earthquakes illustrate the potential for larger, possibly destructive events in a region earmarked for rapid resource development.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL085651","usgsCitation":"Gaudreau, E., Nissen, E., Bergman, E.A., Benz, H.M., Tan, F., and Karasözen, E., 2019, The August 2018 Kaktovik earthquakes: Active tectonics in northeastern Alaska revealed With InSAR and seismology: Geophysical Research Letters, v. 46, no. 24, p. 14412-14420, https://doi.org/10.1029/2019GL085651.","productDescription":"9 p.","startPage":"14412","endPage":"14420","ipdsId":"IP-113641","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -167.51953124999997,\n              64.92354174306496\n            ],\n            [\n              -140.9765625,\n              64.92354174306496\n            ],\n            [\n              -140.9765625,\n              71.35706654962706\n            ],\n            [\n              -167.51953124999997,\n              71.35706654962706\n            ],\n            [\n              -167.51953124999997,\n              64.92354174306496\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"24","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Gaudreau, E.","contributorId":221460,"corporation":false,"usgs":false,"family":"Gaudreau","given":"E.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nissen, E.K.","contributorId":221461,"corporation":false,"usgs":false,"family":"Nissen","given":"E.K.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergman, Eric A. 0000-0002-7069-8286","orcid":"https://orcid.org/0000-0002-7069-8286","contributorId":84513,"corporation":false,"usgs":false,"family":"Bergman","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":778303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, F.","contributorId":221462,"corporation":false,"usgs":false,"family":"Tan","given":"F.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778305,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karasözen, E.","contributorId":221463,"corporation":false,"usgs":false,"family":"Karasözen","given":"E.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":778306,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205020,"text":"sir20195093 - 2019 - Hydrogeologic framework of the Virginia Eastern Shore","interactions":[],"lastModifiedDate":"2022-04-22T21:38:34.08926","indexId":"sir20195093","displayToPublicDate":"2019-12-05T12:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5093","displayTitle":"Hydrogeologic Framework of the Virginia Eastern Shore","title":"Hydrogeologic framework of the Virginia Eastern Shore","docAbstract":"<p>The Yorktown-Eastover aquifer system of the Virginia Eastern Shore consists of upper, middle, and lower confined aquifers overlain by correspondingly named confining units and underlain by the Saint Marys confining unit. Miocene- to Pliocene-age marine-shelf sediments observed in 205 boreholes include medium- to coarse-grained sand and shells that compose the aquifers and fine-grained sand, silt, and clay that compose the confining units. The upper confining unit also includes fine-grained and organic-rich back-barrier and estuarine sediments of Pleistocene age. An overlying surficial aquifer is composed mostly of Pleistocene-age nearshore sand and gravel with smaller amounts of cobbles and boulders.</p><p>In addition, Pleistocene-age sediments that fill three buried paleochannels are for the first time explicitly delineated here as distinct hydrogeologic units. Two aquifers are composed of medium- to coarse-grained fluvial sand and gravel, and an intervening confining unit is composed of fine-grained estuarine sand, silt, clay, and organic material. Aquifer and confining-unit sediments are also mixed with reworked marine-shelf sediments eroded from the sides of the paleochannels.</p><p>Hydrogeologic units of the Yorktown-Eastover aquifer system generally dip eastward, are as much as several tens of feet thick, and have an undulating configuration possibly resulting from the underlying Chesapeake Bay impact crater. Aquifers and confining units are incised by the three paleochannels along an upward-widening and eastward-lengthening series of structural “windows.” Hydrogeologic units within mainstems and branching tributaries of the paleochannels dip southeastward parallel to slopes of the paleochannels, are as much as several tens of feet thick, and laterally abut the Yorktown-Eastover aquifer system along paleochannel sidewalls. The Yorktown-Eastover aquifer system is thereby hydraulically breached by the paleochannels to alternately create barriers to or conduits for groundwater flow.</p><p>Results of previously documented aquifer tests at 58 wells indicate that transmissivity is generally greatest in young, shallow, and coarse-grained nearshore and fluvial sediments of the surficial aquifer and paleochannels. Transmissivity progressively decreases with depth in older, deeper, and finer grained marine-shelf sediments of the Yorktown-Eastover aquifer system, probably because they have undergone compaction as a result of greater overburden pressure over longer periods of time.</p><p>Compiled chloride concentrations in samples from 330 wells generally increase downward, with most of the samples collected at altitudes above −300 feet and with most concentrations less than 250 milligrams per liter. The saltwater-transition zone has a broad trough-like shape aligned with the peninsula, being relatively shallow along the coastline and deeper along the central “spine.” Because movement of the saltwater is slow, the configuration largely reflects groundwater flow prior to widespread groundwater withdrawals. Fresh groundwater has leaked downward along deep parts of the saltwater-transition zone and leaked upward along shallower parts to discharge at the coast.</p><p>The saltwater-transition zone also exhibits an anomalous ridge across the center of the peninsula. Groundwater levels indicate that the saltwater ridge formed primarily by the Exmore paleochannel acting as a large lateral collector drain. Groundwater levels were lowered, and the position of saltwater-transition zone was elevated, by a flow conduit that intercepted groundwater that otherwise would have flowed toward and discharged along the coastline.</p><p>Nearly all freshwater on the Virginia Eastern Shore is supplied by groundwater withdrawals, which have lowered water levels, altered hydraulic gradients, and created a concern for saltwater intrusion. Previous characterizations of groundwater conditions that are relied on to manage groundwater development have been limited by a lack of hydrogeologic information, particularly data on buried paleochannels that are critical to safeguarding the groundwater supply. Using recently available expanded information, the U.S. Geological Survey undertook a study in cooperation with the Virginia Department of Environmental Quality during 2016–19 to develop an improved description of the groundwater system called a “hydrogeologic framework.”</p><p>The hydrogeologic framework can aid water-supply planning and development by providing information on broad trends in aquifer configurations, hydraulic properties, and proximity to saltwater to avoid chloride contamination. Digital models to evaluate effects of groundwater withdrawals can also be improved with expanded data and capabilities to evaluate paleochannel hydraulic connections and the potential for saltwater movement.</p><p>The hydrogeologic framework is limited by the nonuniform distribution of boreholes and the subjective delineation of aquifers and confining units, including those within paleochannels that are regarded as preliminary. The configuration of the saltwater-transition zone is also regarded as preliminary because of the nonuniform distribution of groundwater samples. Low well-sampling frequency precludes characterizing movement of the saltwater-transition zone. A monitoring strategy of sampling and possibly electromagnetic-induction well logging could be used to detect saltwater movement.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195093","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., and Beach, T.A., 2019, Hydrogeologic framework of the Virginia Eastern Shore: U.S. Geological Survey Scientific Investigations Report 2019–5093, 26 p., 13 pl., https://doi.org/10.3133/sir20195093.","productDescription":"Report: viii, 26 p.; 13 Plates: 11.00 x 17.00 inches or smaller; Data Release","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-108409","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":369803,"rank":16,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093.pdf","text":"Report","size":"3.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5093"},{"id":369731,"rank":15,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate13.pdf","text":"Plate 13","size":"352 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations and Numbers of Sampled Wells and Altitude of the 250-Milligram-Per-Liter Chloride-Concentration Surface on the Virginia Eastern Shore"},{"id":369730,"rank":14,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate12.pdf","text":"Plate 12","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Upper Confining Unit on the Virginia Eastern Shore"},{"id":369725,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate07.pdf","text":"Plate 7","size":"346 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Middle Confining Unit on the Virginia Eastern Shore"},{"id":369724,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate06.pdf","text":"Plate 6","size":"340 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Middle Aquifer on the Virginia Eastern Shore"},{"id":369723,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate05.pdf","text":"Plate 5","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Lower Confining Unit on the Virginia Eastern Shore"},{"id":399542,"rank":17,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109487.htm"},{"id":369721,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate03.pdf","text":"Plate 3","size":"323 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Saint Marys Confining Unit on the Virginia Eastern Shore"},{"id":369720,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate02.pdf","text":"Plate 2","size":"336 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Hydrogeologic Section through the Virginia Eastern Shore"},{"id":369719,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate01.pdf","text":"Plate 1","size":"339 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations and Numbers of Boreholes on the Virginia Eastern Shore"},{"id":369714,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MPE5SD","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Borehole hydrogeologic-unit top-surface altitudes, aquifer hydraulic properties, and groundwater-sample chloride-concentration data from 1906 through 2016 for the Virginia Eastern Shore"},{"id":369728,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate10.pdf","text":"Plate 10","size":"319 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Confining Unit on the Virginia Eastern Shore"},{"id":369727,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate09.pdf","text":"Plate 9","size":"316 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Lower Aquifer on the Virginia Eastern Shore"},{"id":369726,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate08.pdf","text":"Plate 8","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Upper Aquifer on the Virginia Eastern Shore"},{"id":369729,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate11.pdf","text":"Plate 11","size":"321 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Paleochannel Upper Aquifer on the Virginia Eastern Shore"},{"id":369722,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093_plate04.pdf","text":"Plate 4","size":"327 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Top-Surface Altitude of the Lower Aquifer on the Virginia Eastern Shore"},{"id":369709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5093/coverthb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.058349609375,\n              37.1165261849112\n            ],\n            [\n              -75.003662109375,\n              37.1165261849112\n            ],\n            [\n              -75.003662109375,\n              38\n            ],\n            [\n              -76.058349609375,\n              38\n            ],\n            [\n              -76.058349609375,\n              37.1165261849112\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_wv@usgs.gov, dc_va@usgs.gov\" data-mce-href=\"mailto: dc_wv@usgs.gov, dc_va@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia/West Virginia Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Framework</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Hydrogeologic-unit top-surface altitudes in 205 boreholes, Virginia Eastern Shore</li><li>Appendix 2. Aquifer hydraulic properties, Virginia Eastern Shore</li><li>Appendix 3. Chloride concentrations in 2,440 groundwater samples, Virginia Eastern Shore</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2019-12-05","noUsgsAuthors":false,"publicationDate":"2019-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"McFarland, E. Randolph 0000-0002-4135-6842 ermcfarl@usgs.gov","orcid":"https://orcid.org/0000-0002-4135-6842","contributorId":195668,"corporation":false,"usgs":true,"family":"McFarland","given":"E.","email":"ermcfarl@usgs.gov","middleInitial":"Randolph","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beach, Todd A.","contributorId":218569,"corporation":false,"usgs":false,"family":"Beach","given":"Todd","email":"","middleInitial":"A.","affiliations":[{"id":39875,"text":"Virginia Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":769586,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227253,"text":"70227253 - 2019 - Identifying and characterizing extrapolation in multivariate response data","interactions":[],"lastModifiedDate":"2022-01-05T14:32:01.511268","indexId":"70227253","displayToPublicDate":"2019-12-05T08:19:48","publicationYear":"2019","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":"Identifying and characterizing extrapolation in multivariate response data","docAbstract":"<p><span>Faced with limitations in data availability, funding, and time constraints, ecologists are often tasked with making predictions beyond the range of their data. In ecological studies, it is not always obvious when and where extrapolation occurs because of the multivariate nature of the data. Previous work on identifying extrapolation has focused on univariate response data, but these methods are not directly applicable to multivariate response data, which are common in ecological investigations. In this paper, we extend previous work that identified extrapolation by applying the predictive variance from the univariate setting to the multivariate case. We propose using the trace or determinant of the predictive variance matrix to obtain a scalar value measure that, when paired with a selected cutoff value, allows for delineation between prediction and extrapolation. We illustrate our approach through an analysis of jointly modeled lake nutrients and indicators of algal biomass and water clarity in over 7000 inland lakes from across the Northeast and Mid-west US. In addition, we outline novel exploratory approaches for identifying regions of covariate space where extrapolation is more likely to occur using classification and regression trees. The use of our Multivariate Predictive Variance (MVPV) measures and multiple cutoff values when exploring the validity of predictions made from multivariate statistical models can help guide ecological inferences.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0225715","usgsCitation":"Bartley, M., Hanks, E.M., Schliep, E.M., Soranno, P.A., and Wagner, T., 2019, Identifying and characterizing extrapolation in multivariate response data: PLoS ONE, v. 14, no. 12, e0225715, 20 p., https://doi.org/10.1371/journal.pone.0225715.","productDescription":"e0225715, 20 p.","ipdsId":"IP-107783","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0225715","text":"Publisher Index Page"},{"id":393911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartley, Meridith L.","contributorId":270913,"corporation":false,"usgs":false,"family":"Bartley","given":"Meridith L.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":830122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim M.","contributorId":178093,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schliep, Erin M.","contributorId":171525,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":830121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207037,"text":"70207037 - 2019 - Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff","interactions":[],"lastModifiedDate":"2019-12-04T15:38:49","indexId":"70207037","displayToPublicDate":"2019-12-04T15:37:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5896,"text":"Journal of Sustainable Water in the Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff","docAbstract":"Catch basins commonly are used by cities as part of a stormwater management plan to remove sediment and associated contaminants from stormwater, keeping them in compliance with regulations. Recently, the city of Madison, Wisconsin modified traditional catch basins by incorporating a fine-mesh (1-mm) Coanda-effect screen into the design with the goal of increasing removal of sediment and organic matter from stormwater. The US Geological Survey (USGS), in cooperation with the City of Madison, installed a water-quality monitoring station at such a catch basin to quantify reductions in total suspended solids (TSS), volatile suspended solids (VSS), suspended sediment concentration (SSC), total phosphorus (TP), and dissolved phosphorus (DP) from urban stormwater before entering Lake Monona. A comparison of the cumulative load from 33 samples collected during the summers of 2016 and 2017 showed 23% and 45% reductions in TSS and SSC, respectively. A smaller reduction was observed for TP, 16%, whereas DP remained unchanged. Reported traditional catch basin sediment removal varies greatly, although typical removal rates are similar. Results from this study will help regulated municipalities determine whether the use of screened catch basins can help meet water-quality goals.","language":"English","publisher":"ASCE","doi":"10.1061/JSWBAY.0000892","usgsCitation":"Buer, N., and Selbig, W.R., 2019, Evaluation of stormwater treatment vault with Coanda-effect screen for removal of solids and phosphorus in urban runoff: Journal of Sustainable Water in the Built Environment, v. 6, no. 1, 04019013, 10 p., https://doi.org/10.1061/JSWBAY.0000892.","productDescription":"04019013, 10 p.","ipdsId":"IP-096348","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":459017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jswbay.0000892","text":"Publisher Index Page"},{"id":369921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane County","city":"Madison","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.0094,43.286],[-89.0084,43.2555],[-89.0094,43.2],[-89.01,43.1131],[-89.0109,43.0849],[-89.0107,43.0271],[-89.0132,42.9353],[-89.013,42.8762],[-89.0119,42.8471],[-89.132,42.8479],[-89.2488,42.8478],[-89.3689,42.8484],[-89.3688,42.8575],[-89.4832,42.858],[-89.6026,42.8575],[-89.7196,42.8587],[-89.8377,42.8598],[-89.8375,42.9471],[-89.8386,43.0317],[-89.8384,43.1181],[-89.8394,43.205],[-89.8325,43.2123],[-89.825,43.2187],[-89.8175,43.226],[-89.8125,43.2342],[-89.8088,43.2369],[-89.8012,43.2365],[-89.7874,43.2356],[-89.771,43.237],[-89.7579,43.2379],[-89.7529,43.2443],[-89.7485,43.2507],[-89.7391,43.2548],[-89.7259,43.2644],[-89.7171,43.2739],[-89.714,43.2821],[-89.7165,43.2867],[-89.7235,43.2935],[-89.7209,43.2935],[-89.6008,43.2932],[-89.4819,43.2942],[-89.3617,43.2954],[-89.3624,43.2832],[-89.246,43.2834],[-89.1271,43.2827],[-89.0094,43.286]]]},\"properties\":{\"name\":\"Dane\",\"state\":\"WI\"}}]}","volume":"6","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buer, Nicolas 0000-0002-4369-8715","orcid":"https://orcid.org/0000-0002-4369-8715","contributorId":204808,"corporation":false,"usgs":true,"family":"Buer","given":"Nicolas","email":"","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776593,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215094,"text":"70215094 - 2019 - Improving predictions of fine particle immobilization in streams","interactions":[],"lastModifiedDate":"2020-10-07T20:12:43.002013","indexId":"70215094","displayToPublicDate":"2019-12-04T15:06:29","publicationYear":"2019","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":"Improving predictions of fine particle immobilization in streams","docAbstract":"Fine particles are critical to stream ecosystem functioning, influencing in-stream processes from pathogen transmission to carbon cycling, all of which depend on particle immobilization.  However, our ability to predict particle immobilization is limited by: (1) availability of combined solute and particle tracer data and (2) identifying parameters that appropriately represent fine particle immobilization, due to the myriad of objective functions and model formulations.  We found that improved predictions of the full distribution of possible fine particle residence times requires using an objective function that assesses both the peak and tailing together with solute tracers to constrain in-stream transport processes. The representation of immobilization processes was significantly improved when solute tracer data were combined with a particle model, starkly contrasting the common assumption that fine particles transport as washload.  We develop a clear strategy for improving fine particle transport predictions, reshaping the potential role of fine particles in water quality management.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL085849","usgsCitation":"Drummond, J.D., Schmadel, N., Kelleher, C., Packman, A.I., and Ward, A.S., 2019, Improving predictions of fine particle immobilization in streams: Geophysical Research Letters, v. 46, no. 23, p. 13,853-13,861, https://doi.org/10.1029/2019GL085849.","productDescription":"9 p.","startPage":"13,853","endPage":"13,861","ipdsId":"IP-114105","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gl085849","text":"Publisher Index Page"},{"id":379197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"23","noUsgsAuthors":false,"publicationDate":"2019-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Drummond, Jennifer D.","contributorId":191390,"corporation":false,"usgs":false,"family":"Drummond","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":800820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmadel, Noah M. 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":800821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelleher, Christa","contributorId":242798,"corporation":false,"usgs":false,"family":"Kelleher","given":"Christa","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":800822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Packman, Aaron I.","contributorId":124517,"corporation":false,"usgs":false,"family":"Packman","given":"Aaron","email":"","middleInitial":"I.","affiliations":[{"id":5041,"text":"Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois, USA","active":true,"usgs":false}],"preferred":false,"id":800823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Adam S","contributorId":191363,"corporation":false,"usgs":false,"family":"Ward","given":"Adam","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":800824,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70212499,"text":"70212499 - 2019 - Offset channels may not accurately record strike-slip fault displacement: Evidence from landscape evolution models","interactions":[],"lastModifiedDate":"2020-12-18T21:19:35.5406","indexId":"70212499","displayToPublicDate":"2019-12-04T09:25:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Offset channels may not accurately record strike-slip fault displacement: Evidence from landscape evolution models","docAbstract":"<p><span>Slip distribution, slip rate, and slip per event for strike‐slip faults are commonly determined by correlating offset stream channels—under the assumption that they record seismic slip—but offset channels are formed by the interplay of tectonic and geomorphic processes. To constrain offset channel development under known tectonic and geomorphic conditions, we use numerical landscape evolution simulations along a theoretical strike‐slip fault with uniform and steady uplift, erosion, and diffusion. We investigate the influence of four tectonic parameters (fault zone width, earthquake recurrence interval, variance of the recurrence interval, and total slip relative to channel spacing) on offset channel development through multiple earthquake cycles. Analysis of &gt;3,000 automatically measured offsets from &gt;135 simulations suggests ~30% variability in individual measurements, but modeled displacement is recovered by averaging multiple measurements. However, the average of multiple offset measurements systematically underestimates modeled slip except when the fault zone is less than ~5 m wide, total slip is less than channel spacing, and offsets are measured shortly after an earthquake. In these simulations, postearthquake landscape evolution widens the geomorphic expression of the fault zone and modifies apparent channel offsets. We distinguish this “geomorphic fault zone” from the tectonic fault zone (zone of coseismic distributed deformation). This study highlights the capability of landscape evolution models to explore a range of conditions not easily defined in natural examples and the importance of averaging multiple measurements. Our results verify that paleoseismic studies must consider how geomorphic change has modified offset markers and use caution interpreting slip histories with multiple earthquakes.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB018596","usgsCitation":"Reitman, N.G., Mueller, K.J., Tucker, G.E., Gold, R.D., Briggs, R.W., and Barnhart, K., 2019, Offset channels may not accurately record strike-slip fault displacement: Evidence from landscape evolution models: Journal of Geophysical Research Solid Earth, v. 124, no. 12, p. 13427-13451, https://doi.org/10.1029/2019JB018596.","productDescription":"25 p.","startPage":"13427","endPage":"13451","ipdsId":"IP-113549","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":377601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Karl J.","contributorId":238813,"corporation":false,"usgs":false,"family":"Mueller","given":"Karl","email":"","middleInitial":"J.","affiliations":[{"id":47791,"text":"Department of Geological Sciences, University of Colorado Boulder, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":796592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Gregory E.","contributorId":177811,"corporation":false,"usgs":false,"family":"Tucker","given":"Gregory","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":796593,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796594,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796595,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnhart, Katherine R.","contributorId":238814,"corporation":false,"usgs":false,"family":"Barnhart","given":"Katherine R.","affiliations":[{"id":47792,"text":"Department of Geological Sciences, University of Colorado Boulder, Boulder, Colorado, USA; Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":796596,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208455,"text":"70208455 - 2019 - Measurement of cyanobacteria bloom magnitude using satellite remote sensing","interactions":[],"lastModifiedDate":"2020-02-11T07:47:17","indexId":"70208455","displayToPublicDate":"2019-12-04T07:43:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Measurement of cyanobacteria bloom magnitude using satellite remote sensing","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio-temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Ocean Land Color Imager (OLCI) on Sentinel-3 data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-54453-y","usgsCitation":"Mishra, S., Stumpf, R.P., Schaeffer, B., Werdell, P.J., Loftin, K., and Meredith, A., 2019, Measurement of cyanobacteria bloom magnitude using satellite remote sensing: Scientific Reports, no. 1, 18310, 17 p., https://doi.org/10.1038/s41598-019-54453-y.","productDescription":"18310, 17 p.","ipdsId":"IP-111006","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":459026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-54453-y","text":"Publisher Index Page"},{"id":372207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, 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","contributorId":214109,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake ","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":781961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werdell, P. Jeremy 0000-0002-3592-0152","orcid":"https://orcid.org/0000-0002-3592-0152","contributorId":222358,"corporation":false,"usgs":false,"family":"Werdell","given":"P.","email":"","middleInitial":"Jeremy","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":781962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":205662,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":781958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meredith, Andrew 0000-0001-9651-7132","orcid":"https://orcid.org/0000-0001-9651-7132","contributorId":222359,"corporation":false,"usgs":false,"family":"Meredith","given":"Andrew","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":781963,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70207032,"text":"70207032 - 2019 - Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2020-07-09T14:33:55.941943","indexId":"70207032","displayToPublicDate":"2019-12-03T18:57:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes","docAbstract":"Sea Lamprey Petromyzon marinus population trends in the Great Lakes are tracked by trapping migratory adults in tributaries and using mark and recapture techniques to estimate abundance.  Understanding what environmental and biological factors influence Sea Lamprey capture in tributaries is crucial to developing efficient trapping methods and reliable abundance estimates.  We analyzed data from trapping sites located on eight Great Lakes tributaries using Cormack-Jolly-Seber models and examined how water temperature, discharge, sex, and length influenced Sea Lamprey apparent survival and capture probability.  Sea Lamprey apparent survival was negatively associated with water temperature in all tributaries.  Additionally, the odds of small Sea Lamprey (≤45 cm) remaining available to capture were 39% less (95% CI: 63% decrease – 1% increase) than large (>45 cm) lamprey odds.  These observed relationships were used to investigate if bias in abundance estimates using the pooled-Petersen estimator and Jolly-Seber models was expected to be similar across trapping locations or influenced by variable environmental conditions and biological traits.  Pooled-Petersen abundance estimates had a positive bias when datasets were generated from simulated populations with empirical relationships between environmental characteristics and catchability.  The degree of bias depended upon changes in stream warming patterns and was not consistent among trapping locations.  Jolly-Seber models using data from either weekly-batch-marked or uniquely-marked individuals generated abundance estimate with low bias when data quality was high, but performed poorly in scenarios with few recaptured Sea Lamprey.  This research can promote improved Sea Lamprey monitoring efforts by providing insight into the reliability of the pooled-Petersen abundance estimator as a tool for tracking Sea Lamprey populations and demonstrating the limitations of adopting more robust methods when data are sparse.","language":"English","publisher":"U.S. Fish and Wildlife Scientific Journals","doi":"10.3996/022019-JFWM-013","usgsCitation":"Lewandoski, S.A., Bravener, G.A., Hrodey, P.J., and Miehls, S.M., 2019, Environmental and biological factors influence migratory Sea Lamprey catchability: Implications for tracking abundance in the Laurentian Great Lakes: Journal of Fish and Wildlife Management, v. 11, no. 1, p. 68-79, https://doi.org/10.3996/022019-JFWM-013.","productDescription":"12 p.","startPage":"68","endPage":"79","ipdsId":"IP-112927","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":459029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70227628,"text":"70227628 - 2019 - Detection probability and occupancy of American woodcock during Singing-ground surveys","interactions":[],"lastModifiedDate":"2022-01-21T15:17:00.679985","indexId":"70227628","displayToPublicDate":"2019-12-03T09:08:52","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detection probability and occupancy of American woodcock during Singing-ground surveys","docAbstract":"<p><span>The Singing-ground Survey (SGS) was designed to exploit the conspicuous breeding-season display of male American woodcock (</span><i>Scolopax minor</i><span>; hereafter, woodcock) to monitor these otherwise inconspicuous birds. The SGS was standardized in 1968 and has since been conducted annually to derive an index of abundance and population trend. Counts of singing male woodcock on the SGS have generally declined through time, but without knowledge of the relationship among counts, woodcock abundance, and the factors affecting detection, considerable uncertainty remains in interpretation of SGS data. Using modified SGS protocols, we surveyed SGS routes in Pine County, Minnesota, in 2009 and 2010 and developed models to assess factors associated with detection probability and estimated occupancy. The intercept-only model (i.e., constant detection and occupancy probabilities across sites and no covariates) included overall detection probability of 0.59 (SE = 0.018) in 2009 and 0.66 (SE = 0.017) in 2010 with an occupancy estimate of 0.74 (SE = 0.049) in 2009 and 0.81 (SE = 0.044) in 2010. The best-supported model of detection probability for both years combined included detection as a function of woodcock abundance, observer, date, disturbance level (i.e., ambient noise that interfered with detecting woodcock), and wind speed. High wind speeds were negatively related to detection, different observers had different detection probabilities, date was quadratically related to detection (indicating a mid-period peak in detection), and high woodcock abundance and low disturbance levels were positively related to detection. We provide suggestions for incorporating these resulting into SGS protocol and analyses.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the eleventh American woodcock symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Eleventh American Woodcock Symposium","conferenceDate":"Oct 24-27, 2017","conferenceLocation":"Roscommon, MI","language":"English","publisher":"University of Minnesota Libraries Publishing","doi":"10.24926/AWS.0126","usgsCitation":"Bergh, S.M., and Andersen, D.E., 2019, Detection probability and occupancy of American woodcock during Singing-ground surveys, <i>in</i> Proceedings of the eleventh American woodcock symposium, Roscommon, MI, Oct 24-27, 2017, p. 200-208, https://doi.org/10.24926/AWS.0126.","productDescription":"9 p.","startPage":"200","endPage":"208","ipdsId":"IP-043992","costCenters":[{"id":199,"text":"Coop Res Unit 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,{"id":70206996,"text":"fs20193073 - 2019 - Reach-scale monitoring and modeling of rivers--Expanding hydraulic data collection beyond the cross section","interactions":[],"lastModifiedDate":"2019-12-10T09:20:15","indexId":"fs20193073","displayToPublicDate":"2019-12-02T14:19:38","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3073","displayTitle":"Reach-Scale Monitoring and Modeling of Rivers—Expanding Hydraulic Data Collection Beyond the Cross Section","title":"Reach-scale monitoring and modeling of rivers--Expanding hydraulic data collection beyond the cross section","docAbstract":"For over 125 years, the U.S. Geological Survey streamgage network has provided important\nhydrologic information about rivers and streams throughout the Nation. Traditional streamgage\nmethods provide reliable stage and streamflow data but typically only monitor stage at a single location in a river and require frequent calibration streamflow measurements. Direct measurements are not always feasible, therefore improved sensors and methods\nare being deployed at gages to better document streamflow conditions between measurements. The technology and techniques of reach-scale monitoring allow the U.S. Geological Survey to collect more data across the full range of streamflow without requiring that a hydrographer be present. The U.S. Geological Survey Arizona Water Science Center’s reach-scale monitoring program will enhance the Arizona streamgage network with more accurate streamflow measurements and provide more extensive streamflow records and geomorphological\ndatasets for our agency partners and the public. Reach-scale monitoring installations and techniques are applicable to streams of the western United States and likely throughout the Nation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193073","collaboration":"Prepared in cooperation with Arizona Department of Transportation","usgsCitation":"Forbes, B.T., Bunch, C.E., DeBenedetto, G., Shaw, C.J., and Gungle, B., 2019, Reach-scale monitoring and modeling of rivers—Expanding hydraulic data collection beyond the cross section: U.S. Geological Survey Fact Sheet 2019–3073, 6p., https://doi.org/10.3133/fs20193073.","productDescription":"6 p.","ipdsId":"IP-075529","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":369839,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3073/fs20193073.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 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 \"}}]}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>, <a href=\"http://az.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"http://az.water.usgs.gov/\">Arizona Water Science Center</a><br>U.S. Geological Survey<br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Why Look Beyond the Cross Section?</li><li>Traditional Monitoring</li><li>Streamgaging</li><li>Indirect Measurement of Peak Streamflow</li><li>What is Reach-Scale Monitoring?</li><li>Data Packages for Advanced Streamflow Modeling</li><li>Transportation and Reach-Scale Monitoring</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-12-02","noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Forbes, Brandon T. 0000-0003-4051-0593 bforbes@usgs.gov","orcid":"https://orcid.org/0000-0003-4051-0593","contributorId":213549,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon","email":"bforbes@usgs.gov","middleInitial":"T.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunch, Claire E. 0000-0002-1360-8598 cebunch@usgs.gov","orcid":"https://orcid.org/0000-0002-1360-8598","contributorId":150240,"corporation":false,"usgs":true,"family":"Bunch","given":"Claire E.","email":"cebunch@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":776488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBenedetto, Geoffrey 0000-0003-0696-4567 gdebened@usgs.gov","orcid":"https://orcid.org/0000-0003-0696-4567","contributorId":220988,"corporation":false,"usgs":true,"family":"DeBenedetto","given":"Geoffrey","email":"gdebened@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":776490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaw, Corey J. 0000-0002-7794-7513","orcid":"https://orcid.org/0000-0002-7794-7513","contributorId":220989,"corporation":false,"usgs":false,"family":"Shaw","given":"Corey","email":"","middleInitial":"J.","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":776491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gungle, Bruce 0000-0001-6406-1206 bgungle@usgs.gov","orcid":"https://orcid.org/0000-0001-6406-1206","contributorId":107628,"corporation":false,"usgs":true,"family":"Gungle","given":"Bruce","email":"bgungle@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":776489,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207142,"text":"70207142 - 2019 - Estimating the degree to which distance and temperature differences drive changes in fish community composition over time in the upper Mississippi River","interactions":[],"lastModifiedDate":"2020-06-19T16:15:06.610147","indexId":"70207142","displayToPublicDate":"2019-12-02T12:10:54","publicationYear":"2019","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":"Estimating the degree to which distance and temperature differences drive changes in fish community composition over time in the upper Mississippi River","docAbstract":"Similarity in community composition declines as distance between locations increases, a phenomenon that has been observed in a wide variety of freshwater, marine and terrestrial ecosystems.  One driver of the distance-similarity relationship is the presence of environmental gradients that alter the suitability of sites for particular species.  Although some environmental gradients, such as geology, do not change on a year-to-year basis, others, such as temperature, vary annually and over longer time periods.  Here, we used a 21-year dataset of fish communities in the upper Mississippi River to identify the effect of distance on variation in community composition and to assess whether the effect of distance is primarily due to its effect on thermal regime.   Because the Mississippi River is aligned mostly north-to-south, larger distances along the river roughly correspond to larger differences in latitude and therefore temperature.  As expected, there was a moderate distance-similarity relationship, suggesting greater distance leads to less similarity.  The effect of distance appeared to increase slightly over time.  Using a subset of data for which air temperature was available, we found that difference among sites in degree days (a surrogate for thermal regime) was more strongly associated with similarity in community composition than physical distance (river km).  Although physical distance presumably incorporates more environmental gradients than just temperature (and other potential mechanisms), temperature alone appears to be more strongly associated with differences in the Mississippi River fish community.","language":"English","publisher":"Public Library of Science (PLOS)","doi":"10.1371/journal.pone.0225630","usgsCitation":"Larson, J.H., Vallazza, J.M., and Knights, B.C., 2019, Estimating the degree to which distance and temperature differences drive changes in fish community composition over time in the upper Mississippi River: PLoS ONE, v. 14, no. 12, e0225630, 13 p., https://doi.org/10.1371/journal.pone.0225630.","productDescription":"e0225630, 13 p.","ipdsId":"IP-098122","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":459037,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0225630","text":"Publisher Index Page"},{"id":437267,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P956DF36","text":"USGS data release","linkHelpText":"R Code for Comparison of Fish Community Structure among River Reaches of the Upper Mississippi River: Potential Influence of Lock and Dam 19"},{"id":437266,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MNCH0W","text":"USGS data release","linkHelpText":"Influence of a high head dam as a dispersal barrier to fish community structure of the Upper Mississippi River: Data"},{"id":370110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.69091796875,\n              36.63316209558658\n            ],\n            [\n              -87.64892578125,\n              36.63316209558658\n            ],\n            [\n              -87.64892578125,\n              45.84410779560204\n            ],\n            [\n              -95.69091796875,\n              45.84410779560204\n            ],\n            [\n              -95.69091796875,\n              36.63316209558658\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"14","issue":"12","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":776942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":776943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":776944,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70203227,"text":"70203227 - 2019 - Survival rates and stopover persistence of American Woodcock using Cape May, New Jersey during fall migration","interactions":[],"lastModifiedDate":"2020-03-09T06:18:12","indexId":"70203227","displayToPublicDate":"2019-12-02T10:03:58","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Survival rates and stopover persistence of American Woodcock using Cape May, New Jersey during fall migration","docAbstract":"<p>Cape May, New Jersey is an important stopover area for American woodcock (<i>Scolopax minor</i>, hereafter woodcock) during fall migration along the Atlantic Coast of the United States. Previous research has indicated that many woodcock stop at Cape May prior to crossing Delaware Bay; however, little is known about survival of woodcock while using Cape May. To better understand woodcock survival on Cape May during fall migration and estimate emigration rates for woodcock migrating through Cape May, we captured and marked a total of 271 woodcock with VHF transmitters and radio-tracked them weekly from November through early January, 2010-2013. Of the 271 marked woodcock, our radio-tracking efforts indicated that 131 migrated from Cape May, 57 remained on Cape May, 72 died, and 11 were censored. We used a multi-state model within Program MARK to estimate weekly survival and emigration probabilities for marked woodcock. Our best-supported model indicated that survival rate varied by year, but was constant by week within years. Weekly survival rate estimates ranged from 0.894 (95% CI = 0.834 – 0.934) in 2010 to 0.962 (95% CI = 0.928 – 0.981) in 2011, which equates to a 9-week period survival rate ranging from 0.365 (95% CI = 0.185 – 0.545) to 0.706 (95% CI = 0.541 – 0.870), respectively. The 2010-2011 field season was marked by several large snowstorms during which a large percentage of marked woodcock died, whereas the other 3 years had more mild conditions and higher woodcock survival rates. Our best-supported model indicated that weekly emigration rates varied by year and week with each year showing a different pattern of emigration from Cape May. Survival and emigration information will be useful in the development of future demographic-based population models for woodcock migrating along the Atlantic Coast.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the eleventh American Woodcock symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Eleventh American Woodcock Symposium","conferenceDate":"October 24-27, 2017","conferenceLocation":"Roscommon, MI","language":"English","publisher":"University of Minnesota Libraries Publishing","doi":"10.24926/AWS.0121","collaboration":"U.S. Fish and Wildlife Service","usgsCitation":"McAuley, D., Zimmerman, G.S., Allen, B.L., Dwyer, C., and Cooper, T., 2019, Survival rates and stopover persistence of American Woodcock using Cape May, New Jersey during fall migration, <i>in</i> Proceedings of the eleventh American Woodcock symposium, v. 11, Roscommon, MI, October 24-27, 2017, p. 146-153, https://doi.org/10.24926/AWS.0121.","productDescription":"8 p.","startPage":"146","endPage":"153","ipdsId":"IP-091382","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24926/aws.0121","text":"Publisher Index Page"},{"id":372993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"Cape May","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.97241973876953,\n              38.91027022759443\n            ],\n            [\n              -74.86736297607422,\n              38.91027022759443\n            ],\n            [\n              -74.86736297607422,\n              38.974357249228206\n            ],\n            [\n              -74.97241973876953,\n              38.974357249228206\n            ],\n            [\n              -74.97241973876953,\n              38.91027022759443\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McAuley, Daniel 0000-0003-3674-6392 dmcauley@usgs.gov","orcid":"https://orcid.org/0000-0003-3674-6392","contributorId":215182,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":761786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, B. L.","contributorId":201458,"corporation":false,"usgs":false,"family":"Allen","given":"B.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":761788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dwyer, C.","contributorId":215183,"corporation":false,"usgs":false,"family":"Dwyer","given":"C.","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, T.R.","contributorId":215184,"corporation":false,"usgs":false,"family":"Cooper","given":"T.R.","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761790,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227757,"text":"70227757 - 2019 - Using pointing dogs and hierarchical models to evaluate American woodcock winter occupancy and densities","interactions":[],"lastModifiedDate":"2022-01-28T14:59:18.950521","indexId":"70227757","displayToPublicDate":"2019-12-02T08:35:12","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using pointing dogs and hierarchical models to evaluate American woodcock winter occupancy and densities","docAbstract":"<p>Use of dogs has increased for multiple wildlife research purposes ranging from carnivore scat detection to estimation of reptile abundance. Use of dogs is not particularly novel for upland gamebird biologists, and pointing dogs have been long considered an important research tool. However, recent advances in Global Positioning System (GPS) technology and the development of hierarchical modeling approaches that account for imperfect detection may improve estimates of occupancy and density of cryptic species such as the American woodcock (Scolopax minor; hereafter, woodcock). We conducted surveys for woodcock using a trained pointing dog wearing a GPS collar during the winters of 2010–2011 and 2011–2012 in East Texas, USA. We surveyed 0.5-km-radius circular plots (<i>n</i><span>&nbsp;</span>= 24; survey sites) randomly placed along secondary roads in Davy Crockett National Forest and on private timber property. Surveys lasted 1.5 hrs and were repeated 3–5 times each winter. We estimated woodcock occupancy and density using multiple modeling approaches at the survey site and forest stand scales within survey sites. Woodcock occupied 88% (21/24) of survey sites and 48% (39/82) of forest stands (i.e., unique cover types) within sites. Using a modified distance sampling technique, we estimated an average density of 0.16 birds/ha (SE = 0.13) throughout both study areas. We describe the first attempt to blend use of pointing dogs with hierarchical modeling approaches to derive estimates of regional diurnal woodcock occupancy and density, and describe relationships between these estimates of abundance and habitat covariates. Although forest stand occupancy estimates had the lowest coefficients of variation, our estimates of density provided the most useful inference of habitat use. Surveys using pointing dogs paired with hierarchical models of occupancy and density may provide a cost-efficient and effective approach to estimate habitat abundance at broad spatial scales.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the eleventh American Woodcock Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"American Woodcock Symposium","conferenceDate":"2017","conferenceLocation":"Michigan, United States","language":"English","publisher":"University of Minnesota Press","doi":"10.24926/AWS.0122","usgsCitation":"Sullins, D.S., Conway, W.C., Haukos, D.A., and Comer, C.E., 2019, Using pointing dogs and hierarchical models to evaluate American woodcock winter occupancy and densities, <i>in</i> Proceedings of the eleventh American Woodcock Symposium, Michigan, United States, 2017, p. 154-167, https://doi.org/10.24926/AWS.0122.","productDescription":"14 p.","startPage":"154","endPage":"167","ipdsId":"IP-090750","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24926/aws.0122","text":"Publisher Index Page"},{"id":395048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Houston County, San Augustine County, Trinity County","otherGeospatial":"Davy Crockett National Forest, West Gulf Coastal Plain Bird Conservation Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.24793243408203,\n              31.45473238771609\n            ],\n            [\n              -94.14974212646484,\n              31.45473238771609\n            ],\n            [\n              -94.14974212646484,\n              31.511532395628638\n            ],\n            [\n              -94.24793243408203,\n              31.511532395628638\n            ],\n            [\n              -94.24793243408203,\n              31.45473238771609\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.44509887695312,\n              30.935212690426727\n            ],\n            [\n              -94.75296020507811,\n              30.935212690426727\n            ],\n            [\n              -94.75296020507811,\n              31.67675841879551\n            ],\n            [\n              -95.44509887695312,\n              31.67675841879551\n            ],\n            [\n              -95.44509887695312,\n              30.935212690426727\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":832103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":832104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comer, Christopher E.","contributorId":166690,"corporation":false,"usgs":false,"family":"Comer","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":832105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70203103,"text":"70203103 - 2019 - Aquatic cycling of mercury","interactions":[],"lastModifiedDate":"2019-12-04T17:16:12","indexId":"70203103","displayToPublicDate":"2019-12-01T17:13:56","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Aquatic cycling of mercury","docAbstract":"<p><span>This chapter examines crucial processes in the aquatic cycling of mercury (Hg) that may lead to microbial production of neurotoxic and bioaccumulative methylmercury (MeHg), and highlights environmental conditions in the Everglades that make it ideal for MeHg production and bioaccumulation. The role of complexation of Hg</span><sup>2+</sup><span>&nbsp;in surface water, especially by dissolved organic matter (DOM), in the transport of mercury to sites of microbial methylation are discussed. Photochemical reactions important in Hg cycling in surface water are also discussed. A principal focus of the chapter is on the environmental conditions that promote MeHg production, especially the role of sulfide and DOM in transport of inorganic Hg into bacteria for methylation, and the types of bacteria that have the ability to methylate Hg. Finally, perturbations to the ecosystem (e.g., fire and drought) that have important effects on Hg cycling are discussed.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mercury and the Everglades. A synthesis and model for complex ecosystem restoration","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-32057-7_1","usgsCitation":"Orem, W.H., Krabbenhoft, D.P., Poulin, B., and Aiken, G.A., 2019, Aquatic cycling of mercury, chap. 1 <i>of</i> Mercury and the Everglades. A synthesis and model for complex ecosystem restoration, p. 1-12, https://doi.org/10.1007/978-3-030-32057-7_1.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-106651","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":369934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":761180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":761181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":761183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiken, George A 0000-0001-8454-0984","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":206312,"corporation":false,"usgs":false,"family":"Aiken","given":"George","email":"","middleInitial":"A","affiliations":[{"id":37307,"text":"formerly USGS, deceased","active":true,"usgs":false}],"preferred":false,"id":761182,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208117,"text":"70208117 - 2019 - Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA","interactions":[],"lastModifiedDate":"2020-01-28T15:40:48","indexId":"70208117","displayToPublicDate":"2019-12-01T15:29:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA","docAbstract":"<div class=\"article-section-wrapper \"><p>The iron oxide-apatite (IOA) deposits of the eastern Adirondack Highlands, New York, are historical high-grade magnetite mines that contain variable concentrations of rare earth element (REE)-bearing apatite crystals. The majority of the deposits are hosted within sodically altered Lyon Mountain granite gneiss, although some deposits occur within paragneiss, gabbro, anorthosite, or potassically altered Lyon Mountain granite gneiss. The IOA deposits and the waste and/or tailings piles associated with them have potential as an unconventional resource for REEs. Reprocessing of these piles would have the advantage of partial recycling of the waste material to produce a set of critical elements.</p><p>Thirty-four ore, nine rock, 25 waste-pile, and four tailings-pile samples were collected and analyzed for major, minor, and trace elements. At the tailings- and waste-pile sites, composite samples were collected by combining 30 to &gt;50 subsamples randomly distributed over each pile. The total REE content of the waste and tailings piles varied from approximately 10 to 22,000 ppm, whereas the ore sample concentrations ranged from approximately 15 to 48,000 ppm total REEs. A positive correlation exists between the total REE content of ore and its associated waste pile. Median light REE/heavy REE values were 2.14 for waste/tailings piles and 2.25 for ore, which is a substantial relative enrichment in the heavy REEs in comparison to many developed REE mines, such as the mined carbonatites of Bayan Obo, China, and Mountain Pass, California. Importantly, the ore and waste samples are significantly enriched in both Y and Nd compared to other REEs in the samples. Other minor components such as Th are also elevated. Airborne radiometric surveys show large positive eTh and eU anomalies corresponding to tailings piles.</p><p>Although it is a limited data set, geochemical data of unaltered and altered host rocks suggest a speculative new model for IOA ore formation in the Adirondack Highlands that is consistent with the geology and previously published data. The ferroan ore-hosting Lyon Mountain granite gneiss underwent localized potassic alteration that enriched the altered rock in Fe, REEs, Th, and other metals. A later sodic alteration event affected the previously potassically altered Lyon Mountain granite gneiss, which increased rock porosity and remobilized Fe, REEs, and other elements from the host rock into the iron ore seams. The sodic fluids responsible for ore formation were enriched in F and Cl.</p></div>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4689","usgsCitation":"Taylor, R., Shah, A.K., Walsh, G.J., and Taylor, C.D., 2019, Geochemistry and geophysics of iron oxide-apatite deposits and associated waste piles with implications for potential rare earth element resources from ore and historic mine waste in the eastern Adirondack Highlands, New York, USA: Economic Geology, v. 114, no. 8, p. 1569-1598, https://doi.org/10.5382/econgeo.4689.","productDescription":"30 p.","startPage":"1569","endPage":"1598","ipdsId":"IP-105561","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":371659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Highlands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.35498046875,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              42.827638636242284\n            ],\n            [\n              -73.2568359375,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              45.24395342262324\n            ],\n            [\n              -76.35498046875,\n              42.827638636242284\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"114","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":780545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":780546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Cliff D. 0000-0001-6376-6298 ctaylor@usgs.gov","orcid":"https://orcid.org/0000-0001-6376-6298","contributorId":1283,"corporation":false,"usgs":true,"family":"Taylor","given":"Cliff","email":"ctaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780547,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70203511,"text":"70203511 - 2019 - Sulfur contamination in the Everglades, a major control on mercury methylation","interactions":[],"lastModifiedDate":"2019-12-03T12:03:22","indexId":"70203511","displayToPublicDate":"2019-12-01T11:59:49","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Sulfur contamination in the Everglades, a major control on mercury methylation","docAbstract":"<p id=\"Par1\" class=\"Para\">In this chapter sulfur contamination of the Everglades and its role as a major control on methylmercury (MeHg) production is examined. Sulfate concentrations over large portions of the Everglades (60% of the ecosystem) are elevated or greatly elevated compared to background conditions of &lt;1&nbsp;mg/L. Land and water management practices in south Florida are the primary reason for the high levels of sulfate loading to the Everglades. Marshes in the northern Everglades that are highly enriched in sulfate have average concentrations of 60&nbsp;mg/L, but water in canals in the Everglades Agricultural Area (EAA) contain the highest concentrations of sulfate averaging 60–70&nbsp;mg/L. Studies that examined the mass balance of sulfur to the Everglades have determined that the primary sources of sulfate include: sulfur currently used in agriculture, and natural and legacy agricultural sulfur released by oxidation of organic soil within the EAA. The extensive loading of sulfate to the ecosystem increases microbial sulfate reduction, the dominant microbial process driving mercury methylation and MeHg production. The biogeochemical processes linking sulfate loading and MeHg production, however, are complex. MeHg production increases as sulfate levels rise from levels &lt;1&nbsp;mg/L up to about 20&nbsp;mg/L. However, production of sulfide (a byproduct of microbial sulfate reduction) starts to inhibit MeHg production above 20&nbsp;mg/L. Sulfate loading to canals in the EAA has impacted the northern Everglades the most, but the Everglades canal system can transport sulfate as far as Everglades National Park (ENP), 80&nbsp;km further south. Plans to deliver more water to ENP as part of restoration may increase overall sulfate loads to the southern Everglades.</p><p id=\"Par2\" class=\"Para\">Reduction of sulfate loading should be a major goal of Everglades restoration because of the many negative effects of sulfate on the ecosystem. The ecosystem has been shown to respond quickly to reductions in sulfate loading, and strategies for reducing sulfate loading may produce positive outcomes for the Everglades in the near-term. Strategies for reducing sulfate loading will need to include: best management practices for agricultural use of sulfate, approaches to minimize soil oxidation in the EAA, and modifications to stormwater treatment areas to improve sulfate retention.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mercury and the Everglades. A Synthesis and Model for Complex Ecosystem Restoration","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-32057-7_2","usgsCitation":"Orem, W.H., Krabbenhoft, D.P., Poulin, B., and George Aiken, 2019, Sulfur contamination in the Everglades, a major control on mercury methylation, chap. 2 <i>of</i> Mercury and the Everglades. A Synthesis and Model for Complex Ecosystem Restoration, p. 13-48, https://doi.org/10.1007/978-3-030-32057-7_2.","productDescription":"36 p.","startPage":"13","endPage":"48","ipdsId":"IP-106372","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":369873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.3153076171875,\n              25.075648445630527\n            ],\n            [\n              -80.33752441406249,\n              25.075648445630527\n            ],\n            [\n              -80.33752441406249,\n              25.854280326572407\n            ],\n            [\n              -81.3153076171875,\n              25.854280326572407\n            ],\n            [\n              -81.3153076171875,\n              25.075648445630527\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":762943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George Aiken","contributorId":215670,"corporation":false,"usgs":false,"family":"George Aiken","affiliations":[{"id":39302,"text":"USGS WMA Boulder (Deceased)","active":true,"usgs":false}],"preferred":false,"id":762944,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70275321,"text":"70275321 - 2019 - Review of Sky dance of the woodcock: The habits and habitats of a strange little bird by Greg Hoch","interactions":[],"lastModifiedDate":"2026-04-29T15:15:24.359225","indexId":"70275321","displayToPublicDate":"2019-12-01T10:11:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3111,"text":"Prairie Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Review of Sky dance of the woodcock: The habits and habitats of a strange little bird by Greg Hoch","docAbstract":"<p>American Woodcock (<i>Scolopax minor</i>) have enthralled conservationists (including Aldo Leopold), bird watchers, wildlife enthusiasts, hunters, and others interested in the natural world for centuries. No doubt, woodcock also have enthralled humans in North America for millennia prior to written descriptions of the woodcock’s courtship displays, habitat preferences, and curious behavior and anatomy. As perhaps the most extensively studied species of shorebird in the world, there is a rich and extensive literature, both scientific and popular, focused on woodcock ecology, behavior, and hunting. To that extensive body of literature,<span>&nbsp;</span><i>Sky Dance of the Woodcock</i><span>&nbsp;</span>provides an updated summary of their natural history, habitat relations, and conservation.<i></i></p><p><i>Sky Dance of the Woodcock</i><span>&nbsp;</span>takes its title from the courtship display of male woodcock, which consists of an elaborate aerial flight incorporating sound produced both vocally and mechanically via highly modified flight feathers. The aerial displays are accompanied by similarly unusual behavior on the ground, including a distinctive ‘peent’ call. This courtship display happens across much of eastern North America each spring, and Hoch uses this wonder to capture the imagination of the readers of his text. Hoch begins the book with an overview of some of the mystery and fascination surrounding woodcock and builds from that opening to describe woodcock anatomy, natural history, and behavior, before describing their courtship display in greater detail. From there, Hoch describes woodcock-habitat relations, provides a historical overview of woodcock hunting, identifies current threats to woodcock populations, summarizes past and recent woodcock research, and finally, presents an updated overview of woodcock conservation and habitat management. Throughout, there is sometimes surprising information about things as simple as what woodcock eat, to more complex assessment of how woodcock use landscapes and migrate to and from spring and summer breeding areas.</p><p>This book will undoubtedly appeal to woodcock enthusiasts of a variety to stripes. Woodcock hunters and bird watchers alike will learn something about woodcock-habitat relations, behavior, and conservation. Professional biologists and researchers will benefit from Hoch’s synthesis of a wide range of information about woodcock, and landowners and managers can use some of the concepts in this book to inform their decisions about how to manage lands under their control. Along the way, everyone who reads Sky Dance of the Woodcock is likely to come away with an enhanced appreciation of this captivating bird.</p>","language":"English","publisher":"Great Plains Natural Science Society","usgsCitation":"Andersen, D.E., 2019, Review of Sky dance of the woodcock: The habits and habitats of a strange little bird by Greg Hoch: Prairie Naturalist, v. 51, no. 2, p. 79-80.","productDescription":"2 p.","startPage":"79","endPage":"80","ipdsId":"IP-114425","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":503627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":503626,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.unl.edu/tpn/283/"}],"volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":960565,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70260153,"text":"70260153 - 2019 - Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health","interactions":[],"lastModifiedDate":"2024-10-30T14:39:24.653338","indexId":"70260153","displayToPublicDate":"2019-12-01T09:33:11","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":18999,"text":"GNS Science Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"2019/04","title":"Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health","docAbstract":"<p><span>This report presents data and summarises the findings of a reconnaissance trip investigating the impacts of the April 2015 eruption of Calbuco volcano, Chile, undertaken in November-December 2016. This study is mostly focused on the Los Lagos region, focusing on impacts occurring within ~30 km of the volcano, which includes the tourism town of Puerto Varas and port city of Puerto Montt. Eruption impacts and response strategies may be similar for moderate size eruptions from other stratovolcanoes in temperate regions. As such, this study provides useful information for development of contingency plans at active volcanoes around the world. The 2015 eruption of Calbuco volcano began at 18:04 (local time) on 22 April 2015 and consisted of three eruptive phases. The first lasted for 1.5 hours and generated a 15-km eruption column and plume that was directed towards the northeast. Pyroclastic density currents (PDCs) were generated locally and distributed radially, affecting many of the major rivers. A second phase began at 01:00 (local time) on 23 April 2015, lasted six hours and generated a 17-km high eruption column and plume that was dispersed towards the north-northeast, and the most voluminous pyroclastic density currents of the sequence. A third eruptive phase occurred on 30 April 12:10 (local time) resulting in a 5-km column and plume dispersed towards the east.</span></p>","language":"English","publisher":"The Institute of Geological and Nuclear Sciences Limited (GNS Science)","doi":"10.21420/02YC-VX66","usgsCitation":"Hayes, J., Deligne, N., Bertin, L., Calderon, R., Wardman, J., Wilson, T.J., Leonard, G., C., S., Wallace, K.L., and Baxter, P., 2019, Impacts of the 2015 eruption of Calbuco volcano on Chilean infrastructure, utilities, agriculture, and health: GNS Science Report 2019/04, 102 p., https://doi.org/10.21420/02YC-VX66.","productDescription":"102 p.","ipdsId":"IP-105929","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Calbuco volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.48307304563127,\n              -40.573371240910895\n            ],\n            [\n              -73.48307304563127,\n              -42.33035124814165\n            ],\n            [\n              -71.89602918061058,\n              -42.33035124814165\n            ],\n            [\n              -71.89602918061058,\n              -40.573371240910895\n            ],\n            [\n              -73.48307304563127,\n              -40.573371240910895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hayes, J.","contributorId":345669,"corporation":false,"usgs":false,"family":"Hayes","given":"J.","affiliations":[{"id":82688,"text":"University of Canterbury, NZ","active":true,"usgs":false}],"preferred":false,"id":917219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deligne, N. I.","contributorId":149573,"corporation":false,"usgs":false,"family":"Deligne","given":"N. I.","affiliations":[],"preferred":false,"id":917221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bertin, L","contributorId":345670,"corporation":false,"usgs":false,"family":"Bertin","given":"L","email":"","affiliations":[{"id":82689,"text":"SERNAGEOMIN, Chile","active":true,"usgs":false}],"preferred":false,"id":917223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calderon, Rodrigo","contributorId":270274,"corporation":false,"usgs":false,"family":"Calderon","given":"Rodrigo","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":true,"id":917224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wardman, J.","contributorId":345671,"corporation":false,"usgs":false,"family":"Wardman","given":"J.","affiliations":[{"id":16634,"text":"Bermuda Institute of Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":917225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, T. J.","contributorId":31942,"corporation":false,"usgs":false,"family":"Wilson","given":"T.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":917220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leonard, G.","contributorId":149590,"corporation":false,"usgs":false,"family":"Leonard","given":"G.","email":"","affiliations":[],"preferred":false,"id":917222,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"C., Stewart.","contributorId":345672,"corporation":false,"usgs":false,"family":"C.","given":"Stewart.","email":"","affiliations":[{"id":82690,"text":"GNS Science / Massey University, NZ","active":true,"usgs":false}],"preferred":false,"id":917226,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wallace, Kristi L. 0000-0002-0962-048X kwallace@usgs.gov","orcid":"https://orcid.org/0000-0002-0962-048X","contributorId":3454,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi","email":"kwallace@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917227,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Baxter, P.","contributorId":149588,"corporation":false,"usgs":false,"family":"Baxter","given":"P.","email":"","affiliations":[],"preferred":false,"id":917228,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70227737,"text":"70227737 - 2019 - Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction","interactions":[],"lastModifiedDate":"2022-01-28T15:34:56.321091","indexId":"70227737","displayToPublicDate":"2019-12-01T09:31:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction","docAbstract":"<p><span>Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framework for modeling functional responses with respect to a covariate without assuming a functional form. Many scientific disciplines use Gaussian process approximations to improve prediction and make inference on latent processes and parameters. When prediction is desired on unobserved covariates given realizations of the response variable, this is called inverse prediction. Because inverse prediction is often mathematically and computationally challenging, predicting unobserved covariates often requires fitting models that are different from the hypothesized generative model. We present a novel computational framework that allows for efficient inverse prediction using a Gaussian process approximation to generative models. Our framework enables scientific learning about how the latent processes co-vary with respect to covariates while simultaneously providing predictions of missing covariates. The proposed framework is capable of efficiently exploring the high dimensional, multi-modal latent spaces that arise in the inverse problem. To demonstrate flexibility, we apply our method in a generalized linear model framework to predict latent climate states given multivariate count data. Based on cross-validation, our model has predictive skill competitive with current methods while simultaneously providing formal, statistical inference on the underlying community dynamics of the biological system previously not available.</span></p>","language":"English","publisher":"Institute of Mathematical Statistics","doi":"10.1214/19-AOAS1281","usgsCitation":"Tipton, J.R., Hooten, M., Nolan, C., Booth, R.K., and McLachlan, J., 2019, Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction: Annals of Applied Statistics, v. 13, no. 4, p. 2363-2388, https://doi.org/10.1214/19-AOAS1281.","productDescription":"26 p.","startPage":"2363","endPage":"2388","ipdsId":"IP-089036","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/19-aoas1281","text":"Publisher Index Page"},{"id":395052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tipton, John R.","contributorId":272496,"corporation":false,"usgs":false,"family":"Tipton","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":56379,"text":"u ark","active":true,"usgs":false}],"preferred":false,"id":831989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":831988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Connor","contributorId":272497,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","affiliations":[{"id":56380,"text":"u az","active":true,"usgs":false}],"preferred":false,"id":831990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Booth, Robert K.","contributorId":272498,"corporation":false,"usgs":false,"family":"Booth","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56381,"text":"lehigh  u","active":true,"usgs":false}],"preferred":false,"id":831991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLachlan, Jason","contributorId":272499,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","affiliations":[{"id":36611,"text":"Notre Dame","active":true,"usgs":false}],"preferred":false,"id":831992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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