{"pageNumber":"768","pageRowStart":"19175","pageSize":"25","recordCount":184617,"records":[{"id":70202295,"text":"70202295 - 2019 - Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda)","interactions":[],"lastModifiedDate":"2019-03-15T12:33:32","indexId":"70202295","displayToPublicDate":"2019-02-20T16:17:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, <i>Lavinia exilicauda</i>)","title":"Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda)","docAbstract":"<p><span>In the United States, the Endangered Species Act (ESA) of 1973 was enacted to conserve species which are endangered or threatened throughout all or a portion of their range. The definition of ‘species’ includes subspecies and distinct population segments (DPSs). In freshwater fishes, use of DPS designations has largely been restricted to salmonid fishes (Salmonidae), although the DPS concept is increasingly applied to other fishes as well. As more taxa approach threatened status, the difficult question becomes what to do when genetic evidence does not strongly support formal taxonomic designations (full species or subspecies). We examine the potential use of the DPS concept to protect fishes using the example of Hitch (</span><i>Lavinia exilicauda</i><span>), a cyprinid fish endemic to California. The Hitch is divided up into three formally described, geographically separated subspecies. However, genomic studies (RADseq), presented here with three independent analyses using a large data set, only weakly support subspecies designations. Results suggest population but not subspecies structure. Nevertheless, conventional taxonomic methods, strong contemporary isolation, the importance of protecting genetic diversity, and high cultural values still qualify all three designated subspecies for DPS status and demonstrate how taxa such as Clear Lake Hitch can warrant protection under the ESA.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10144","usgsCitation":"Baumsteiger, J., Young, M.J., and Moyle, P.B., 2019, Using the Distinct Population Segment concept to protect fishes with low levels of genomic differentiation: conservation of an endemic minnow (Hitch, Lavinia exilicauda): Transactions of the American Fisheries Society, v. 148, no. 2, p. 406-416, https://doi.org/10.1002/tafs.10144.","productDescription":"11 p.","startPage":"406","endPage":"416","ipdsId":"IP-097862","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":361396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Baumsteiger, Jason","contributorId":200425,"corporation":false,"usgs":false,"family":"Baumsteiger","given":"Jason","email":"","affiliations":[],"preferred":false,"id":757690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyle, Peter B.","contributorId":117099,"corporation":false,"usgs":false,"family":"Moyle","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":757691,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202292,"text":"70202292 - 2019 - Sediment trapping and carbon sequestration in floodplains of the lower Atchafalaya Basin, LA: Allochthonous vs. autochthonous carbon sources","interactions":[],"lastModifiedDate":"2019-06-13T14:26:31","indexId":"70202292","displayToPublicDate":"2019-02-20T16:10:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Sediment trapping and carbon sequestration in floodplains of the lower Atchafalaya Basin, LA: Allochthonous vs. autochthonous carbon sources","docAbstract":"<p><span>Recent studies suggest that about 2 Pg of organic C is stored on floodplains worldwide. The present study indicates the Atchafalaya River, fifth largest river in the United States in terms of discharge, traps 30 mm/y of sediment on average within its floodplain, which is the highest average non‐episodic rate of fluvial deposition on the U.S. Coastal Plain. We installed sediment sampling stations at 23 sites, normally in transect, in the Atchafalaya Basin; these sites represent the range of hydrogeomorphic conditions on the floodplain based on hydrologic connectivity with the river main stem. The rate of sedimentation translates into about 12.5 Tg/y and includes 694 Mg/y of organic C. Highest sedimentation rates are associated with areas of high connectivity to channels and prograding deltaic processes. The δ</span><sup>13</sup><span>C content suggests that 35% of deposited C is derived from river‐suspended sediment compared to litterfall in the Basin. Thus, much of the organic C sequestered is allochthonous material. However, isolated interior sites with limited connectivity to the channel may generate and sequester large amounts of autochthonous C. The substantial trapping of both auto‐ and allochthonous C (392 Mg/y) make this freshwater‐forested floodplain critical in storage of material before reaching the coastal delta and estuary. This C deposition rate (340 g C m</span><sup>‐2</sup><span>y</span><sup>‐1</sup><span>) exceeds all other rates reported in recent Blue Carbon and Tidal Freshwater Forested Wetland studies. Atchafalaya C sequestration occurs in/near areas with tidal influence and like other coastal systems is an important site for trapping mineral and organic sediment and in global C cycling.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2018JG004533","usgsCitation":"Hupp, C.R., Kroes, D.E., Noe, G.E., Schenk, E.R., and Day, R.H., 2019, Sediment trapping and carbon sequestration in floodplains of the lower Atchafalaya Basin, LA: Allochthonous vs. autochthonous carbon sources: Journal of Geophysical Research: Biogeosciences, v. 124, no. 3, p. 663-677, https://doi.org/10.1029/2018JG004533.","productDescription":"15 p.","startPage":"663","endPage":"677","ipdsId":"IP-093039","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467885,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004533","text":"Publisher Index Page"},{"id":361394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Atchafalaya Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92,\n              29\n            ],\n            [\n              -91,\n              29\n            ],\n            [\n              -91,\n              30.5\n            ],\n            [\n              -92,\n              30.5\n            ],\n            [\n              -92,\n              29\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":757668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroes, Daniel E. 0000-0001-9107-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9107-9077","contributorId":213413,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":757670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schenk, Edward R.","contributorId":202018,"corporation":false,"usgs":false,"family":"Schenk","given":"Edward","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":757671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757672,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201134,"text":"sir20185155 - 2019 - Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota","interactions":[],"lastModifiedDate":"2019-02-21T16:34:58","indexId":"sir20185155","displayToPublicDate":"2019-02-20T12:45:38","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":"2018-5155","displayTitle":"Stochastic Model for Simulating Souris River Basin Regulated Streamflow Upstream from Minot, North Dakota","title":"Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota","docAbstract":"<p>The Souris River Basin is a 24,000 square-mile basin in the Provinces of Saskatchewan and Manitoba in Canada, and the State of North Dakota in the United States. Above-average snowpack during the winter of 2010–11, along with record-setting rains in May and June of 2011, led to record flooding that caused extensive damage to Minot, North Dakota, and numerous smaller communities in Saskatchewan, Manitoba, and North Dakota. As a result, the International Souris River Board created the Souris River Flood Task Force to evaluate potential reservoir operation changes and flood control measures to manage future floods and droughts. Part of this evaluation involved identifying a need for a stochastic streamflow model to estimate the likelihood of future flooding or drought.</p><p>A stochastic natural (unregulated) streamflow simulation model described in a previous report was built upon in this report to include the effects of regulation of four reservoirs (Rafferty, Alameda, and Boundary Reservoirs and Lake Darling) and their operation guidelines. First, a regulated reservoir storage/streamflow routing model was developed and calibrated from when all four reservoirs were in operation until the end of the reconstructed natural streamflow dataset provided by the U.S. Army Corps of Engineers (1992–2011). The regulated reservoir storage/streamflow routing model then was combined with the stochastic natural (unregulated) streamflow model to provide a stochastic regulated streamflow simulation model for the Souris River Basin upstream from Minot, North Dakota.</p><p>The stochastic regulated streamflow simulation model was used to estimate regulated flood frequency curves, which are useful for feasibility and design of critical structures such as levees or bridges. Three potential future climatic conditions were considered in this analysis: condition A (wet equilibrium), representing wet (similar to 1970–2017) climatic conditions; condition B (transition), representing transition from wet to dry (similar to 1912–69) climatic conditions; and condition C (dry equilibrium), representing dry climatic conditions. Comparison of the estimated flood frequency curves for regulated flow among the three climatic conditions indicated large differences in flood magnitudes for the more extreme (1-percent or less) annual exceedance probabilities. The estimated 0.2-percent annual exceedance probability flood magnitude for the Souris River upstream from Minot, N. Dak., was 29,300 cubic feet per second for condition A (wet equilibrium), compared to 14,800 cubic feet per second for condition C (dry equilibrium). For comparison, the recorded peak streamflow for 2011 for the Souris River upstream from Minot, N. Dak., was 26,900 cubic feet per second. Although it is not possible to predict how long the current (1970–2017) wet climatic conditions may persist, flood risk for at least the next 25 years, or until about 2040, may be represented best by climatic condition A.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185155","collaboration":"Prepared in cooperation with the North Dakota State Water Commission","usgsCitation":"Kolars, K.A., Vecchia, A.V., and Galloway, J.M., 2019, Stochastic model for simulating Souris River Basin regulated streamflow upstream from Minot, North Dakota: U.S. Geological Survey Scientific Investigations Report 2018–5155, 24 p., https://doi.org/10.3133/sir20185155.","productDescription":"viii, 24 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-090130","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":361373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5155/coverthb.jpg"},{"id":361374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5155/sir20185155.pdf","text":"Report","size":"1.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5155"}],"country":"United States","state":"North Dakota","city":"Minot","otherGeospatial":"Souris River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.04052734375,\n              48.99824008113872\n            ],\n            [\n              -104.74365234375,\n              49.42884000063522\n            ],\n            [\n              -104.7930908203125,\n              50.004208515595614\n            ],\n            [\n              -103.480224609375,\n              50.52041218671901\n            ],\n            [\n              -102.0245361328125,\n              50.604159488561\n            ],\n            [\n              -101.195068359375,\n              50.25071752130677\n            ],\n            [\n              -100.65673828125,\n              49.745781306155735\n            ],\n            [\n              -99.60891723632812,\n              49.648069803718805\n            ],\n            [\n              -99.18594360351562,\n              49.577773933420914\n            ],\n            [\n              -99.2340087890625,\n              49.39131220507362\n            ],\n            [\n              -99.76547241210936,\n              49.413653634531116\n            ],\n            [\n              -99.4482421875,\n              48.100094697973795\n            ],\n            [\n              -101.502685546875,\n              47.99727386804474\n            ],\n            [\n              -103.568115234375,\n              48.52388120259336\n            ],\n            [\n              -104.04052734375,\n              48.99824008113872\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey<br>821 East Interstate Avenue <br>Bismarck, ND 58503</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Stochastic Regulated Streamflow Model</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-02-20","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kolars, Kelsey A. 0000-0002-0540-3285","orcid":"https://orcid.org/0000-0002-0540-3285","contributorId":210965,"corporation":false,"usgs":true,"family":"Kolars","given":"Kelsey","email":"","middleInitial":"A.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202031,"text":"ofr20191006 - 2019 - Assessing causes of mortality for endangered juvenile Lost River suckers (Deltistes luxatus) in mesocosms in Upper Klamath Lake, south-central Oregon, 2016","interactions":[],"lastModifiedDate":"2019-02-21T16:39:23","indexId":"ofr20191006","displayToPublicDate":"2019-02-20T12:32:19","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1006","displayTitle":"Assessing Causes of Mortality for Endangered Juvenile Lost River Suckers (<em>Deltistes luxatus</em>) in Mesocosms in Upper Klamath Lake, South-Central Oregon, 2016","title":"Assessing causes of mortality for endangered juvenile Lost River suckers (Deltistes luxatus) in mesocosms in Upper Klamath Lake, south-central Oregon, 2016","docAbstract":"<h1>Executive Summary</h1><p class=\"p1\">The recovery of endangered Lost River suckers (<i>Deltistes luxatus</i>) in Upper Klamath Lake, south-central Oregon, has been impeded because juveniles are not recruiting into adult spawning populations. Adult sucker populations spawn each spring but mortality of age-0 suckers during their first summer is excessively high, and recruitment of juveniles into adult populations does not occur in most years. The last significant year class to join spawning aggregations was hatched in 1991. Capture rates for age-0 Lost River suckers decrease so substantially each summer that it is thought that mortality is nearly 100 percent within the first year of life each year. Causes of mortality are not understood but poor water quality, parasites, disease, predation, and non-native species are suspected to contribute to mortality. Upper Klamath Lake is hypereutrophic and summer water-quality conditions have large diurnal and seasonal fluctuations. Photosynthesis of <i>Aphanizomenon flos-aquae</i>, the most abundant cyanobacterium in Upper Klamath Lake, is responsible for large fluctuations in dissolved-oxygen (DO) concentrations and pH.</p><p class=\"p1\">We introduced hatchery-raised, passive integrated transponder-tagged juvenile Lost River suckers into large mesocosms located at Fish Banks, Mid North, and Rattlesnake Point in Upper Klamath Lake, Oregon, to assess sucker mortality relative to water-quality conditions. We identified the date of death for each sucker by assessing movement patterns among vertically stratified antennas. We modeled daily mortality using known fate models relative to water-quality conditions measured by sondes. Histopathology was used to understand causes of eminent mortality for moribund suckers.</p><p class=\"p1\">Fish mortality, growth, health, and movement patterns varied among locations, but it was unclear whether this variation was due to water-quality or other factors. Seasonal mortality was 58.8 percent at Fish Banks, 27.4 percent at Mid North, and 11.5 percent at Rattlesnake Point. Growth over the 109-day study period was lowest at Fish Banks (34.5 ±10.0 millimeters [mm] standard length (SL); 18.6 ±7.7 grams [g]), intermediate at Mid North (57.5 ±13.6 mm SL; 40.1 ±15.4 g), and greatest at Rattlesnake Point (78.4 ±13.0 mm SL; 72.5 ±18.7 g). Our ability to assess causes of juvenile sucker mortality in mesocosms using our modelling approach was limited by low daily mortality. Zero to 3 mortalities occurred per day, except on July 30 at Fish Banks when 7 mortalities occurred. Relative to any other measured and tested water-quality condition, mortality was more likely to occur on days with large fluctuations in oxygen percent saturation. When we assessed the fit of the most parsimonious model, performance was poor, which suggested that other factors were contributing to mortality. Our ability to assess the relationship between seasonal patterns in water quality and fish mortality were limited by the absence of substantial differences in water quality among sites, inconsistency in the depth at which measurements were collected, and no clear pattern in conditions leading up to and during mortality events. Except for DO at Rattlesnake Point and diel temperature&nbsp;variations at Fish Banks, seasonally summarized water-quality factors were similar among sites. The locations of water-quality monitors within the water column likely explain the differences in DO at Rattlesnake Point and temperature variation at Fish Banks. Furthermore, DO concentrations and other water-quality factors occurring during and prior to mortality events were inconsistent.</p><p class=\"p1\">Microscopic assessments indicated severe gill hyperplasia, fusion of the secondary lamellae, and severe <i>Ichthyobodo </i>sp. infestations on the gills of most moribund suckers. Liver glycogen was usually depleted in suckers with severe <i>Ichthyobodo </i>sp. infestations. <i>Ichthyobodo </i>sp. infestations probably were the immediate cause of death and probably originated from the Klamath Tribes Fish Research Facility, although this parasite also is present in Upper Klamath Lake and severe water-quality conditions may have contributed to morbidity. As suckers in the mesocosms died, they were replaced with suckers from the Fish Research Facility that likely were heavily parasitized with <i>Ichthyobodo </i>sp. Therefore, it is possible that the gradient in mortality rate among sites was owing to site-varying differences in inadvertent increases in introduced parasite loads.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191006","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hereford, D.M., Conway, C.M., Burdick, S.M., Elliott, D.G., Perry, T.M., Dolan-Caret, A., and Harris, A.C., 2019, Assessing causes of mortality for endangered juvenile Lost River suckers (Deltistes luxatus) in mesocosms in Upper Klamath Lake, south-central Oregon, 2016: U.S. Geological Survey Open -File Report 2019-1006, 80 p., https://doi.org/10.3133/ofr20191006.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-098400","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361283,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1006/ofr20191006.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1006"},{"id":361282,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1006/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.10273742675781,\n              42.22750046697999\n            ],\n            [\n              -121.79374694824219,\n              42.22750046697999\n            ],\n            [\n              -121.79374694824219,\n              42.595554553719204\n            ],\n            [\n              -122.10273742675781,\n              42.595554553719204\n            ],\n            [\n              -122.10273742675781,\n              42.22750046697999\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wfrc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/wfrc\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-02-20","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hereford, Danielle M.","contributorId":152642,"corporation":false,"usgs":true,"family":"Hereford","given":"Danielle M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":756777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":756778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":756779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":756780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perry, Todd M. 0000-0003-2899-2518","orcid":"https://orcid.org/0000-0003-2899-2518","contributorId":213307,"corporation":false,"usgs":true,"family":"Perry","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":756781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dolan-Caret, Amari","contributorId":212866,"corporation":false,"usgs":false,"family":"Dolan-Caret","given":"Amari","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":756782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":756783,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70201276,"text":"sir20185138 - 2019 - Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16","interactions":[],"lastModifiedDate":"2019-05-21T16:40:24","indexId":"sir20185138","displayToPublicDate":"2019-02-20T12:03:37","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":"2018-5138","displayTitle":"Hydraulic and Water-Quality Indicators of Aquifer Zones Contributing Groundwater Flow to Wells in the Santa Fe Group Aquifer System near Southeast Albuquerque, New Mexico, 2013–16","title":"Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16","docAbstract":"<p>An ethylene dibromide (EDB) plume extends approximately 5,880 feet northeast from the Bulk Fuels Facility on Kirtland Air Force Base. The leading edge of the EDB plume is about 3,700 feet upgradient from several water-supply wells. The water-supply wells are screened in the upper Santa Fe Group aquifer system. Within the upper Santa Fe Group, two primary clay-rich layers, the A1 and A2 units, separate water-producing zones. The U.S. Geological Survey, in cooperation with the Albuquerque Bernalillo County Water Utility Authority and the U.S. Air Force, installed four sentinel well nests and two aquifer-test pumping wells between the EDB plume and the water-supply wells. The purpose of the sentinel wells is to provide early warning of EDB plume migration towards water-supply wells. The sentinel well nests include at least three wells that are screened above, in between, and below the A1 and A2 units. The two aquifer-test pumping wells, installed for performing hydraulic tests on the aquifer system, are screened across both clay layers, as are the nearby water-supply wells. Well-bore flow logging indicated that greater than 60 percent of groundwater flow to the wells was through the deepest interval below the lowermost clay layer (A1 unit). The interval between the A1 and A2 units is the second most productive interval. Water-quality data also indicated that water drawn from the aquifer-test pumping wells and previously studied nearby water-supply wells is most similar in composition to water from the sentinel wells screened in the middle and deep intervals.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185138","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority and the U.S. Air Force","usgsCitation":"Travis, R.E., and Myers, N.C., 2019, Hydraulic and water-quality indicators of aquifer zones contributing groundwater flow to wells in the Santa Fe Group aquifer system near southeast Albuquerque, New Mexico, 2013–16 (ver. 1.1, May 2019): U.S. Geological Survey Scientific Investigations Report 2018–5138, 21 p., https://doi.org/10.3133/sir20185138.","productDescription":"v, 21 p.","numberOfPages":"32","onlineOnly":"Y","temporalStart":"2013-01-01","temporalEnd":"2016-12-31","ipdsId":"IP-093706","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":361320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5138/coverthb3.jpg"},{"id":361321,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5138/sir20185138.pdf","text":"Report","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5138"},{"id":363734,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5138/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018–5138 Version History"}],"country":"United States","state":"New Mexico","county":"Bernalillo County","city":"Albuquerque","otherGeospatial":"Kirtland Air Force Base, Santa Fe Group Aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107,\n              34.9\n            ],\n            [\n              -106.33,\n              34.9\n            ],\n            [\n              -106.33,\n              35.25\n            ],\n            [\n              -107,\n              35.25\n            ],\n            [\n              -107,\n              34.9\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":" Version 1.1 : May 14, 2019","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Groundwater Flow To Wells</li><li>Summary</li><li>Acknowledgments</li><li>References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-02-20","revisedDate":"2019-05-21","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Travis, R. E. 0000-0001-8601-7791 rtravis@usgs.gov","orcid":"https://orcid.org/0000-0001-8601-7791","contributorId":206438,"corporation":false,"usgs":true,"family":"Travis","given":"R.","email":"rtravis@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Nathan C. 0000-0002-7469-3693 nmyers@usgs.gov","orcid":"https://orcid.org/0000-0002-7469-3693","contributorId":1055,"corporation":false,"usgs":true,"family":"Myers","given":"Nathan","email":"nmyers@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753457,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202289,"text":"70202289 - 2019 - Hydrodynamic controls on sediment retention in an emerging diversion-fed delta","interactions":[],"lastModifiedDate":"2019-02-20T11:53:02","indexId":"70202289","displayToPublicDate":"2019-02-20T11:52:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrodynamic controls on sediment retention in an emerging diversion-fed delta","docAbstract":"<p><span>The&nbsp;morphodynamics&nbsp;of river-dominated deltas are largely controlled by the supply and retention of sediment within deltaic&nbsp;wetlands&nbsp;and the rate of relative&nbsp;sea-level rise. Yet,&nbsp;sediment budgets&nbsp;for deltas are often poorly constrained. In the Mississippi River Delta, a system rapidly losing land due to natural and anthropogenic causes, restoration efforts seek to build new land through the use of river diversions. At the Davis Pond Freshwater Diversion, a new&nbsp;crevasse&nbsp;splay has emerged since construction was completed in 2002. Here, we use beryllium-7 activity in&nbsp;sediment cores&nbsp;and USGS measurements of discharge and&nbsp;turbidity&nbsp;to calculate seasonal sediment input, deposition, and retention within the vegetated Davis Pond receiving basin. In winter/spring 2015, which included an experimental period of high discharge through the diversion, Davis Pond received 106,800 metric tons of sediment, 44% of which was retained within the basin. During this time, mean flow velocity was 0.21 m s</span><sup>−1</sup><span>&nbsp;and mean turbidity was 56 formazin nephelometric units (FNU). In summer/fall 2015, the Davis Pond basin received 35,900 metric tons of sediment, 81% of which was retained. Mean flow velocity in summer/fall was 0.10 m s</span><sup>−1</sup><span>&nbsp;and mean turbidity was 55 FNU. The increase in sediment retention from winter/spring 2015 to summer/fall 2015 may be due in part to the corresponding drop in&nbsp;water flow&nbsp;velocity, which allowed more sediment to settle out of suspension. Although high water discharge increases sediment input and deposition, increased turbulence associated with&nbsp;higher current&nbsp;velocity appears to increase sediment throughput and thereby decrease the sediment trapping efficiency. Sediment retention in Davis Pond is on the high end of the range seen in deltaic wetlands, perhaps due to the enclosed geometry of the receiving basin. Future diversion design and operation should target moderate water discharge and flow velocities in order to jointly maximize sediment deposition and retention and provide optimal conditions for delta growth.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.02.008","usgsCitation":"Keogh, M.E., Kolker, A.S., Snedden, G., and Renfro, A.A., 2019, Hydrodynamic controls on sediment retention in an emerging diversion-fed delta: Geomorphology, v. 332, p. 100-111, https://doi.org/10.1016/j.geomorph.2019.02.008.","productDescription":"12 p.","startPage":"100","endPage":"111","ipdsId":"IP-092068","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467886,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2019.02.008","text":"Publisher Index Page"},{"id":437565,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V7N49P","text":"USGS data release","linkHelpText":"Mineral content, bulk density, and beryllium-7 activity of wetland soils of the Davis Pond Freshwater Diversion Outfall Area, Louisiana, in 2015"},{"id":361386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.36529541015625,\n              29.844217466091493\n            ],\n            [\n              -90.2362060546875,\n              29.844217466091493\n            ],\n            [\n              -90.2362060546875,\n              29.963857983730453\n            ],\n            [\n              -90.36529541015625,\n              29.963857983730453\n            ],\n            [\n              -90.36529541015625,\n              29.844217466091493\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"332","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keogh, Molly E.","contributorId":213408,"corporation":false,"usgs":false,"family":"Keogh","given":"Molly","email":"","middleInitial":"E.","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":757660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolker, Alexander S.","contributorId":213409,"corporation":false,"usgs":false,"family":"Kolker","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":38749,"text":"Tulane University; Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":757661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":212275,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Renfro, Alisha A.","contributorId":213410,"corporation":false,"usgs":false,"family":"Renfro","given":"Alisha","email":"","middleInitial":"A.","affiliations":[{"id":38750,"text":"National Wildlife Federation, Mississippi River Delta Campaign","active":true,"usgs":false}],"preferred":false,"id":757662,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70202282,"text":"70202282 - 2019 - Dynamic N-mixture models with temporal variability in detection probability","interactions":[],"lastModifiedDate":"2019-02-20T10:44:50","indexId":"70202282","displayToPublicDate":"2019-02-20T10:44:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic N-mixture models with temporal variability in detection probability","docAbstract":"<p><span>In theory parameters of dynamic N-mixture models can be estimated with multiple years of data without the robust design under the assumption of constant detection probability. However, such an assumption can rarely be met in long-term studies, and the consequences of violating this assumption in the inferences of dynamic N-mixture models have not been assessed. In this study we used simulation studies to evaluate inferences of the original dynamic N-mixture model and two of its spatial extensions in the face of temporal variability in detection probability. We first evaluated the dynamic N-mixture models when detection probability that varied temporally was wrongly treated as a constant. We then evaluated if the robust design was necessary for dynamic N-mixture models to provide valid parameter estimates when detection probability was correctly assumed to vary temporally. Our results showed that, when detection probability that varied temporally was wrongly treated as a constant, biases were introduced in the parameter estimates of dynamic N-mixture models. When detection probability was correctly assumed to vary temporally, the models could provide valid parameter estimates with the robust design. The model could also provide valid parameter estimates when detection probability was a random effect, even without the robust design. Based on our results, we strongly recommended considering temporal variability in detection probability when using dynamic N-mixture models to analyze long-term data and adopting the robust design in long-term surveys. Our work here is not only useful for data analysis but also important for research design, and thus are relevant to a wide range of studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.12.007","usgsCitation":"Zhao, Q., and Royle, J.A., 2019, Dynamic N-mixture models with temporal variability in detection probability: Ecological Modelling, v. 393, p. 20-24, https://doi.org/10.1016/j.ecolmodel.2018.12.007.","productDescription":"5 p.","startPage":"20","endPage":"24","ipdsId":"IP-103124","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":361376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"393","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":213406,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","email":"","affiliations":[{"id":34045,"text":"Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523","active":true,"usgs":false}],"preferred":false,"id":757623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757622,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70223367,"text":"70223367 - 2019 - Socioecological determinants of drought impacts and coping strategies for ranching operations in the Great Plains","interactions":[],"lastModifiedDate":"2021-08-25T13:24:49.325426","indexId":"70223367","displayToPublicDate":"2019-02-20T08:21:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Socioecological determinants of drought impacts and coping strategies for ranching operations in the Great Plains","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0035\"><span>In Great Plains&nbsp;rangelands, drought is a recurring disturbance.&nbsp;</span>Ranchers<span>&nbsp;</span>in this region expect to encounter drought but may not be adequately prepared for it. Efforts to encourage drought preparedness would benefit from a better understanding of the conditions under which managers make decisions to minimize the impacts of drought. We tested the direct and moderating roles of the drought hazard and the social-ecological context on drought impacts and response. This study was conducted with ranchers in western and central South Dakota and Nebraska following the drought that began in 2012. We surveyed ranchers regarding the effects of the drought and their responses and used multimodel analysis to explore the relationships among measures of drought preparedness, drought response, and drought impacts. Drought severity was the primary predictor of all impacts, but specific types of impacts were varied depending on the operation’s enterprise mix, resources, and management. The socioecological characteristics of the ranch system predicted drought response actions taken, by either providing the necessary resources and capacity to take action or creating sensitivity in the system that required action to be taken. We conclude with recommendations for learning from current drought experiences in order to better adapt to future drought events.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2019.01.002","usgsCitation":"Haigh, T., Schact, W., Knutson, C., Smart, A., Volesky, J., Allen, C.R., Hayes, M., and Burbach, M., 2019, Socioecological determinants of drought impacts and coping strategies for ranching operations in the Great Plains: Rangeland Ecology and Management, v. 72, no. 3, p. 561-571, https://doi.org/10.1016/j.rama.2019.01.002.","productDescription":"11 p.","startPage":"561","endPage":"571","ipdsId":"IP-102618","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":388479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haigh, T.R.","contributorId":264686,"corporation":false,"usgs":false,"family":"Haigh","given":"T.R.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schact, W.","contributorId":264687,"corporation":false,"usgs":false,"family":"Schact","given":"W.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knutson, C.L.","contributorId":264688,"corporation":false,"usgs":false,"family":"Knutson","given":"C.L.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smart, A.","contributorId":264690,"corporation":false,"usgs":false,"family":"Smart","given":"A.","email":"","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":821872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Volesky, J.","contributorId":264693,"corporation":false,"usgs":false,"family":"Volesky","given":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821874,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayes, M.P.","contributorId":56174,"corporation":false,"usgs":false,"family":"Hayes","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":821875,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burbach, M.","contributorId":264697,"corporation":false,"usgs":false,"family":"Burbach","given":"M.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":821876,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70210524,"text":"70210524 - 2019 - Resource selection and wintering phenology of White-winged Scoters in southern New England: Implications for offshore wind energy development","interactions":[],"lastModifiedDate":"2020-06-11T14:31:43.806356","indexId":"70210524","displayToPublicDate":"2019-02-20T07:47:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Resource selection and wintering phenology of White-winged Scoters in southern New England: Implications for offshore wind energy development","docAbstract":"<p>Southern New England provides key wintering habitat for White-winged Scoters (<i>Melanitta fusca</i>). This area has also pioneered the development of offshore wind energy in North America and the U.S. Bureau of Ocean Energy Management (BOEM) has established nine Wind Energy Area (WEA) lease blocks along the Atlantic Outer Continental Shelf in areas that may provide important staging and wintering habitat for scoters and other species of sea ducks. Concern over the potential impact of offshore wind energy on sea duck populations has led to efforts to develop models to understand their distribution, habitat use and site fidelity. We used satellite telemetry to document winter phenology and site fidelity, as well as fine-scale resource selection and habitat use of 40 White-winged Scoters along the southern New England continental shelf. Scoters spent over half of the annual cycle on the wintering grounds and demonstrated a high degree of inter-annual site fidelity to composite core-use areas. Sizes of individual 50% core-use home ranges were variable (x̅ = 868 km2; range = 32 to 4,220 km2) and individual 95% utilization distributions ranged widely (x̅ = 4,388 km2; range = 272 to 18,235 km2). More than half of all tagged birds occupied two or more discrete core-use areas that were up to 400 km apart. Throughout the study area, scoters selected for areas with lower salinity, lower sea surface temperature, higher chlorophyll-a concentrations, and higher hard-bottom substrate probability. Resource selection function models classified 18,649 km2 (23%) of the study area as high probability of use, which included or immediately bordered ~420 km2 of proposed WEA lease blocks. Future offshore wind energy developments in the region should avoid key habitats highlighted by this study and carefully consider the environmental characteristics selected by sea ducks when planning and siting future WEAs.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duy014","usgsCitation":"Meattey, D.E., McWilliams, S.R., Paton, P.W., Lepage, C., Gilliland, S.G., Savoy, L., Olsen, G.H., and Osenkowski, J.E., 2019, Resource selection and wintering phenology of White-winged Scoters in southern New England: Implications for offshore wind energy development: Condor, v. 121, no. 1, duy014, https://doi.org/10.1093/condor/duy014.","productDescription":"duy014","ipdsId":"IP-090294","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488696,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/nrs_facpubs/529","text":"External Repository"},{"id":375459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Southern New England","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.3447265625,\n              40.84706035607122\n            ],\n            [\n              -69.9169921875,\n              40.84706035607122\n            ],\n            [\n              -69.9169921875,\n              43.866218006556394\n            ],\n            [\n              -73.3447265625,\n              43.866218006556394\n            ],\n            [\n              -73.3447265625,\n              40.84706035607122\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"121","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Meattey, Dustin E.","contributorId":225141,"corporation":false,"usgs":false,"family":"Meattey","given":"Dustin","email":"","middleInitial":"E.","affiliations":[{"id":41045,"text":"Department of Natural Resources Sciences, University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":790515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McWilliams, Scott R.","contributorId":172328,"corporation":false,"usgs":false,"family":"McWilliams","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":790516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paton, Peter W.C.","contributorId":225142,"corporation":false,"usgs":false,"family":"Paton","given":"Peter","email":"","middleInitial":"W.C.","affiliations":[{"id":41045,"text":"Department of Natural Resources Sciences, University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":790517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lepage, Christine","contributorId":194564,"corporation":false,"usgs":false,"family":"Lepage","given":"Christine","email":"","affiliations":[],"preferred":false,"id":790518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gilliland, Scott G.","contributorId":225143,"corporation":false,"usgs":false,"family":"Gilliland","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":41046,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, Sackville, NB","active":true,"usgs":false}],"preferred":false,"id":790519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Savoy, Lucas","contributorId":171896,"corporation":false,"usgs":false,"family":"Savoy","given":"Lucas","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":790612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":790520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Osenkowski, Jason E.","contributorId":225144,"corporation":false,"usgs":false,"family":"Osenkowski","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":41047,"text":"Rhode Island Department of Environmental Management, West Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":790521,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70227202,"text":"70227202 - 2019 - On the eruption age and provenance of the Old Crow tephra","interactions":[],"lastModifiedDate":"2022-01-04T13:38:54.208359","indexId":"70227202","displayToPublicDate":"2019-02-20T07:33:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"On the eruption age and provenance of the Old Crow tephra","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Tephrochronology&nbsp;is used to correlate and reconstruct geographically disparate sedimentary records of changing environment, climate, and landscape throughout geologic time. Single&nbsp;tephra&nbsp;layers represent isochronous markers across broad regions, thus accurate and precise radiometric constraints on the timing of eruption are critical to their utility. The Old Crow tephra is found throughout eastern&nbsp;Beringia&nbsp;and represents the largest preserved Pleistocene ashfall event in the region. Despite its volume and significance as a stratigraphic marker, the provenance of this tephra is debated, and the interpreted eruption age of&nbsp;marine isotope stage&nbsp;(MIS) 5 at ∼125 ka has vacillated. To investigate provenance and eruption age, we develop a geochemical fingerprint for the Old Crow tephra via&nbsp;titanomagnetite&nbsp;geochemistry, and&nbsp;zircon&nbsp;crystallization/cooling age via coupled U/Pb, U/Th, and (U</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Th)/He zircon&nbsp;geochronology. Our results indicate that Old Crow oxides are geochemically distinct from the commonly assumed source-caldera system at the Emmons Lake Volcanic Center (ELVC). Zircon crystals from the Old Crow tephra range in age from Proterozoic to Pleistocene, with concordant zircon U/Pb, U/Th, and (U</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Th)/He dates on the youngest population of grains suggesting crystallization in their parent&nbsp;magma, and in turn eruption, at 202.9 ± 9.5 ka. We discuss strengths and shortcomings of our radiogenic datasets in light of this result and review the far-reaching implications of a change in Old Crow eruption age.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2018.12.026","usgsCitation":"Burgess, S.D., Coble, M., Vazquez, J.A., Coombs, M.L., and Wallace, K.L., 2019, On the eruption age and provenance of the Old Crow tephra: Quaternary Science Reviews, v. 207, p. 64-79, https://doi.org/10.1016/j.quascirev.2018.12.026.","productDescription":"16 p.","startPage":"64","endPage":"79","ipdsId":"IP-092238","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2018.12.026","text":"Publisher Index Page"},{"id":393841,"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              -168.5302734375,\n              52.93539665862316\n            ],\n            [\n              -158.642578125,\n              52.93539665862316\n            ],\n            [\n              -158.642578125,\n              56.992882804633986\n            ],\n            [\n              -168.5302734375,\n              56.992882804633986\n            ],\n            [\n              -168.5302734375,\n              52.93539665862316\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"207","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burgess, Seth D. 0000-0002-4238-3797 sburgess@usgs.gov","orcid":"https://orcid.org/0000-0002-4238-3797","contributorId":200371,"corporation":false,"usgs":true,"family":"Burgess","given":"Seth","email":"sburgess@usgs.gov","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coble, Matthew 0000-0002-7536-0559","orcid":"https://orcid.org/0000-0002-7536-0559","contributorId":270794,"corporation":false,"usgs":false,"family":"Coble","given":"Matthew","email":"","affiliations":[{"id":56217,"text":"Victoria University of Wellington","active":true,"usgs":false}],"preferred":false,"id":830067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":830068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":830069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":830070,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215777,"text":"70215777 - 2019 - Pace and process of active folding and fluvial incision across the Kantishna Hills anticline, central Alaska","interactions":[],"lastModifiedDate":"2023-11-08T15:12:58.112004","indexId":"70215777","displayToPublicDate":"2019-02-19T16:51:55","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":"Pace and process of active folding and fluvial incision across the Kantishna Hills anticline, central Alaska","docAbstract":"<p><span>Rates of northern Alaska Range thrust system deformation are poorly constrained. Shortening at the system's west end is focused on the Kantishna Hills anticline. Where the McKinley River cuts across the anticline, the landscape records both Late Pleistocene deformation and climatic change. New optically stimulated luminescence and cosmogenic&nbsp;</span><sup>10</sup><span>Be depth profile dates of three McKinley River terrace levels (~22, ~18, and ~14–9&nbsp;ka) match independently determined ages of local glacial maxima, consistent with climate‐driven terrace formation. Terrace ages quantify rates of differential bedrock incision, uplift, and shortening based on fault depth inferred from microseismicity. Differential rock uplift and incision (≤1.4&nbsp;m/kyr) drive significant channel width narrowing in response to ongoing folding at a shortening rate of ~1.2&nbsp;m/kyr. Our results constrain northern Alaska Range thrust system deformation rates, and elucidate superimposed landscape responses to Late Pleistocene climate change and active folding with broad geomorphic implications.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL081509","usgsCitation":"Bender, A., Lease, R.O., Haeussler, P., Rittenour, T.M., Corbett, L.B., Bierman, P., and Caffee, M.W., 2019, Pace and process of active folding and fluvial incision across the Kantishna Hills anticline, central Alaska: Geophysical Research Letters, v. 46, no. 6, p. 3235-3244, https://doi.org/10.1029/2018GL081509.","productDescription":"10 p.","startPage":"3235","endPage":"3244","ipdsId":"IP-104095","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":467888,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl081509","text":"Publisher Index Page"},{"id":379942,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kantishna Hills Anticline","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -152,\n              62.98705624498942\n            ],\n            [\n              -150.96010784195508,\n              63.15735497855914\n            ],\n            [\n              -151.18806303078333,\n              63.528946255723135\n            ],\n            [\n              -152.17666527134193,\n              63.34288710983481\n            ],\n            [\n              -152,\n              62.98705624498942\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"46","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":803397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":803398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":803399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rittenour, Tammy M.","contributorId":140755,"corporation":false,"usgs":false,"family":"Rittenour","given":"Tammy","email":"","middleInitial":"M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":803400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corbett, Lee B.","contributorId":152123,"corporation":false,"usgs":false,"family":"Corbett","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":803401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bierman, Paul R.","contributorId":198743,"corporation":false,"usgs":false,"family":"Bierman","given":"Paul R.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":803402,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caffee, Marc W. 0000-0002-6846-8967","orcid":"https://orcid.org/0000-0002-6846-8967","contributorId":193417,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"W.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":803403,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70202269,"text":"70202269 - 2019 - Oxygen isotopic investigation of silicic magmatism in the Stillwater caldera complex, Nevada: Generation of large-volume, low-δ18O rhyolitic tuffs and assessment of their regional context in the Great Basin of the western United States","interactions":[],"lastModifiedDate":"2019-06-18T10:08:47","indexId":"70202269","displayToPublicDate":"2019-02-19T16:28:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Oxygen isotopic investigation of silicic magmatism in the Stillwater caldera complex, Nevada: Generation of large-volume, low-δ<sup>18</sup>O rhyolitic tuffs and assessment of their regional context in the Great Basin of the western United States","title":"Oxygen isotopic investigation of silicic magmatism in the Stillwater caldera complex, Nevada: Generation of large-volume, low-δ18O rhyolitic tuffs and assessment of their regional context in the Great Basin of the western United States","docAbstract":"<p><span>Successive caldera-forming eruptions from ca. 30 to 25 Ma generated a large nested caldera complex in western Nevada that was subsequently dissected by Basin and Range extension, providing extraordinary cross-sectional views through diverse volcanic and plutonic rocks. A high-resolution oxygen isotopic study was conducted on units that represent all major parts of the Job Canyon, Louderback Mountains, Poco Canyon, and Elevenmile Canyon caldera cycles (29.2−25.1 Ma), and several Cretaceous plutons that flank the Stillwater caldera complex. We provide new oxygen and strontium isotope data for 12 additional caldera centers in the Great Basin, which are synthesized with &gt;150 published oxygen and strontium isotope analyses for regional Mesozoic basement rocks. Stillwater zircons span a large isotopic range (δ</span><sup>18</sup><span>O</span><sub>zircon</sub><span>&nbsp;of 3.6‰−8.2‰), and all caldera cycles possess low-δ</span><sup>18</sup><span>O zircons. In some cases, they are a small proportion of the total populations, and in others, they dominate, such as in the low-δ</span><sup>18</sup><span>O rhyolitic tuffs of Job Canyon and Poco Canyon (δ</span><sup>18</sup><span>O</span><sub>zircon</sub><span>&nbsp;= 4.0‰−4.3‰; δ</span><sup>18</sup><span>O</span><sub>magma</sub><span>&nbsp;= 5.5‰−6‰). These are the first low-δ</span><sup>18</sup><span>O rhyolites documented in middle Cenozoic calderas of the Great Basin, adding to the global occurrence of these important magma types that fingerprint recycling of shallow crust altered by low-δ</span><sup>18</sup><span>O meteoric waters. The appearance of low-δ</span><sup>18</sup><span>O rhyolites in the Stillwater caldera complex is overprinted on a Great Basin−wide trend of miogeoclinal sediment contribution to silicic magmas that elevates δ</span><sup>18</sup><span>O compositions, making identification of&nbsp;</span><sup>18</sup><span>O depletions difficult. Though not a nominally low-δ</span><sup>18</sup><span>O rhyolite, the tuff of Elevenmile Canyon possesses both low-δ</span><sup>18</sup><span>O and high-δ</span><sup>18</sup><span>O zircon cores that are overgrown by homogenized zircon rims that approximate the bulk zircon average, pointing to batch assembly of isotopically diverse upper crustal melts to generate one of the most voluminous (2500−5000 km</span><sup>3</sup><span>) tuff eruptions in the Great Basin. Despite overlapping in space and time, each caldera-forming cycle of the Stillwater complex has a unique oxygen isotope record as retained in single zircons. Most plutons that were spatially and temporally coincident with calderas have isotopic compositions that diverge from the caldera-forming tuffs and cannot be their cogenetic remnants.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35021.1","usgsCitation":"Watts, K., John, D.A., Colgan, J.P., Henry, C., Bindeman, I.N., and Valley, J.W., 2019, Oxygen isotopic investigation of silicic magmatism in the Stillwater caldera complex, Nevada: Generation of large-volume, low-δ18O rhyolitic tuffs and assessment of their regional context in the Great Basin of the western United States: GSA Bulletin, v. 131, no. 7-8, p. 1133-1156, https://doi.org/10.1130/B35021.1.","productDescription":"14 p.","startPage":"1133","endPage":"1156","ipdsId":"IP-097705","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467889,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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,{"id":70202271,"text":"70202271 - 2019 - Complex immune responses and molecular reactions to pathogens and disease in a desert reptile (Gopherus agassizii)","interactions":[],"lastModifiedDate":"2019-03-15T12:34:54","indexId":"70202271","displayToPublicDate":"2019-02-19T16:23:54","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}},"displayTitle":"Complex immune responses and molecular reactions to pathogens and disease in a desert reptile (<i>Gopherus agassizii</i>)","title":"Complex immune responses and molecular reactions to pathogens and disease in a desert reptile (Gopherus agassizii)","docAbstract":"<p><span>Immune function plays an important role in an animal's defense against infectious disease. In reptiles, immune responses may be complex and counterintuitive, and diagnostic tools used to identify infection, such as induced antibody responses are limited. Recent studies using gene transcription profiling in tortoises have proven useful in identifying immune responses to various intrinsic and extrinsic stressors. As part of a larger experiment with Mojave desert tortoises (</span><i>Gopherus agassizii</i><span>), we facilitated the transmission of the pathogenic bacteria,&nbsp;</span><i>Mycoplasma agassizii<span>&nbsp;</span></i><span>(Myag), to naïve adults and measured innate and induced immune reactions over time. Specifically, we evaluated clinical condition, presence of Myag in the nasal/oral cavity, induced antibody responses specific to Myag, and measured molecular reactions (gene transcript profiles) in 15 captive tortoises classified as naïve, exposed, or infected and 14 wild tortoises for comparison. Myag was confirmed inside the nasal/oral cavity in exposed tortoises within 30–60&nbsp;days of introduction to infected animals, yet we did not detect Myag specific induced antibody responses in these individuals until 420–595&nbsp;days post exposure. Surprisingly, we found no overall differences in the gene transcript profiles between our experimental treatment groups throughout this study. This work highlights the complexities in assessing immune function and diagnosing pathogen related infections in tortoises and other reptiles.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4897","usgsCitation":"Drake, K.K., Aiello, C., Bowen, L., Lewison, R.L., Esque, T., Nussear, K.E., Waters-Dynes, S.C., and Hudson, P.J., 2019, Complex immune responses and molecular reactions to pathogens and disease in a desert reptile (Gopherus agassizii): Ecology and Evolution, v. 9, no. 5, p. 2516-2534, https://doi.org/10.1002/ece3.4897.","productDescription":"19 p.","startPage":"2516","endPage":"2534","ipdsId":"IP-103924","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":460468,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4897","text":"Publisher Index Page"},{"id":437567,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P940J8EY","text":"USGS data release","linkHelpText":"Ecological and Disease Data for Induced Immune Responses and Antibody Levels for Mycoplasma spp. in Captive and Wild Mojave Desert Tortoises (Gopherus agassizii)"},{"id":361360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiello, Christina M. 0000-0002-2399-5464","orcid":"https://orcid.org/0000-0002-2399-5464","contributorId":213367,"corporation":false,"usgs":false,"family":"Aiello","given":"Christina M.","affiliations":[{"id":38741,"text":"former USGS WERC employee","active":true,"usgs":false}],"preferred":false,"id":757576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewison, Rebecca L.","contributorId":194537,"corporation":false,"usgs":false,"family":"Lewison","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":757578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, Kenneth E.","contributorId":117361,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":757579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":757580,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hudson, Peter J.","contributorId":204377,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":757581,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70202277,"text":"70202277 - 2019 - Phylogeography and evolution of infectious hematopoietic necrosis virus in China","interactions":[],"lastModifiedDate":"2019-02-19T16:20:53","indexId":"70202277","displayToPublicDate":"2019-02-19T16:20:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Phylogeography and evolution of infectious hematopoietic necrosis virus in China","docAbstract":"<p><span>Infectious hematopoietic necrosis virus (IHNV) is a well-known rhabdoviral pathogen of salmonid fish. In this study, a comprehensive analysis of 40 IHNV viruses isolated from thirteen fish farms in nine geographically dispersed Chinese provinces during 2012 to 2017 is presented. Identity of nucleotide and amino acid sequences among all the complete glycoprotein (G) genes from Chinese isolates was 98.0–100% and 96.7–100%, respectively. Coalescent phylogenetic analyses revealed that all the Chinese IHN virus characterized in this study were in a monophyletic clade that had a most recent common ancestor with the J Nagano (JN) subgroup within the J genogroup of IHNV. Within the Chinese IHNV clade isolates obtained over successive years from the same salmon fish farm clustered in strongly supported subclades, suggesting maintenance and diversification of virus over time within individual farms. There was also evidence for regional virus transmission within provinces, and some cases of longer distance transmission between distant provinces, such as Gansu and Yunnan. The data demonstrated that IHNV has evolved into a new subgroup in salmon farm environments in China, and IHNV isolates are undergoing molecular evolution within fish farms. We suggest that Chinese IHNV comprises a separate JC subgroup within the J genogroup of IHNV.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2018.10.030","usgsCitation":"Xu, L., Zhao, J., Liu, M., Kurath, G., Breyta, R.B., Ren, G., Yin, J., Liu, H., and Lu, T., 2019, Phylogeography and evolution of infectious hematopoietic necrosis virus in China: Molecular Phylogenetics and Evolution, v. 131, p. 19-28, https://doi.org/10.1016/j.ympev.2018.10.030.","productDescription":"10 p.","startPage":"19","endPage":"28","ipdsId":"IP-097179","costCenters":[{"id":654,"text":"Western Fisheries Research 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Liming","contributorId":198109,"corporation":false,"usgs":false,"family":"Xu","given":"Liming","email":"","affiliations":[],"preferred":false,"id":757593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Jingzhuang","contributorId":198110,"corporation":false,"usgs":false,"family":"Zhao","given":"Jingzhuang","email":"","affiliations":[],"preferred":false,"id":757594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Miao","contributorId":198111,"corporation":false,"usgs":false,"family":"Liu","given":"Miao","email":"","affiliations":[],"preferred":false,"id":757595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X 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Jiasheng","contributorId":198113,"corporation":false,"usgs":false,"family":"Yin","given":"Jiasheng","email":"","affiliations":[],"preferred":false,"id":757599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liu, Hongbai","contributorId":198114,"corporation":false,"usgs":false,"family":"Liu","given":"Hongbai","email":"","affiliations":[],"preferred":false,"id":757600,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lu, Tongyan","contributorId":198116,"corporation":false,"usgs":false,"family":"Lu","given":"Tongyan","email":"","affiliations":[],"preferred":false,"id":757601,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70202058,"text":"tm7C21 - 2019 - User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script","interactions":[],"lastModifiedDate":"2019-03-12T11:01:57","indexId":"tm7C21","displayToPublicDate":"2019-02-19T15:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C21","displayTitle":"User’s Guide for  Assessment Tract Aggregation GUI (ATA GUI)—A Graphical User Interface for the AggtEx.fn R Script","title":"User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script","docAbstract":"<p>The U.S. Geological Survey three-part method for mineral resource assessments estimates numbers of undiscovered mineral deposits as probability distributions in geologically defined regions termed “permissive tracts.” This report describes a graphical user interface (GUI) script developed in open-source statistical software (R) that aggregates estimated undiscovered deposits of a given type from two or more permissive tracts using the AggtEx.fn R script. The AggtEx.fn R script aggregates undiscovered deposit estimates assuming independence, total dependence, or some degree of correlation among aggregated areas, given a user-specified correlation matrix. The script outputs three sets of aggregated estimates based on those three assumptions.</p><p>The GUI script described in this report, Assessment Tract Aggregation GUI (ATA GUI), provides an easy-to-use tool that supports implementation of the AggtEx.fn R script, installation of the R packages needed to run the application, and creation of a combined input file from individual files generated by the MapMark4GUI software. Users can also use EMINERS output information by creating a file of output values following the MapMark4GUI output file format. The probabilistic estimates of aggregated undiscovered deposits produced by ATA GUI can be used as input for MapMark4GUI to estimate contained resources for the aggregated tracts. MapMark4GUI uses Monte Carlo simulation to combine undiscovered deposit estimates with tonnage and grade models to simulate undiscovered mineral resources for a region of interest. This simulation includes the amounts of commodities and rock that could be present within a permissive tract. This report includes instructions on installing and running the ATA GUI script and describes the input and output files used and created during the aggregation process.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: <i>Automated data processing and computations</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C21","collaboration":" ","usgsCitation":"Shapiro, J.L., and Robinson, G.R., Jr., 2019, User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script: U.S. Geological Survey Techniques and Methods, book 7, chap. C21, 9 p., https://doi.org/10.3133/tm7c21.","productDescription":"Report: iv, 9 p.; Assessment Tract Aggregation GUI Package","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098557","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":361327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c21/coverthb.jpg"},{"id":361328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c21/tmc721.pdf","text":"Report","size":"1.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C21"},{"id":361329,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c21/tm7c21_ATAGUI_Package.zip","text":"Assessment Tract Aggregation GUI Package","size":"751 KB","linkFileType":{"id":6,"text":"zip"}}],"contact":"<p><a href=\"https://minerals.usgs.gov/east/index.html\" data-mce-href=\"https://minerals.usgs.gov/east/index.html\">Eastern Mineral and Environmental Resources Science Center</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>954 Mail Stop <br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Background</li><li>Assessment Tract Aggregation GUI</li><li>Assessment Tract Aggregation GUI Package</li><li>Input Files</li><li>Installation Instructions</li><li>Launching Assessment Tract Aggregation GUI</li><li>Output Files</li><li>Using the Aggregation Results to Estimate Undiscovered Resources with MapMark4GUI</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-19","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Jason L. 0000-0002-7641-9735","orcid":"https://orcid.org/0000-0002-7641-9735","contributorId":204311,"corporation":false,"usgs":true,"family":"Shapiro","given":"Jason L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":756815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Jr. 0000-0002-9676-9564","orcid":"https://orcid.org/0000-0002-9676-9564","contributorId":8479,"corporation":false,"usgs":true,"family":"Robinson","suffix":"Jr.","email":"","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":756816,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202265,"text":"70202265 - 2019 - Occupancy models for citizen-science data","interactions":[],"lastModifiedDate":"2019-02-19T13:21:25","indexId":"70202265","displayToPublicDate":"2019-02-19T13:21:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy models for citizen-science data","docAbstract":"<ol class=\"\"><li>Large‐scale citizen‐science projects, such as atlases of species distribution, are an important source of data for macroecological research, for understanding the effects of climate change and other drivers on biodiversity, and for more applied conservation tasks, such as early‐warning systems for biodiversity loss.</li><li>However, citizen‐science data are challenging to analyse because the observation process has to be taken into account. Typically, the observation process leads to heterogeneous and non‐random sampling, false absences, false detections, and spatial correlations in the data. Increasingly, occupancy models are being used to analyse atlas data.</li><li>We advocate a dual approach to strengthen inference from citizen science data for the questions the programme is intended to address: (a) the survey design should be chosen with a particular set of questions and associated analysis strategy in mind and (b) the statistical methods should be tailored not only to those questions but also to the specific characteristics of the data.</li><li>We review the consequences of particular survey design choices that typically need to be made in atlas‐style citizen‐science projects. These include spatial resolution of the sampling units, allocation of effort in space, and collection of information about the observation process. On the analysis side, we review extensions of the basic occupancy models that are frequently necessary with atlas data, including methods for dealing with heterogeneity, non‐independent detections, false detections, and violation of the closure assumption.</li><li>New technologies, such as cell‐phone apps and fixed remote detection devices, are revolutionizing citizen‐science projects. There is an opportunity to maximize the usefulness of the resulting datasets if the protocols are rooted in robust statistical designs and data analysis issues are being considered. Our review provides guidelines for designing new projects and an overview of the current methods that can be used to analyse data from such projects.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13090","usgsCitation":"Altwegg, R., and Nichols, J.D., 2019, Occupancy models for citizen-science data: Methods in Ecology and Evolution, v. 10, no. 1, p. 8-21, https://doi.org/10.1111/2041-210X.13090.","productDescription":"14 p.","startPage":"8","endPage":"21","ipdsId":"IP-096838","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13090","text":"Publisher Index Page"},{"id":361349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Altwegg, Res","contributorId":171528,"corporation":false,"usgs":false,"family":"Altwegg","given":"Res","email":"","affiliations":[],"preferred":false,"id":757564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":757553,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70202266,"text":"70202266 - 2019 - Per- and polyfluoroalkyl substances (PFAS) in plasma of the West Indian manatee (Trichechus manatus)","interactions":[],"lastModifiedDate":"2019-02-19T13:14:28","indexId":"70202266","displayToPublicDate":"2019-02-19T13:14:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Per- and polyfluoroalkyl substances (PFAS) in plasma of the West Indian manatee (<i>Trichechus manatus</i>)","title":"Per- and polyfluoroalkyl substances (PFAS) in plasma of the West Indian manatee (Trichechus manatus)","docAbstract":"<p><span>Per- and polyfluoroalkyl substances (PFAS) are ubiquitous, synthetic anthropogenic chemicals known to infiltrate and persist in biological systems as a result of their stability and bioaccumulation potential. This study investigated 15 PFAS, including short-chain&nbsp;carboxylic and sulfonic acids, and their presence in a threatened&nbsp;herbivore, the West Indian&nbsp;manatee&nbsp;(</span><span><i>Trichechus manatus</i></span><span>). Seven of the 15 PFAS examined were detected in manatee plasma. Perfluorooctanesulfonic acid (PFOS) (ranging from 0.13 to 166 ng/g ww) and perfluorononanoic acid (PFNA) (ranging from 0.038 to 3.52 ng/g ww) were detected in every manatee plasma sample examined (</span><i>n</i><span> = 69), with differing medians across sampling sites in Florida, Crystal River (</span><i>n</i><span> = 39), Brevard County (</span><i>n</i><span> = 18), Everglades National Park (</span><i>n</i><span> = 8), and four samples (</span><i>n</i><span> = 4) from Puerto Rico. With an herbivorous diet and long life-span, the manatee provides a new perspective to monitoring PFAS&nbsp;contamination.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2019.02.010","usgsCitation":"Palmer, K., Bangma, J.T., Reiner, J.L., Bonde, R.K., Korte, J.E., Boggs, A.S., and Bowden, J.A., 2019, Per- and polyfluoroalkyl substances (PFAS) in plasma of the West Indian manatee (Trichechus manatus): Marine Pollution Bulletin, v. 140, p. 610-615, https://doi.org/10.1016/j.marpolbul.2019.02.010.","productDescription":"6 p.","startPage":"610","endPage":"615","ipdsId":"IP-091457","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460471,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc6529203","text":"External Repository"},{"id":361348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"140","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Palmer, Kady","contributorId":213359,"corporation":false,"usgs":false,"family":"Palmer","given":"Kady","email":"","affiliations":[{"id":35839,"text":"College of Charleston","active":true,"usgs":false}],"preferred":false,"id":757555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bangma, Jacqueline T.","contributorId":213360,"corporation":false,"usgs":false,"family":"Bangma","given":"Jacqueline","email":"","middleInitial":"T.","affiliations":[{"id":38740,"text":"Medical University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":757556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reiner, Jessica L.","contributorId":213361,"corporation":false,"usgs":false,"family":"Reiner","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":757557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korte, Jeffrey E.","contributorId":213362,"corporation":false,"usgs":false,"family":"Korte","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":38740,"text":"Medical University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":757558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boggs, Ashley S. P.","contributorId":213364,"corporation":false,"usgs":false,"family":"Boggs","given":"Ashley","email":"","middleInitial":"S. P.","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":757560,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowden, John A.","contributorId":213363,"corporation":false,"usgs":false,"family":"Bowden","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":757559,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70215593,"text":"70215593 - 2019 - Spatially distributed denitrification in a karst springshed","interactions":[],"lastModifiedDate":"2020-10-25T17:58:54.311132","indexId":"70215593","displayToPublicDate":"2019-02-19T12:54:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7176,"text":"Hydrologic Processes","active":true,"publicationSubtype":{"id":10}},"title":"Spatially distributed denitrification in a karst springshed","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Karst spring measurements assess biogeochemical processes occurring within groundwater contributing areas to springs (springsheds) but can only provide aggregated information. To better understand spatially distributed processes that comprise these aggregated measures, we investigated aquifer denitrification evidence in groundwater wells (<i>n</i>&nbsp;=&nbsp;16) distributed throughout a springshed in the Upper Floridan aquifer in northern Florida. Aquifer geochemistry, nitrate isotopes, and dissolved gases were compared against similar measurements at the spring outlet to evaluate spatial heterogeneity of denitrification evidence in relation to land surface–aquifer connectivity. Sample locations spanned spatial variation in recharge processes (i.e., diffuse vs. focused recharge) and proximity to sources of denitrification reactants (e.g., wetlands). Although no distinct spatial pattern in denitrification was uncovered, excess dissolved N<sub>2</sub><span>&nbsp;</span>gas measurements were only above detection in the unconfined springshed, with some evidence of a wetland proximity effect. Measured oxidation–reduction potential and dissolved oxygen poorly predicted denitrification, indicating that measured denitrification may be occurring upgradient from sampled wells. Despite dramatic spatial chemical heterogeneity across wells, mean values for recharge nitrate concentrations (0.02 to 5.56&nbsp;mg&nbsp;N&nbsp;L<sup>−1</sup>) and excess N<sub>2</sub><span>&nbsp;</span>from aquifer denitrification (below detection to 1.37&nbsp;mg&nbsp;N&nbsp;L<sup>−1</sup>) corresponded reasonably with mean spring outlet measurements for initial nitrate (0.78 to 1.36&nbsp;mg&nbsp;N&nbsp;L<sup>−1</sup>) and excess N<sub>2</sub><span>&nbsp;</span>(0.15 to 1.04&nbsp;mg&nbsp;N&nbsp;L<sup>−1</sup>). Congruence between groundwater and spring measurements indicates that combining sampling at the spring outlet and across the springshed is useful for understanding spatial aquifer denitrification. However, this approach would be improved with a high‐density sampling network with transects of wells along distinct groundwater flow paths.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13380","usgsCitation":"Henson, W.R., Cohen, M.J., and Graham, W.D., 2019, Spatially distributed denitrification in a karst springshed: Hydrologic Processes, v. 33, no. 8, p. 1191-1203, https://doi.org/10.1002/hyp.13380.","productDescription":"13 p.","startPage":"1191","endPage":"1203","ipdsId":"IP-075617","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":379723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.1884765625,\n              29.36302703778376\n            ],\n            [\n              -81.73828125,\n              29.36302703778376\n            ],\n            [\n              -81.73828125,\n              30.44867367928756\n            ],\n            [\n              -83.1884765625,\n              30.44867367928756\n            ],\n            [\n              -83.1884765625,\n              29.36302703778376\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":802887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Wendy D.","contributorId":196587,"corporation":false,"usgs":false,"family":"Graham","given":"Wendy","email":"","middleInitial":"D.","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":802888,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70202264,"text":"70202264 - 2019 - Physical mechanisms influencing localized patterns of temperature variability and coral bleaching within a system of reef atolls","interactions":[],"lastModifiedDate":"2019-08-15T11:47:49","indexId":"70202264","displayToPublicDate":"2019-02-19T12:28:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Physical mechanisms influencing localized patterns of temperature variability and coral bleaching within a system of reef atolls","docAbstract":"<p><span>Interactions between oceanic and atmospheric processes within coral reefs can significantly alter local-scale (&lt; km) water temperatures, and consequently drive variations in heat stress and bleaching severity. The Scott Reef atoll system was one of many reefs affected by the 2015–2016 mass coral bleaching event across tropical Australia, and specifically experienced sea surface temperature anomalies of 2&nbsp;°C that caused severe mass bleaching (&gt; 60%) over most of this system; however, the bleaching patterns were not uniform. Little is known about the processes governing thermodynamic variability within atolls, particularly those that are dominated by large amplitude tides. Here, we identify three mechanisms at Scott Reef that alleviated heat stress during the marine heatwave in 2016: (1) the cool wake of a tropical cyclone that induced temperature drops of 1.3&nbsp;°C over a period of 8&nbsp;days; (2) air–sea heat fluxes that interacted with the reef morphology during neap tides at one of the atolls to reduce water temperatures by up to 2.9&nbsp;°C; (3) internal tidal processes that forced deeper and cooler water (up to 2.7&nbsp;°C) into some sections of the shallow reefs. The latter two processes created localized areas of reduced temperatures that led to lower incidences of coral bleaching for parts of the reef. We predict these processes are likely to occur in other similar tide-dominated reef environments worldwide. Identifying locations where physical processes reduce heat stress will likely be critical for coral reefs in the future, by maintaining communities that can help facilitate local recovery of reefs following bleaching events that are expected to increase in frequency and severity in the coming decades.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00338-019-01771-2","usgsCitation":"Green, R.H., Lowe, R.J., Buckley, M.L., Lopez, T.M., and Gilmour, J., 2019, Physical mechanisms influencing localized patterns of temperature variability and coral bleaching within a system of reef atolls: Coral Reefs, v. 38, no. 4, p. 759-771, https://doi.org/10.1007/s00338-019-01771-2.","productDescription":"13 p.","startPage":"759","endPage":"771","ipdsId":"IP-099328","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467891,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/81833bb5-4339-4e8c-9d3a-4041d54c8df6","text":"External Repository"},{"id":361342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Scott Reef system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              121.7,\n              -14.3\n            ],\n            [\n              122.3,\n              -14.3\n            ],\n            [\n              122.3,\n              -13.6\n            ],\n            [\n              121.7,\n              -13.6\n            ],\n            [\n              121.7,\n              -14.3\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Rebecca H.","contributorId":208503,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca","email":"","middleInitial":"H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":757549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":757550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopez, Taryn M. 0000-0001-6831-4573","orcid":"https://orcid.org/0000-0001-6831-4573","contributorId":213357,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","email":"","middleInitial":"M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":757551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gilmour, James","contributorId":213358,"corporation":false,"usgs":false,"family":"Gilmour","given":"James","email":"","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":757552,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197676,"text":"sir20185079 - 2019 - Carbon dioxide mineralization feasibility in the United States","interactions":[],"lastModifiedDate":"2019-02-19T14:59:46","indexId":"sir20185079","displayToPublicDate":"2019-02-19T12:15:00","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":"2018-5079","displayTitle":"Carbon Dioxide Mineralization Feasibility in the United States","title":"Carbon dioxide mineralization feasibility in the United States","docAbstract":"<p>Geologic carbon dioxide (CO<sub>2</sub>) storage is one of many methods for stabilizing the increasing concentration of CO<sub>2</sub> in the Earth’s atmosphere. The injection of CO<sub>2</sub> in deep subsurface sedimentary reservoirs is the most commonly discussed method; however, the potential for CO<sub>2</sub> leakage can create long-term stability concerns. This report discusses the feasibility of an alternative form of geologic CO<sub>2</sub> storage: CO<sub>2</sub> mineralization. In this method, CO<sub>2</sub> reacts with rocks and minerals to form solid and stable carbonate rocks. New pilot projects and laboratory-based kinetics experiments have revealed that this method, both in situ and ex situ, may be a viable option for storage. In situ storage targets in-place rocks at the surface or subsurface. Ex situ storage targets industrial byproducts at the surface like mine tailings. Environmental risks include induced seismicity for in situ methods if pressure is not managed properly, as well as potential water and land use effects. However, there are fewer long-term CO<sub>2</sub>-leakage concerns for mineralization methods compared to saline storage methods and therefore potentially lower long-term monitoring costs. The costs and benefits of CO<sub>2</sub> mineralization are compared to those of CO<sub>2</sub> storage in saline reservoirs using estimates of pressure-limited dynamic storage capacity. This report highlights the regional potential of areas in the United States for in situ and ex situ storage, as well as their proximity to potential sources of CO<sub>2</sub>. Especially suitable targets include asbestos or other ultramafic mine tailings, in situ ultramafic rocks on the East and West Coasts, the Columbia River basalts in the Pacific Northwest, the Midcontinent Rift basalts in the midcontinent, and the basaltic Hawaiian Islands.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185079","usgsCitation":"Blondes, M.S., Merrill, M.D., Anderson, S.T., and DeVera, C.A., 2019, Carbon dioxide mineralization feasibility in the United States: U.S. Geological Survey Scientific Investigations Report 2018–5079, 29 p., https://doi.org/10.3133/sir20185079.","productDescription":"viii, 29 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095254","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437568,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D92L53","text":"USGS data 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States\"}}]}","contact":"<p><a href=\"https://energy.usgs.gov/GeneralInfo/AbouttheEnergyProgram.aspx\" data-mce-href=\"https://energy.usgs.gov/GeneralInfo/AbouttheEnergyProgram.aspx\">Energy Resources Program</a><br>12201 Sunrise Valley Drive <br>913 National Center <br>Reston, VA 20192<br>Email: <a href=\"mailto:gd-energyprogram@usgs.gov \" data-mce-href=\"mailto:gd-energyprogram@usgs.gov\">gd-energyprogram@usgs.gov </a></p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgments</li><li>Abstract</li><li>1. Introduction</li><li>2. Reaction Rate Experiments and Models</li><li>3. In Situ Carbon Dioxide Mineralization</li><li>4. Ex Situ Carbon Dioxide Mineralization</li><li>5. Pilot Projects</li><li>6. Possible Environmental Effects</li><li>7. Economic Constraints and Risk</li><li>8. Regional Carbon Dioxide Mineralization Feasibility in the United States</li><li>9. Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-02-19","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":738153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":738154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":738155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVera, Christina A. 0000-0002-4691-6108","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":204979,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":738156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208587,"text":"70208587 - 2019 - Wasting disease and static environmental variables drive sea star assemblages in the northern Gulf of Alaska","interactions":[],"lastModifiedDate":"2020-02-19T12:13:23","indexId":"70208587","displayToPublicDate":"2019-02-19T11:59:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Wasting disease and static environmental variables drive sea star assemblages in the northern Gulf of Alaska","docAbstract":"<p><span>Sea stars are ecologically important in rocky intertidal habitats where they can play an apex predator role, completely restructuring communities. The recent sea star die-off throughout the eastern Pacific, known as Sea Star Wasting Disease, has prompted a need to understand spatial and temporal patterns of sea star assemblages and the environmental variables that structure these assemblages. We examined spatial and temporal patterns in sea star assemblages (composition and density) across regions in the northern Gulf of Alaska and assessed the role of seven static environmental variables (distance to freshwater inputs, tidewater glacial presence, exposure to wave action, fetch, beach slope, substrate composition, and tidal range) in influencing sea star assemblage structure before and after sea star declines. Environmental variables correlated with sea star distribution can serve as proxies to environmental stressors, such as desiccation, attachment, and wave action. Intertidal sea star surveys were conducted annually from 2005 to 2018 at five sites in each of four regions that were between 100 and 420 km apart across the northern Gulf of Alaska. In the pre-disease years, assemblages were different among regions, correlated mostly to tidewater glacier presence, fetch, and tidal range. The assemblages after wasting disease were different from those before the event with lower diversity and lower density. In addition to these declines, the disease manifested itself at different times across the northern Gulf of Alaska and did not impact all species uniformly across sites. Post sea star wasting, there was a shift in the environmental variables that correlated with sea star structure, resulting in sea star assemblages being highly correlated with slope, fetch, and tidal range. In essence, sea star wasting disease resulted in a shift in the sea star assemblage that is now correlating with a slightly different combination of environmental variables. Understanding the delicate interplay of environmental variables that influence sea star assemblages could expand knowledge of the habitat preferences and tolerance ranges of important and relatively unstudied species within the northern Gulf of Alaska.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2019.151209","usgsCitation":"Konar, B., Mitchell, T.J., Iken, K., Dean, T., Esler, D., Lindeberg, M., Pister, B., and Weitzman, B., 2019, Wasting disease and static environmental variables drive sea star assemblages in the northern Gulf of Alaska: Journal of Experimental Marine Biology and Ecology, v. 520, p. 1-10, https://doi.org/10.1016/j.jembe.2019.151209.","productDescription":"151209, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-107631","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Northern Gulf of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.62158203125,\n              57.28498092462365\n            ],\n            [\n              -145.535888671875,\n              57.28498092462365\n            ],\n            [\n              -145.535888671875,\n              61.554109444927185\n            ],\n            [\n              -154.62158203125,\n              61.554109444927185\n            ],\n            [\n              -154.62158203125,\n              57.28498092462365\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"520","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Konar, Brenda","contributorId":131034,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":782618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Timothy J.","contributorId":222573,"corporation":false,"usgs":false,"family":"Mitchell","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":782619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iken, K.","contributorId":178282,"corporation":false,"usgs":false,"family":"Iken","given":"K.","affiliations":[],"preferred":false,"id":782620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dean, Thomas","contributorId":140481,"corporation":false,"usgs":false,"family":"Dean","given":"Thomas","affiliations":[{"id":13512,"text":"Coastal Resources Inc., Carlsbad, CA","active":true,"usgs":false}],"preferred":false,"id":782621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":true,"id":782622,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindeberg, Mandy","contributorId":195895,"corporation":false,"usgs":false,"family":"Lindeberg","given":"Mandy","email":"","affiliations":[],"preferred":false,"id":782623,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pister, Benjamin","contributorId":219669,"corporation":false,"usgs":false,"family":"Pister","given":"Benjamin","email":"","affiliations":[{"id":40046,"text":"Ocean Alaska Science and Learning Center, National Park Service","active":true,"usgs":false}],"preferred":false,"id":782624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":782625,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70202237,"text":"70202237 - 2019 - Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","interactions":[],"lastModifiedDate":"2019-02-19T11:45:14","indexId":"70202237","displayToPublicDate":"2019-02-19T11:45:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests","docAbstract":"<p><span>In order to produce useful hydrologic and aquatic habitat data from the Landsat system, the U.S. Geological Survey has developed the “Dynamic Surface Water Extent” (DSWE) Landsat Science Product. DSWE will provide long-term, high-temporal resolution data on variations in inundation extent. The model used to generate DSWE is composed of five decision-rule based tests that do not require scene-based training. To allow its general application, required inputs are limited to the Landsat at-surface reflectance product and a digital elevation model. Unlike other Landsat-based water products, DSWE includes pixels that are only partially covered by water to increase inundation dynamics information content. Previously published DSWE model development included one wetland-focused test developed through visual inspection of field-collected Everglades spectra. A comparison of that test’s output against Everglades Depth Estimation Network (EDEN) in situ data confirmed the expectation that omission errors were a prime source of inaccuracy in vegetated environments. Further evaluation exposed a tendency toward commission error in coniferous forests. Improvements to the subpixel level “partial surface water” (PSW) component of DSWE was the focus of this research. Spectral mixture models were created from a variety of laboratory and image-derived endmembers. Based on the mixture modeling, a more “aggressive” PSW rule improved accuracy in herbaceous wetlands and reduced errors of commission elsewhere, while a second “conservative” test provides an alternative when commission errors must be minimized. Replication of the EDEN-based experiments using the revised PSW tests yielded a statistically significant increase in mean overall agreement (4%, p = 0.01, n = 50) and a statistically significant decrease (11%, p = 0.009, n = 50) in mean errors of omission. Because the developed spectral mixture models included image-derived vegetation endmembers and laboratory spectra for soil groups found across the US, simulations suggest where the revised DSWE PSW tests perform as they do in the Everglades and where they may prove problematic. Visual comparison of DSWE outputs with an unusual variety of coincidently collected images for locations spread throughout the US support conclusions drawn from Everglades quantitative analyses and highlight DSWE PSW component strengths and weaknesses.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs11040374","usgsCitation":"Jones, J., 2019, Improved automated detection of subpixel-scale inundation – Revised Dynamic Surface Water Extent (DSWE) partial surface water tests: Remote Sensing, v. 11, no. 4, p. 1-26, https://doi.org/10.3390/rs11040374.","productDescription":"Article 374; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-102379","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11040374","text":"Publisher Index Page"},{"id":361339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":757437,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208585,"text":"70208585 - 2019 - Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska","interactions":[],"lastModifiedDate":"2020-02-19T11:53:13","indexId":"70208585","displayToPublicDate":"2019-02-19T11:44:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska","docAbstract":"<p><span>Many marine organisms show significant levels of genetic heterogeneity on local spatial scales despite exhibiting limited genetic structure at large geographic scales which can be produced through a variety of mechanisms. The Arctic cod (</span><i>Boreogadus saida</i><span>) is a circumpolar species and is a vital species in Arctic food webs. To examine population genetic structure of Arctic cod at macro- and micro-geographic scales, we characterized variation at mitochondrial DNA (mtDNA) and microsatellite loci among Arctic cod located in the Chukchi and Beaufort seas in Alaska. We found two distinct mtDNA haplotype clusters, although there was no underlying geographic pattern (</span><i>F</i><sub>ST</sub><span>&nbsp;= −0.001). Congruent with this finding, microsatellite loci suggested a panmictic population (</span><i>F</i><sub>ST</sub><span>&nbsp;= 0.001) across northern Alaskan marine waters at a large spatial scale. However, we found slight but significant micro-geographic partitioning of genetic variation in the southern shelf of the Beaufort Sea that appeared to be associated with the western reaches of the Mackenzie River plume. This fine-scale spatial pattern was not associated with kin-associated groups, suggesting larvae cohorts are not remaining together throughout development. We hypothesize that this pattern reflects the intermixing of Pacific and Arctic origin lineages of Arctic cod.</span></p>","language":"English","publisher":"Oxford Uni. Press","doi":"10.1093/icesjms/fsz041","usgsCitation":"Wilson, R.E., Sage, G.K., Wedemeyer, K., Sonsthagen, S.A., Menning, D.M., Gravley, M.C., Nelson, R.J., and Talbot, S.L., 2019, Micro-geographic population genetic structure within Arctic cod (Boreogadus saida) in Beaufort Sea of Alaska: ICES Journal of Marine Science, v. 76, no. 6, p. 1713-1721, https://doi.org/10.1093/icesjms/fsz041.","productDescription":"9 p.","startPage":"1713","endPage":"1721","ipdsId":"IP-102019","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beafort Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -166.728515625,\n              68.95839084822076\n            ],\n            [\n              -141.416015625,\n              69.2249968541159\n            ],\n            [\n              -141.416015625,\n              73.94679115710252\n            ],\n            [\n              -168.8818359375,\n              73.87371654457475\n            ],\n            [\n              -169.716796875,\n              66.9816661111497\n            ],\n            [\n              -165.8056640625,\n              67.08455048507471\n            ],\n            [\n              -166.4208984375,\n              67.82583637985663\n            ],\n            [\n              -166.728515625,\n              68.95839084822076\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":782604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":782605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wedemeyer, Kate","contributorId":207047,"corporation":false,"usgs":false,"family":"Wedemeyer","given":"Kate","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":782606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782609,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, R. John","contributorId":98215,"corporation":false,"usgs":true,"family":"Nelson","given":"R.","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":782610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":782611,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70202260,"text":"70202260 - 2019 - Estimating uncertainty of North American landbird population sizes","interactions":[],"lastModifiedDate":"2019-02-19T11:38:08","indexId":"70202260","displayToPublicDate":"2019-02-19T11:38:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating uncertainty of North American landbird population sizes","docAbstract":"<p><span>An important metric for many aspects of species conservation planning and risk assessment is an estimate of total population size. For landbirds breeding in North America, Partners in Flight (PIF) generates global, continental, and regional population size estimates. These estimates are an important component of the PIF species assessment process, but have also been used by others for a range of applications. The PIF population size estimates are primarily calculated using a formula designed to extrapolate bird counts recorded by the North American Breeding Bird Survey (BBS) to regional population estimates. The extrapolation formula includes multiple assumptions and sources of uncertainty, but there were previously no attempts to quantify this uncertainty in the published population size estimates aside from a categorical data quality score. Using a Monte Carlo approach, we propagated the main sources of uncertainty arising from individual components of the model through to the final estimation of landbird population sizes. This approach results in distributions of population size estimates rather than point estimates. We found the width of uncertainty of population size estimates to be generally narrower than the order-of-magnitude distances between the population size score categories PIF uses in the species assessment process, suggesting confidence in the categorical ranking used by PIF. Our approach provides a means to identify species whose uncertainty bounds span more than one categorical rank, which was not previously possible with the data quality scores. Although there is still room for additional improvements to the estimation of avian population sizes and uncertainty, particularly with respect to replacing categorical model components with empirical estimates, our estimates of population size distributions have broader utility to a range of conservation planning and risk assessment activities relying on avian population size estimates.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.5751/ACE-01331-140104","usgsCitation":"Stanton, J.C., Blancher, P.J., Rosenberg, K.V., Panjabi, A.O., and Thogmartin, W.E., 2019, Estimating uncertainty of North American landbird population sizes: Avian Conservation and Ecology, v. 14, no. 1, Article 4; 16 p., https://doi.org/10.5751/ACE-01331-140104.","productDescription":"Article 4; 16 p.","ipdsId":"IP-090781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467893,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01331-140104","text":"Publisher Index Page"},{"id":437569,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90SWVFU","text":"USGS data release","linkHelpText":"Population Size uncertainty estimates"},{"id":361335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":757537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":757538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":757539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70200151,"text":"sir20185125 - 2019 - Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","interactions":[],"lastModifiedDate":"2019-02-19T14:54:42","indexId":"sir20185125","displayToPublicDate":"2019-02-19T11:28:48","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":"2018-5125","displayTitle":"Potential for Increased Inundation in Flood-Prone Regions of Southeast Florida in Response to Climate and Sea-Level Changes in Broward County, Florida, 2060–69","title":"Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69","docAbstract":"<p>The U.S. Geological Survey, in cooperation with Broward County Environmental Planning and Resilience Division, has developed county-scale and local-scale groundwater/surface-water models to study the potential for increased inundation and flooding in eastern Broward County that are due to changes in future climate and sea-level rise. These models were constructed by using MODFLOW 2005, with the surface-water system represented by using the Surface-Water Routing process and a new Urban Runoff process. The local-scale model allowed the use of finer grid resolution in a selected area of the county, whereas the county-scale model provided boundary conditions for the local-scale model and insight into the hydrologic behavior of the larger system. The aquifer layering, properties, and boundaries relied heavily on a previous three-dimensional variable-density solute-transport model of the same area developed by the U.S. Geological Survey. The surface-water system within these new models actively simulates a part of the extensive canal network by using level-pool routing and active structure operations within the Surface-Water Routing process. These models were used to simulate a historical base-case period (1990–99) by using measured data and regional climate model rainfall and potential evapotranspiration output. The simulated flow and water-level results generally captured the behavior of the hydrologic system. A future period (2060–69) was simulated by using regional climate model rainfall and potential evapotranspiration output representing a wetter and drier future and low, intermediate, and high sea-level rise projections. The results were used to evaluate the potential effects on the surface-water drainage system, coastal-structure operation, and wet-season groundwater levels.</p><p>Future period simulations using the county-scale model indicate that (1) the effects of the changing climate and sea level are much more evident in eastern and coastal areas of Broward County compared to western areas, with increases in groundwater level nearly equivalent to sea-level rise; (2) coastal groundwater-level increases are distributed farther inland in the wetter future scenarios than in the drier future scenarios; (3) water levels at the westernmost groundwater station locations exhibited little change caused by sea-level rise and showed more dependence on changes in precipitation; (4) there was a reduced west-to-east groundwater gradient with increasing sea-level rise; and (5) increased downstream tidal stage at the S–13 structure resulted in increased reliance on the pump to control upstream inland canal stages. Future simulations using the local-scale model indicate similar behavior as seen in the county-scale model: (1) the coastal areas exhibited the largest impacts in groundwater levels in the future scenarios; (2) the westernmost, interior areas exhibited little change during the future scenarios; and (3) there was an increased reliance on the pump at the S–13 coastal structure but to a lesser extent than indicated in the county-scale model because of the reduced temporal scale of the local-scale model.</p><p>Possible adaptation and mitigation strategies were simulated to evaluate the county-scale and local-scale models’ ability to simulate hydrologic changes. Alterations to S–13 pump operations within the county-scale model were tested, and results indicate a reduced effect of sea-level rise inland of the control structure, but the affected area is spatially limited. The concept of using pumps to reduce the local groundwater levels in two neighborhood-sized areas was tested by using the local-scale model. The MODFLOW 2005 Drain package was used to remove groundwater by using drainage elevations set to zero, 1 foot, and 2 feet above average wet-season groundwater levels. Area 1 was well connected to coastal boundaries, and a high rate of groundwater removal was required, whereas the rate of groundwater removal required was greatly reduced in Area 2, which is less connected to tidal boundaries. Water for these scenarios was assumed to be pumped to tide with no downstream effects.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185125","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Resilience Division","usgsCitation":"Decker, J.D., Hughes, J.D., and Swain, E.D., 2019, Potential for increased inundation in flood-prone regions of southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69: U.S. Geological Survey Scientific Investigations Report 2018–5125, 106 p., https://doi.org/10.3133/sir20185125.","productDescription":"Report: viii, 106 p.; Data Release","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-066244","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":361163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5125/sir20185125.pdf","text":"Report","size":"10.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5125"},{"id":361162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5125/coverthb.jpg"},{"id":361164,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E6INWZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW 2005 data sets for the simulation of potential increased inundation in flood-prone regions of Southeast Florida in response to climate and sea-level changes in Broward County, Florida, 2060–69"}],"country":"United States","state":"Florida","county":"Broward County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.44326782226562,\n              25.95557515483912\n            ],\n            [\n              -80.07522583007812,\n              25.95557515483912\n            ],\n            [\n              -80.07522583007812,\n              26.331576128197028\n            ],\n            [\n              -80.44326782226562,\n              26.331576128197028\n            ],\n            [\n              -80.44326782226562,\n              25.95557515483912\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey <br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Simulation of the Hydrologic System for Historical Conditions During 1990–99</li><li>Effects of Climate Changes and Sea-Level Rise on Groundwater Levels, Canal Stages, and Flows at Coastal Structures</li><li>Simulation of Hypothetical Mitigation Strategies</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Simulated Groundwater Response to Individual Precipitation Events</li><li>Appendix 2. Numerical Model Construction</li><li>Appendix 3. Sensitivity Testing of Numerical Models</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-02-19","noUsgsAuthors":false,"publicationDate":"2019-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Decker, Jeremy D. 0000-0002-0700-515X","orcid":"https://orcid.org/0000-0002-0700-515X","contributorId":202857,"corporation":false,"usgs":true,"family":"Decker","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":748294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748295,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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