{"pageNumber":"794","pageRowStart":"19825","pageSize":"25","recordCount":165485,"records":[{"id":70200007,"text":"70200007 - 2018 - Geology of San Francisco","interactions":[],"lastModifiedDate":"2018-10-17T13:43:32","indexId":"70200007","displayToPublicDate":"2018-10-01T13:43:27","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology of San Francisco","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geology of San Francisco, United States of America; Geology of the cities of the World series","language":"English","publisher":"Association of Environmental & Engineering Geologists","usgsCitation":"Graymer, R.W., Givler, R., Baldwin, J., Lettis, W., Johnson, S., Greene, H., and Dartnell, P., 2018, Geology of San Francisco, chap. <i>of</i> Geology of San Francisco, United States of America; Geology of the cities of the World series, p. 41-60.","productDescription":"20 p.","startPage":"41","endPage":"60","ipdsId":"IP-098424","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":358488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358244,"type":{"id":15,"text":"Index Page"},"url":"https://www.aegweb.org/page/GeologyCities"}],"country":"United States","state":"California","otherGeospatial":"San Francisco","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a931e4b034bf6a7e5080","contributors":{"authors":[{"text":"Graymer, Russell W. 0000-0003-4910-5682 rgraymer@usgs.gov","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":1052,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","email":"rgraymer@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":748865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Givler, Robert","contributorId":209817,"corporation":false,"usgs":false,"family":"Givler","given":"Robert","email":"","affiliations":[],"preferred":false,"id":748866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, John","contributorId":209818,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","affiliations":[],"preferred":false,"id":748867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lettis, William","contributorId":61605,"corporation":false,"usgs":true,"family":"Lettis","given":"William","email":"","affiliations":[],"preferred":false,"id":748868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Samuel","contributorId":206420,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":748870,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":78669,"corporation":false,"usgs":true,"family":"Greene","given":"H. Gary","affiliations":[],"preferred":false,"id":748871,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":748872,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70201571,"text":"70201571 - 2018 - Are hatchery-reared Rainbow Trout and Brown Trout effective predators on juvenile native fish?","interactions":[],"lastModifiedDate":"2018-12-18T13:42:04","indexId":"70201571","displayToPublicDate":"2018-10-01T13:42:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Are hatchery-reared Rainbow Trout and Brown Trout effective predators on juvenile native fish?","docAbstract":"<p><span>Hatchery‐reared Rainbow Trout&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;and Brown Trout&nbsp;</span><i>Salmo trutta</i><span>&nbsp;are typically fed exclusively on commercially prepared pelleted feeds and have no experience catching or consuming live fish at the time of stocking. Despite this lack of predation experience, it is commonly assumed that stocked Rainbow Trout and Brown Trout will adversely impact native fish populations by preying upon juvenile native fish. We evaluated the relative predation effectiveness of wild‐caught Rainbow Trout (210–389&nbsp;mm TL) and Brown Trout (185–313&nbsp;mm TL) compared with hatchery‐reared Rainbow Trout (198–321&nbsp;mm TL) and Brown Trout (196–290&nbsp;mm TL). We used Bonytail&nbsp;</span><i>Gila elegans</i><span>(60–85&nbsp;mm TL), Humpback Chub&nbsp;</span><i>Gila cypha</i><span>&nbsp;(24–59&nbsp;mm TL), and Roundtail Chub&nbsp;</span><i>Gila robusta</i><span>&nbsp;(40–65&nbsp;mm TL) as prey in overnight predation trials conducted in the laboratory from 2013 to 2016. After 14 d in a captive setting, wild Rainbow Trout and Brown Trout consumed &gt;70% of prey in trials with no cover, while hatchery‐reared fish consumed &lt;30% of prey. In addition, we evaluated if the predation ability of hatchery fish would improve over time by feeding them Fathead Minnows&nbsp;</span><i>Pimephales promelas</i><span>, rather than pelleted feed, for up to 30&nbsp;d. Predation success of Rainbow Trout and Brown Trout increased by an average of 28% and 21%, respectively, after 14&nbsp;d of eating exclusively fish. Rainbow Trout tested after 30&nbsp;d of eating fish increased in their ability to catch and eat small prey by an average of 29%. The predation effectiveness of hatchery‐reared fish appears to improve with experience eating live fish. Although stocking Rainbow Trout and Brown Trout does increase the number of predators present in natural systems, the relative predation threat posed by hatchery‐reared fish may be less than that of wild fish, especially in locations where stocked fish do not persist. Lack of experience in catching fish and the effects of captive rearing practices and environments on both physiology and behavior all likely contribute to reduced predation effectiveness of hatchery Rainbow Trout and Brown Trout.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10216","usgsCitation":"Ward, D.L., Morton-Starner, R., and Vaage, B., 2018, Are hatchery-reared Rainbow Trout and Brown Trout effective predators on juvenile native fish?: North American Journal of Fisheries Management, v. 38, no. 5, p. 1105-1113, https://doi.org/10.1002/nafm.10216.","productDescription":"9 p.","startPage":"1105","endPage":"1113","ipdsId":"IP-089894","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437728,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RLNCAE","text":"USGS data release","linkHelpText":"Hatchery Trout Predation Data, Arizona"},{"id":360476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-14","publicationStatus":"PW","scienceBaseUri":"5c1a1533e4b0708288c2352f","contributors":{"authors":[{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morton-Starner, Rylan rmorton-starner@usgs.gov","contributorId":5256,"corporation":false,"usgs":true,"family":"Morton-Starner","given":"Rylan","email":"rmorton-starner@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vaage, Benjamin 0000-0003-1730-4302 bvaage@usgs.gov","orcid":"https://orcid.org/0000-0003-1730-4302","contributorId":211598,"corporation":false,"usgs":true,"family":"Vaage","given":"Benjamin","email":"bvaage@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754461,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70200509,"text":"70200509 - 2018 - Interactions and impacts of domesticated animals on cranes in agriculture","interactions":[],"lastModifiedDate":"2018-10-24T10:35:29","indexId":"70200509","displayToPublicDate":"2018-10-01T13:39:41","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Interactions and impacts of domesticated animals on cranes in agriculture","docAbstract":"<p>Affiliations of most cranes to humans and agriculture means they often interact with a variety of domestic animals. Those interactions can be beneficial or neutral when domestic animal densities and their impact on wetland or grassland systems are low to moderate, as found in more traditional agricultural practices. The most common interaction is with grazers, primarily domestic ungulates such as cattle, horses, and sheep. Cranes can benefit from the rapid recycling of grassland nutrients, maintenance of open areas, and invertebrate foods that grazers facilitate. Examples of the close interactions among cranes and grazers are found in South Africa, Central Eurasia, China, India, and North America. Overgrazing and direct disturbances from domestic livestock are usually detrimental to cranes and interact with other factors such as altered wetland hydrology, fire, and changing climate. Cranes are most likely to interact with domestic birds in wetlands (ducks and geese) or farm areas (poultry) where they are attracted to areas where the domestic birds are being fed and maintained in large open areas. Risks of disease transmission between domestic birds and cranes are the greatest concern. Dogs associated with humans and agricultural activities are generally a threat where cranes are raising their chicks nearby.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Cranes and agriculture: A global guide for sharing the landscape","language":"English","publisher":"International Crane Foundation","usgsCitation":"Austin, J.E., Momose, K., and Archibald, G.W., 2018, Interactions and impacts of domesticated animals on cranes in agriculture, chap. <i>of</i> Cranes and agriculture: A global guide for sharing the landscape, p. 72-82.","productDescription":"11 p.","startPage":"72","endPage":"82","ipdsId":"IP-059709","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":358676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358627,"type":{"id":15,"text":"Index Page"},"url":"https://www.savingcranes.org/education/library/books/"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a931e4b034bf6a7e5085","contributors":{"authors":[{"text":"Austin, Jane E. 0000-0001-8775-2210 jaustin@usgs.gov","orcid":"https://orcid.org/0000-0001-8775-2210","contributorId":146411,"corporation":false,"usgs":true,"family":"Austin","given":"Jane","email":"jaustin@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":749200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Momose, Kunikazu","contributorId":209955,"corporation":false,"usgs":false,"family":"Momose","given":"Kunikazu","email":"","affiliations":[{"id":38035,"text":"Tancho Protection Group, NPO, Kushiro, Japan","active":true,"usgs":false}],"preferred":false,"id":749201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archibald, George W.","contributorId":73705,"corporation":false,"usgs":false,"family":"Archibald","given":"George","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":749202,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70201693,"text":"70201693 - 2018 - A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform","interactions":[],"lastModifiedDate":"2018-12-21T13:38:22","indexId":"70201693","displayToPublicDate":"2018-10-01T13:38:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform","docAbstract":"<p><span>Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands&nbsp;</span><i>versus</i><span>&nbsp;non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R</span><sup>2</sup><span>&nbsp;value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at&nbsp;</span><a rel=\"noreferrer noopener\" href=\"http://www.croplands.org/\" target=\"_blank\" data-mce-href=\"http://www.croplands.org/\">www.croplands.org</a><span>&nbsp;and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC)&nbsp;</span><a rel=\"noreferrer noopener\" href=\"https://www.lpdaac.usgs.gov/node/1282\" target=\"_blank\" data-mce-href=\"https://www.lpdaac.usgs.gov/node/1282\">https://www.lpdaac.usgs.gov/node/1282</a><span>.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2018.07.017","usgsCitation":"Teluguntla, P., Thenkabail, P.S., Oliphant, A., Xiong, J., Gumma, M.K., Congalton, R.G., Yadav, K., and Huete, A., 2018, A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform: ISPRS Journal of Photogrammetry and Remote Sensing, v. 144, p. 325-340, 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,{"id":70202303,"text":"70202303 - 2018 - President's address for Wetland Science and Practice - October 2018","interactions":[],"lastModifiedDate":"2019-02-21T13:12:00","indexId":"70202303","displayToPublicDate":"2018-10-01T13:11:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5164,"text":"Wetland Science & Practice","active":true,"publicationSubtype":{"id":10}},"title":"President's address for Wetland Science and Practice - October 2018","docAbstract":"<p>As 2018 moves into its last quarter, those of us in the southern U.S. check the skies for hurricanes, academics and students return to the classroom, and researchers wrap up the last of their year’s field work. For SWS, the last quarter brings new ways to promote internationalization...</p>","language":"English","publisher":"Society of Wetland Scientists","usgsCitation":"Middleton, B.A., 2018, President's address for Wetland Science and Practice - October 2018: Wetland Science & Practice, p. 309-309.","productDescription":"1 p.","startPage":"309","endPage":"309","ipdsId":"IP-101288","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":361411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361405,"type":{"id":15,"text":"Index Page"},"url":"https://www.sws.org/category/20.html"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757715,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70202221,"text":"70202221 - 2018 - Salt marsh loss affects tides and sediment budget in shallow bays","interactions":[],"lastModifiedDate":"2019-02-15T12:46:00","indexId":"70202221","displayToPublicDate":"2018-10-01T12:45:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Salt marsh loss affects tides and sediment budget in shallow bays","docAbstract":"<p><span>The current paradigm is that salt marshes and their important ecosystem services are threatened by global climate change; indeed, large marsh losses have been documented worldwide. Morphological changes associated with salt marsh erosion are expected to influence the hydrodynamics and sediment dynamics of coastal systems. Here the influence of salt marsh erosion on the tidal hydrodynamics and sediment storage capability of shallow bays is investigated. Hydrodynamics, sediment transport, and vegetation dynamics are simulated using the numerical framework Coupled Ocean‐Atmosphere‐Wave‐Sediment Transport in the Barnegat Bay‐Little Egg Harbor system, USA. We show that salt marsh erosion influences the propagation of tides into back‐barrier basins, reducing the periodic inundation and sediment delivery to marsh platforms. As salt marshes erode, the sediment trapping potential of marsh platforms decreases exponentially. In this test case, up to 50% of the sediment mass trapped by vegetation is lost once a quarter of the marsh area is eroded. Similarly, without salt marshes the sediment budget of the entire bay significantly declines. Therefore, a positive feedback might be triggered such that as the salt marsh retreats the sediment storage capacity of the system declines, which could in turn further exacerbate marsh degradation.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2018JF004617","usgsCitation":"Donatelli, C., Ganju, N., Zhang, X., Fagherazzi, S., and Leonardi, N., 2018, Salt marsh loss affects tides and sediment budget in shallow bays: Journal of Geophysical Research F: Earth Surface, v. 123, no. 10, p. 2647-2662, https://doi.org/10.1029/2018JF004617.","productDescription":"16 p.","startPage":"2647","endPage":"2662","ipdsId":"IP-091535","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468350,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2018jf004617","text":"External Repository"},{"id":361287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay-Little Egg Harbor system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.5,\n              39.4\n            ],\n            [\n              -74,\n              39.4\n            ],\n            [\n              -74,\n              40.1\n            ],\n            [\n              -74.5,\n              40.1\n            ],\n            [\n              -74.5,\n              39.4\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"123","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Donatelli, Carmine","contributorId":205614,"corporation":false,"usgs":false,"family":"Donatelli","given":"Carmine","email":"","affiliations":[{"id":37127,"text":"University of Liverpool, Liverpool UK","active":true,"usgs":false}],"preferred":false,"id":757311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Xiaohe","contributorId":213308,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaohe","email":"","affiliations":[],"preferred":false,"id":757312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagherazzi, Sergio","contributorId":89282,"corporation":false,"usgs":true,"family":"Fagherazzi","given":"Sergio","affiliations":[],"preferred":false,"id":757313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonardi, Nicoletta","contributorId":202868,"corporation":false,"usgs":false,"family":"Leonardi","given":"Nicoletta","email":"","affiliations":[{"id":36541,"text":"University of Liverpool, Department of Geography and Planning, 74 Bedford St S.","active":true,"usgs":false}],"preferred":false,"id":757314,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70197909,"text":"70197909 - 2018 - Puerto Rico and the U.S. Virgin Islands","interactions":[],"lastModifiedDate":"2018-11-19T11:54:18","indexId":"70197909","displayToPublicDate":"2018-10-01T11:54:11","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5780,"text":"NOAA  State Climate Summaries","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"149-PR","title":"Puerto Rico and the U.S. Virgin Islands","docAbstract":"<p>Average annual temperature for Puerto Rico and the U.S. Virgin Islands has increased by more than 1.5°F since 1950. Under a higher emissions pathway, historically unprecedented warming is projected by the end of the 21st century, including increases in extreme heat events. </p><p>Future changes in total precipitation are uncertain, but extreme precipitation is projected to increase, with associated increases in the intensity and frequency of flooding. </p><p>Sea level has risen by 0.6 inches per decade at San Juan, Puerto Rico since 1961, near the global sea level rise rate during the second half of the 20th century. Global sea level rise projections range from 1 to 8 feet by 2100, with similar rises projected for Puerto Rico and the U.S. Virgin Islands. Rising sea levels pose widespread and continuing threats to both natural and built environments in coastal communities. </p><p>Hurricanes are a major threat to both Puerto Rico and the U.S. Virgin Islands. Hurricane rainfall rates, storm surge heights due to sea level rise, and the number of the strongest (Category 3, 4, and 5) hurricanes are all projected to increase in a warming climate.</p>","language":"English","publisher":"NOAA","usgsCitation":"Runkle, J., Kunkel, K.E., Stevens, L.E., Champion, S., Easterling, D., Terando, A., Sun, L., Stewart, B.C., and Landers, G., 2018, Puerto Rico and the U.S. Virgin Islands: NOAA  State Climate Summaries 149-PR, 5 p.","productDescription":"5 p.","ipdsId":"IP-098723","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":359549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":355350,"type":{"id":15,"text":"Index Page"},"url":"https://statesummaries.ncics.org/sites/default/files/downloads/PR-screen-hi.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bf3d9f3e4b045bfcae0c9b9","contributors":{"editors":[{"text":"Champion, Sarah 0000-0002-5080-6286","orcid":"https://orcid.org/0000-0002-5080-6286","contributorId":205982,"corporation":false,"usgs":false,"family":"Champion","given":"Sarah","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":739030,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Easterling, David","contributorId":205983,"corporation":false,"usgs":false,"family":"Easterling","given":"David","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":739031,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":739029,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Sun, Liqiang","contributorId":205984,"corporation":false,"usgs":false,"family":"Sun","given":"Liqiang","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":739032,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Stewart, Brooke C.","contributorId":195288,"corporation":false,"usgs":false,"family":"Stewart","given":"Brooke","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":739033,"contributorType":{"id":2,"text":"Editors"},"rank":8},{"text":"Landers, Glenn","contributorId":205985,"corporation":false,"usgs":false,"family":"Landers","given":"Glenn","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":739034,"contributorType":{"id":2,"text":"Editors"},"rank":9}],"authors":[{"text":"Runkle, Jennifer 0000-0003-4611-1745","orcid":"https://orcid.org/0000-0003-4611-1745","contributorId":205980,"corporation":false,"usgs":false,"family":"Runkle","given":"Jennifer","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":739026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kunkel, Kenneth E.","contributorId":147887,"corporation":false,"usgs":false,"family":"Kunkel","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":739027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Laura E. 0000-0002-8842-702X","orcid":"https://orcid.org/0000-0002-8842-702X","contributorId":205981,"corporation":false,"usgs":false,"family":"Stevens","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":739028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champion, Sarah 0000-0002-5080-6286","orcid":"https://orcid.org/0000-0002-5080-6286","contributorId":205982,"corporation":false,"usgs":false,"family":"Champion","given":"Sarah","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":751481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Easterling, David","contributorId":205983,"corporation":false,"usgs":false,"family":"Easterling","given":"David","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":751482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terando, Adam 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":197511,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":751483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sun, Liqiang","contributorId":205984,"corporation":false,"usgs":false,"family":"Sun","given":"Liqiang","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":751484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stewart, Brooke C.","contributorId":195288,"corporation":false,"usgs":false,"family":"Stewart","given":"Brooke","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":751485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Landers, Glenn","contributorId":205985,"corporation":false,"usgs":false,"family":"Landers","given":"Glenn","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":751486,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70201601,"text":"70201601 - 2018 - Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to Honnedaga Lake, NY","interactions":[],"lastModifiedDate":"2018-12-20T11:50:18","indexId":"70201601","displayToPublicDate":"2018-10-01T11:50:12","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5792,"text":"Summary Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"18-18","title":"Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to Honnedaga Lake, NY","docAbstract":"Liming techniques are being explored in many regions as a means to accelerate the recovery of aquatic biota from decades of acid deposition. The preservation or restoration of native sportfish populations has usually been the impetus for liming programs, and as such, less attention has been paid to its effects on other biological assemblages such as macroinvertebrates. In 2012, a program was initiated using in-stream and aerial (whole-watershed) liming to improve water quality and Brook Trout (Salvelinus fontinalis) recruitment in three acidified tributaries of a high-elevation lake in New York State. Concurrently, macroinvertebrates were sampled annually between 2013 and 2016 at 3 treated sites and 3 untreated reference sites to assess the effects of each liming technique on this community. Despite improvements in water chemistry in all three limed streams, our results generally suggest that neither liming technique improved the condition of macroinvertebrate communities. The watershed application caused an immediate and unsustained decrease in the density of macroinvertebrates driven largely by a one-year reduction of the acid-tolerant Leuctra stoneflies. The in-stream applications appeared to reduce the density of macroinvertebrates, particularly in one stream where undissolved lime covered the natural substrate. The inability of either liming technique to improve the condition of macroinvertebrate communities may be partly explained by the persistence of acidic episodes in all three streams. This suggests that in order to be effective, liming programs should strive to eliminate even temporary episodes of unsuitable water chemistry.","language":"English","publisher":"NYSERDA","usgsCitation":"Lampman, G., George, S.D., Baldigo, B.P., Lawrence, G.B., and Fuller, R.L., 2018, Effects of watershed and in-stream liming on macroinvertebrate communities in acidified tributaries to Honnedaga Lake, NY: Summary Report 18-18, v, 21 p.","productDescription":"v, 21 p.","ipdsId":"IP-087452","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":360624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360440,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports#eco"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.8667,\n              43.5\n            ],\n            [\n              -74.7833,\n              43.5\n            ],\n            [\n              -74.7833,\n              43.55\n            ],\n            [\n              -74.8667,\n              43.55\n            ],\n            [\n              -74.8667,\n              43.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1cb860e4b0708288c83830","contributors":{"authors":[{"text":"Lampman, Gregory","contributorId":211768,"corporation":false,"usgs":false,"family":"Lampman","given":"Gregory","affiliations":[],"preferred":false,"id":754808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Randall L.","contributorId":196969,"corporation":false,"usgs":false,"family":"Fuller","given":"Randall","email":"","middleInitial":"L.","affiliations":[{"id":35994,"text":"Colgate University, Hamilton, NY","active":true,"usgs":false}],"preferred":false,"id":754476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201827,"text":"70201827 - 2018 - What makes a first‐magnitude spring?: Global sensitivity analysis of a speleogenesis model to gain insight into karst network and spring genesis","interactions":[],"lastModifiedDate":"2019-01-31T11:39:35","indexId":"70201827","displayToPublicDate":"2018-10-01T11:39:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"What makes a first‐magnitude spring?: Global sensitivity analysis of a speleogenesis model to gain insight into karst network and spring genesis","docAbstract":"<p><span>Often, karstic conduit network geometry is unknown. This lack of knowledge represents a significant limitation when modeling flow and solute transport in karst systems. In this study, we apply Morris Method Global Sensitivity Analysis to a speleogenesis model to identify model input parameters, and combinations thereof, that most significantly influence evolution of karst conduit networks, development of first‐magnitude springs, and resulting flow and solute transport pulse responses. Based on an idealized model of the Silver Springshed in Central Florida USA, results showed that porous matrix hydraulic conductivity and parameters that govern connectivity of vertical and horizontal preferential flow paths (proto‐conduits) are the most influential parameters. In particular, a lower porous matrix conductivity is more likely to produce a first‐order magnitude spring. For the boundary conditions assumed in this application, conduits tend to develop in low topographic regions that drained nearby high regions. Morris ensemble realizations that generated first‐magnitude springs exhibit similar flow and solute transport pulse responses at the spring vent, despite differences in network configuration. However, distributed head fields are highly spatially variable, implying substantial spatial variability among solute flow paths and travel times from the land surface to the spring across realizations.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2017WR021950","usgsCitation":"Henson, W.R., de Rooij, R., and Graham, W.D., 2018, What makes a first‐magnitude spring?: Global sensitivity analysis of a speleogenesis model to gain insight into karst network and spring genesis: Water Resources Research, v. 54, no. 10, p. 7417-7434, https://doi.org/10.1029/2017WR021950.","productDescription":"18 p.","startPage":"7417","endPage":"7434","ipdsId":"IP-087767","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437729,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S9FMOU","text":"USGS data release","linkHelpText":"Model Data Set and Executables Supporting the Journal Publication for \"What Makes a First-Magnitude Spring?--Global Uncertainty Analysis of a Speleogenesis Model to Gain Insight into Karst Spring Genesis\""},{"id":360862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-08","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":755497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Rooij, Rob","contributorId":212029,"corporation":false,"usgs":false,"family":"de Rooij","given":"Rob","email":"","affiliations":[{"id":38390,"text":"University of Florida Water Institute","active":true,"usgs":false}],"preferred":false,"id":755498,"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":755499,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70199911,"text":"70199911 - 2018 - Preliminary evaluation of behavioral response of nesting waterbirds to small unmanned aircraft flight","interactions":[],"lastModifiedDate":"2018-10-03T11:39:09","indexId":"70199911","displayToPublicDate":"2018-10-01T11:38:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary evaluation of behavioral response of nesting waterbirds to small unmanned aircraft flight","docAbstract":"<p><span>Small unmanned aircraft systems present an emerging technology with the potential to survey colonial waterbird populations while reducing disturbance in comparison to traditional ground counts. Recent research with these systems has been performed on some colonially nesting avian species; however, none have focused on wading bird species. During 2015–2016, this study tested the behavioral response of a mixed-species rookery (Cattle Egret (</span><i>Bubulcus ibis</i><span>), Snowy Egret (</span><i>Egretta thula</i><span>), Glossy Ibis (</span><i>Plegadis falcinellus</i><span>) and a groundnesting colony of Common Terns (</span><i>Sterna hirundo</i><span>)) in shrub habitat to small unmanned aircraft system flights at 12 m, 15 m, 30 m, and 50 m. Even at the lowest altitudes, the birds either showed no reaction or acclimated within 60 sec of the fly-over. Conversely, physically entering the colony to conduct ground surveys resulted in all Common Terns flushing from their nests beginning when the observer was 50 m away and required significantly more time in the colony overall: ~30–60 min vs. ~3–7 min with the small unmanned aircraft system. While this study focuses only on the behavioral response of nesting birds and not comparison of count estimates, these results provide preliminary evidence that small unmanned aircraft systems provide the potential to monitor colonial nesting bird populations while minimizing disturbance to the colony.</span></p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.041.0314","usgsCitation":"Reintsma, K., McGowan, P.C., Callahan, C.R., Collier, T., Gray, D., Sullivan, J.D., and Prosser, D.J., 2018, Preliminary evaluation of behavioral response of nesting waterbirds to small unmanned aircraft flight: Waterbirds, v. 41, no. 3, p. 326-331, https://doi.org/10.1675/063.041.0314.","productDescription":"6 p.","startPage":"326","endPage":"331","ipdsId":"IP-093211","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":358089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f81e4b0fc368eb5386d","contributors":{"authors":[{"text":"Reintsma, Kaitlyn","contributorId":208435,"corporation":false,"usgs":true,"family":"Reintsma","given":"Kaitlyn","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":747253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":747254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":747255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collier, Tom","contributorId":208436,"corporation":false,"usgs":false,"family":"Collier","given":"Tom","email":"","affiliations":[{"id":37801,"text":"UASbio","active":true,"usgs":false}],"preferred":false,"id":747256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, David","contributorId":208437,"corporation":false,"usgs":false,"family":"Gray","given":"David","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":747257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":747258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":747252,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70201104,"text":"70201104 - 2018 - Stock structure, dynamics, demographics, and movements of walleyes spawning in four tributaries to Green Bay","interactions":[],"lastModifiedDate":"2018-11-29T11:34:28","indexId":"70201104","displayToPublicDate":"2018-10-01T11:34:21","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Stock structure, dynamics, demographics, and movements of walleyes spawning in four tributaries to Green Bay","docAbstract":"<p><span>To test assumptions related to the current conceptual model for walleye&nbsp;</span><i>Sander vitreus</i><span>management&nbsp;in Green Bay, we evaluated whether: 1) spawning aggregations in the Fox, Menominee, Oconto, and Peshtigo rivers represent genetically distinct stocks; 2)&nbsp;population dynamics&nbsp;and demographics vary among walleye spawning at these locations; 3) walleye spawning in these rivers contribute to the&nbsp;fishery&nbsp;in northern Green Bay, and 4) walleye spawning in these rivers exhibit spawning&nbsp;site fidelity&nbsp;or if they stray among rivers.&nbsp;Genetic differentiation&nbsp;among the four&nbsp;tributaries&nbsp;was low and sex-specific total length (TL), mean TL at age 5, and age-class diversity were generally similar among rivers and observed differences were not consistent. Movements of walleye inferred from angler tag returns suggest that walleye spawning (and tagged) in the four tributaries typically remain within southern Green Bay; however, this assertion may be confounded by the distribution of angling effort that provides tag recoveries. Straying rates among rivers ranged from 0 to 23% and were likely sufficient to preclude genetic differentiation among stocks. Collectively, results suggest that walleye spawning in the Fox, Menominee, Oconto, and Peshtigo rivers do not function as separate stocks and do not significantly contribute to the fishery outside of southern Green Bay. The primary assumption of the current conceptual model that remains to be tested is whether the walleye fishery in southern Green Bay is supported primarily by fish spawning in these four rivers, or if there are substantial contributions from fish spawning at other unknown locations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2018.07.002","usgsCitation":"Dembkowski, D.J., Isermann, D.A., Hogler, S., Larson, W., and Turnquist, K.N., 2018, Stock structure, dynamics, demographics, and movements of walleyes spawning in four tributaries to Green Bay: Journal of Great Lakes Research, v. 44, no. 5, p. 970-978, https://doi.org/10.1016/j.jglr.2018.07.002.","productDescription":"9 p.","startPage":"970","endPage":"978","ipdsId":"IP-090620","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":359790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.08563232421875,\n              44.49258696288604\n            ],\n            [\n              -87.01446533203125,\n              44.49258696288604\n            ],\n            [\n              -87.01446533203125,\n              45.460130637921004\n            ],\n            [\n              -88.08563232421875,\n              45.460130637921004\n            ],\n            [\n              -88.08563232421875,\n              44.49258696288604\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0108d3e4b0815414cc2df5","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":210893,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":752690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":752688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogler, Steven R.","contributorId":210894,"corporation":false,"usgs":false,"family":"Hogler","given":"Steven R.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":752691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":752689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turnquist, Keith N.","contributorId":210895,"corporation":false,"usgs":false,"family":"Turnquist","given":"Keith","email":"","middleInitial":"N.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":752692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70198509,"text":"sir20185106 - 2018 - Simulation of groundwater flow, 1895–2010, and effects of additional groundwater withdrawals on future stream base flow in the Elkhorn and Loup River Basins, central Nebraska—Phase three","interactions":[],"lastModifiedDate":"2018-10-02T10:59:41","indexId":"sir20185106","displayToPublicDate":"2018-10-01T11:33:36","publicationYear":"2018","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":"2018-5106","title":"Simulation of groundwater flow, 1895–2010, and effects of additional groundwater withdrawals on future stream base flow in the Elkhorn and Loup River Basins, central Nebraska—Phase three","docAbstract":"<p>The U.S.&nbsp;Geological Survey, in cooperation with the Lewis and Clark, Lower Elkhorn, Lower Loup, Lower Platte North, Lower Niobrara, Middle Niobrara, Upper Elkhorn, and the Upper Loup Natural Resources Districts, designed a study to refine the spatial and temporal discretization of a previously modeled area. This updated study focused on a 30,000-square-mile area of the High Plains aquifer and constructed regional groundwater-flow models to evaluate the effects of groundwater withdrawal on stream base flow in the Elkhorn and Loup River Basins, Nebraska. The model was calibrated to match groundwater-level and base-flow data from the stream-aquifer system from pre-1940 through 2010 (including predevelopment [pre-1895], early development [1895–1940], and historical development [1940 through 2010] conditions) using an automated parameter-estimation method. The calibrated model then was used to simulate hypothetical development conditions (2011 through 2060). Predicted changes to stream base flow based on simulated changes to groundwater withdrawal will aid in developing strategies for management of hydrologically connected water supplies.<br></p><p>Additional wells were simulated throughout the model domain and pumped for 50&nbsp;years to assess the effect of wells on aquifer depletions, including stream base flow. The percentage of withdrawal for each well after 50&nbsp;years, which was compensated by aquifer reductions to stream base flow, storage, or evapotranspiration, was computed and mapped. These depletions are influenced by aquifer properties, time, and distance from the well. Stream base-flow depletion results showed that the closer the added well was to a stream, the greatest the effect on the stream base flow. Areas of stream base-flow depletion percentages greater than 80&nbsp;percent were generally within 1&nbsp;mile (mi) from the stream. The distance increased to 6&nbsp;mi near the confluence of the Dismal and Middle Loup Rivers, and the North Loup and Calamus Rivers. The percentage of stream base-flow depletion decreased as the distance from the stream increased. Areas more than 10&nbsp;mi from the stream generally had a stream base-flow depletion of 10&nbsp;percent or less. Evapotranspiration depletion was largest in areas closest to streams, specifically in the Elkhorn River watershed. It was also larger in areas of interdunal wetlands within the Sand Hills. Evapotranspiration depletion was negligible in areas greater than 5&nbsp;mi from a stream, with the exception of interdunal areas in Cherry, Grant, and Arthur Counties. The storage depletion percentage increased as the distance from a stream increased. Storage depletion was largest in areas between streams. Areas experiencing the smallest amount of storage depletion were adjacent to streams. Calibrated model outputs and streamflow depletion analysis are publicly available online.<br></p><p>Accuracy of the simulations is affected by input data limitations, system simplifications, assumptions, and resources available at the time of the simulation construction and calibration. Most of the important limitations relate either to data used as simulation inputs or to data used to estimate simulation inputs. Development of the regional simulations focused on generalized hydrogeologic characteristics within the study area and did not attempt to describe variations important to local-scale conditions. These simulations are most appropriate for analyzing groundwater-management scenarios for large areas and during long periods and are not suitable for analysis of small areas or short periods.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185106","collaboration":"Prepared in cooperation with the Lewis and Clark, Lower Elkhorn, Lower Loup, Lower Platte North, Lower Niobrara, Middle Niobrara, Upper Elkhorn, and  Upper Loup Natural Resources Districts","usgsCitation":"Flynn, A.T., and Stanton, J.S., 2018, Simulation of groundwater flow, 1895–2010, and effects of additional groundwater withdrawals on future stream base flow in the Elkhorn and Loup River Basins, central Nebraska—Phase three: U.S. Geological Survey Scientific Investigations Report 2018–5106, 65 p., https://doi.org/10.3133/sir20185106.","productDescription":"Report: ix, 65 p.; Data Releases","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-085070","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":357262,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RITFNL","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT groundwater flow model used to evaluate groundwater flow in the Elkhorn and Loup River Basins, Central Nebraska, Phase Three: U.S. Geological Survey data release"},{"id":356818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5106/coverthb3.jpg"},{"id":357263,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UA3UUD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-level and digital data for the Elkhorn and Loup River Basins groundwater flow model, Phase Three"},{"id":357261,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5106/sir20185106.pdf","text":"Report","size":"18.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5106"}],"country":"United States","state":"Nebraska","otherGeospatial":"Elkhorn and Loup River Basins","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -102.14216807317632,\n              40.58107734258557\n            ],\n            [\n              -97.251923792,\n              40.58107734258557\n            ],\n            [\n              -97.251923792,\n              42.959577151422394\n            ],\n            [\n              -102.14216807317632,\n              42.959577151422394\n            ],\n            [\n              -102.14216807317632,\n              40.58107734258557\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"mailto:%20dc_ne@usgs.gov\" href=\"mailto:%20dc_ne@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/ne-water\" href=\"https://www.usgs.gov/centers/ne-water\">Nebraska Water Science Center</a><br>U.S. Geological Survey<br>5231 South 19th Street<br>Lincoln, NE 68512</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Simulation of Groundwater Flow</li><li>Simulation of Effect of Additional Groundwater Withdrawals on Future Stream Base-Flow, Evapotranspiration, and Storage Depletion</li><li>Model Assumptions</li><li>Model Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix Figures</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-10-01","noUsgsAuthors":false,"publicationDate":"2018-10-01","publicationStatus":"PW","scienceBaseUri":"5bc02f82e4b0fc368eb5386f","contributors":{"authors":[{"text":"Flynn, Amanda T. 0000-0001-9768-2076 aflynn@usgs.gov","orcid":"https://orcid.org/0000-0001-9768-2076","contributorId":176644,"corporation":false,"usgs":true,"family":"Flynn","given":"Amanda","email":"aflynn@usgs.gov","middleInitial":"T.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":741804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Jennifer S. 0000-0002-2520-753X jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":741805,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70201106,"text":"70201106 - 2018 - Evaluation of anal fin spines, otoliths, and scales for estimating age and back-calculated lengths of yellow perch in southern Green Bay","interactions":[],"lastModifiedDate":"2018-11-29T11:31:48","indexId":"70201106","displayToPublicDate":"2018-10-01T11:31:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of anal fin spines, otoliths, and scales for estimating age and back-calculated lengths of yellow perch in southern Green Bay","docAbstract":"<p><span>Southern Green Bay supports important&nbsp;fisheries&nbsp;for yellow perch&nbsp;</span><i>Perca flavescens</i><span>&nbsp;and valid estimates of&nbsp;age structure&nbsp;and growth are critical to effective&nbsp;management. Anal fin spines and scales are used by the&nbsp;Wisconsin&nbsp;Department of Natural Resources for age estimation, but these structures may provide lower precision and accuracy than&nbsp;otoliths. The primary objective of our assessment was to determine if age estimates, among-reader precision, and mean back-calculated total lengths (TLs) at age differed among scales, anal fin spines, and otoliths. Ages estimated from anal fin spines were more precise than scale ages, were as precise as otolith-based ages, and generally agreed with consensus ages estimated from sectioned otoliths. Relationships between TL and radii of calcified structures were linear for scales, anal spines, and otoliths along two different transects. Mean back-calculated TLs were generally similar between intercept-corrected direct proportion (ICDP) and linear regression (LR) models, but otolith-based direct proportion models (no intercept correction) generally provided higher back-calculated mean TLs at ages 1 and 2 than ICDP and LR models. Mean back-calculated TLs at age estimated from whole otoliths were higher than estimates for other structures; but differences among anal fin spines, scales, and sectioned otoliths were &lt;10 mm. Our results suggest biologists have little to gain by switching to otoliths when assessing age structure and growth for this fast-growing yellow perch population with relatively few fish ≥age 6, but additional analyses are warranted for slower-growing perch populations in the Great Lakes where older fish are more common.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2018.06.002","usgsCitation":"Isermann, D.A., Breeggemann, J.J., and Paroli, T.J., 2018, Evaluation of anal fin spines, otoliths, and scales for estimating age and back-calculated lengths of yellow perch in southern Green Bay: Journal of Great Lakes Research, v. 44, no. 5, p. 979-989, https://doi.org/10.1016/j.jglr.2018.06.002.","productDescription":"11 p.","startPage":"979","endPage":"989","ipdsId":"IP-090742","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":359789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Bay","volume":"44","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0108d4e4b0815414cc2df7","contributors":{"authors":[{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":752697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breeggemann, Jason J.","contributorId":149395,"corporation":false,"usgs":false,"family":"Breeggemann","given":"Jason","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":752698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paroli, Tammie J.","contributorId":210899,"corporation":false,"usgs":false,"family":"Paroli","given":"Tammie","email":"","middleInitial":"J.","affiliations":[{"id":38155,"text":"WI DNR","active":true,"usgs":false}],"preferred":false,"id":752699,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70199840,"text":"70199840 - 2018 - Occupancy modeling species–environment relationships with non‐ignorable survey designs","interactions":[],"lastModifiedDate":"2018-10-02T11:16:16","indexId":"70199840","displayToPublicDate":"2018-10-01T11:16:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy modeling species–environment relationships with non‐ignorable survey designs","docAbstract":"<p><span>Statistical models supporting inferences about species occurrence patterns in relation to environmental gradients are fundamental to ecology and conservation biology. A common implicit assumption is that the sampling design is ignorable and does not need to be formally accounted for in analyses. The analyst assumes data are representative of the desired population and statistical modeling proceeds. However, if data sets from probability and non‐probability surveys are combined or unequal selection probabilities are used, the design may be non‐ignorable. We outline the use of pseudo‐maximum likelihood estimation for site‐occupancy models to account for such non‐ignorable survey designs. This estimation method accounts for the survey design by properly weighting the pseudo‐likelihood equation. In our empirical example, legacy and newer randomly selected locations were surveyed for bats to bridge a historic statewide effort with an ongoing nationwide program. We provide a worked example using bat acoustic detection/non‐detection data and show how analysts can diagnose whether their design is ignorable. Using simulations we assessed whether our approach is viable for modeling data sets composed of sites contributed outside of a probability design. Pseudo‐maximum likelihood estimates differed from the usual maximum likelihood occupancy estimates for some bat species. Using simulations we show the maximum likelihood estimator of species–environment relationships with non‐ignorable sampling designs was biased, whereas the pseudo‐likelihood estimator was design unbiased. However, in our simulation study the designs composed of a large proportion of legacy or non‐probability sites resulted in estimation issues for standard errors. These issues were likely a result of highly variable weights confounded by small sample sizes (5% or 10% sampling intensity and four revisits). Aggregating data sets from multiple sources logically supports larger sample sizes and potentially increases spatial extents for statistical inferences. Our results suggest that ignoring the mechanism for how locations were selected for data collection (e.g., the sampling design) could result in erroneous model‐based conclusions. Therefore, in order to ensure robust and defensible recommendations for evidence‐based conservation decision‐making, the survey design information in addition to the data themselves must be available for analysts. Details for constructing the weights used in estimation and code for implementation are provided.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1754","usgsCitation":"Irvine, K.M., Rodhouse, T., Wright, W.J., and Olsen, A.R., 2018, Occupancy modeling species–environment relationships with non‐ignorable survey designs: Ecological Applications, v. 28, no. 6, p. 1616-1625, https://doi.org/10.1002/eap.1754.","productDescription":"10 p.","startPage":"1616","endPage":"1625","ipdsId":"IP-088406","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468351,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc6457115","text":"External Repository"},{"id":437730,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55MPV","text":"USGS data release","linkHelpText":"Software Supplement to accompany 'Estimating Species-Environment Relationships with Non-ignorable Sampling Designs'"},{"id":358015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-19","publicationStatus":"PW","scienceBaseUri":"5bc02f83e4b0fc368eb53871","contributors":{"authors":[{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":746859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":746860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Wilson J. 0000-0003-4276-3850 wjwright@usgs.gov","orcid":"https://orcid.org/0000-0003-4276-3850","contributorId":198317,"corporation":false,"usgs":true,"family":"Wright","given":"Wilson","email":"wjwright@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":746862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen, Anthony R.","contributorId":208362,"corporation":false,"usgs":false,"family":"Olsen","given":"Anthony","email":"","middleInitial":"R.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":747118,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227828,"text":"70227828 - 2018 - Wild migrations: Atlas of Wyoming's ungulates","interactions":[],"lastModifiedDate":"2022-02-01T17:10:43.351932","indexId":"70227828","displayToPublicDate":"2018-10-01T11:07:33","publicationYear":"2018","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"Wild migrations: Atlas of Wyoming's ungulates","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Oregon State University Press","usgsCitation":"Rudd, W.J., Kauffman, M., Meacham, J., Sawyer, H., Ostlind, E., and Steingisser, A., 2018, Wild migrations: Atlas of Wyoming's ungulates, 208 p.","productDescription":"208 p.","ipdsId":"IP-093026","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.03881835937499,\n              41.0130657870063\n            ],\n            [\n              -104.029541015625,\n              41.0130657870063\n            ],\n            [\n              -104.029541015625,\n              44.98811302615805\n            ],\n            [\n              -111.03881835937499,\n              44.98811302615805\n            ],\n            [\n              -111.03881835937499,\n              41.0130657870063\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rudd, William J.","contributorId":273041,"corporation":false,"usgs":false,"family":"Rudd","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":832504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meacham, James","contributorId":244696,"corporation":false,"usgs":false,"family":"Meacham","given":"James","email":"","affiliations":[],"preferred":false,"id":832505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":832506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ostlind, Emilene","contributorId":273042,"corporation":false,"usgs":false,"family":"Ostlind","given":"Emilene","email":"","affiliations":[],"preferred":false,"id":832507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steingisser, Alethea","contributorId":201403,"corporation":false,"usgs":false,"family":"Steingisser","given":"Alethea","email":"","affiliations":[],"preferred":false,"id":832508,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70200932,"text":"70200932 - 2018 - A geostatistical state‐space model of animal densities for stream networks","interactions":[],"lastModifiedDate":"2018-11-16T11:06:33","indexId":"70200932","displayToPublicDate":"2018-10-01T11:06:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A geostatistical state‐space model of animal densities for stream networks","docAbstract":"<p><span>Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty underestimated. We developed a novel statistical method to account for spatiotemporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15&nbsp;yr. Increasing the number of survey sites within the network improved the performance of the nonspatial model but only marginally improved the density estimates in the spatiotemporal model. We applied this model to brook trout data from the West Susquehanna Watershed in Pennsylvania collected over 34&nbsp;yr from 1981 to 2014. We found the model including temporal and spatiotemporal autocorrelation best described young of the year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately high spatiotemporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatiotemporal correlation and higher temporal autocorrelation.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1767","usgsCitation":"Hocking, D., Thorson, J.T., O’Neil, K., and Letcher, B., 2018, A geostatistical state‐space model of animal densities for stream networks: Ecological Applications, v. 28, no. 7, p. 1782-1796, https://doi.org/10.1002/eap.1767.","productDescription":"15 p.","startPage":"1782","endPage":"1796","ipdsId":"IP-098139","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468352,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/53438","text":"External Repository"},{"id":359510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"7","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-23","publicationStatus":"PW","scienceBaseUri":"5befe5bce4b045bfcadf7f3e","contributors":{"authors":[{"text":"Hocking, Daniel J.","contributorId":210650,"corporation":false,"usgs":false,"family":"Hocking","given":"Daniel J.","affiliations":[{"id":38122,"text":"University of MD","active":true,"usgs":false}],"preferred":false,"id":751374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorson, James T.","contributorId":146580,"corporation":false,"usgs":false,"family":"Thorson","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":751375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Kyle","contributorId":210652,"corporation":false,"usgs":false,"family":"O’Neil","given":"Kyle","email":"","affiliations":[{"id":38124,"text":"University of MA","active":true,"usgs":false}],"preferred":false,"id":751376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":167313,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":751373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70228121,"text":"70228121 - 2018 - Migration trends for king and common eiders and yellow-billed loons past Point Barrow in a rapidly changing environment","interactions":[],"lastModifiedDate":"2022-02-04T17:12:30.916117","indexId":"70228121","displayToPublicDate":"2018-10-01T11:05:32","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"BOEM 2018-059","title":"Migration trends for king and common eiders and yellow-billed loons past Point Barrow in a rapidly changing environment","docAbstract":"<p>Most of the king (<i>Somateria spectabilis</i>) and common eiders (<i>S. mollissima v-nigra</i>) nesting in northern Alaska and northwestern Canada migrate past Point Barrow, Alaska, during the spring and fall migration. Yellow-billed loons (<i>Gavia adamsii</i>) also migrate past Point Barrow and are a species of international conservation concern. Spring migration counts of eiders have been conducted approximately every ten years at Point Barrow since 1976, and indicated that both eider species experienced population declines of approximately 50% between 1976 and 1996, and that the declines had stabilized by 2004. Population estimates derived from migration counts have not been previously estimated for yellow-billed loons. We conducted spring counts of eiders and loons in 2015 and 2016 to obtain population estimates to compare with those from 1994, 1995, 2003, and 2004 in order to evaluate long-term and current trends. We estimated (95% confidence intervals) that 796,419 (304,011) king and 96,775 (39,913) common eiders passed Point Barrow in 2015, and 322,381 (145,833) king and 130,390 (34,548) common eiders passed Point Barrow in 2016. Both and king and common eider population estimates increased from 1994 through 2016, however, the increase over time was not significant (F &lt; 5.07, P &gt; 0.087, df = 1). Our population estimates for king eiders were very different between the two years of this study, possibly due to a very short and intense migration peak in 2016, resulting in a population count that was biased low because sampling periods did not adequately capture the peak of migration. The numbers of common eiders were similar between the two years, as well as for the 12 years since the previous count. Photo analysis of flocks indicated that observer counts were on average 4% lower than photo counts (paired t-test; |t| = 3.26, df = 297, P &lt; 0.001) for flocks less than 1400 individuals (observer count). Estimates of yellow-billed loon populations were very variable and are biased low as numbers of loons passing Pt. Barrow were still high when our counts ended in late May. It is important that counts continue to be conducted for these species of conservation and subsistence importance, but that techniques be refined to reduce bias and variability, and to find solutions to the increasing difficulty of conducting a count from the shore-fast ice in spring.</p>","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Powell, A., Bentzen, R., and Suydam, R., 2018, Migration trends for king and common eiders and yellow-billed loons past Point Barrow in a rapidly changing environment: Final Report BOEM 2018-059, iii, 19 p.","productDescription":"iii, 19 p.","ipdsId":"IP-097667","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395445,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.boem.gov/sites/default/files/boem-newsroom/Library/Publications/2018/BOEM2018-059.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Point Barrow","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.0330810546875,\n              71.23287161628951\n            ],\n            [\n              -156.24755859375,\n              71.23287161628951\n            ],\n            [\n              -156.24755859375,\n              71.52839020407738\n            ],\n            [\n              -157.0330810546875,\n              71.52839020407738\n            ],\n            [\n              -157.0330810546875,\n              71.23287161628951\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":833168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bentzen, R.","contributorId":274625,"corporation":false,"usgs":false,"family":"Bentzen","given":"R.","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":833169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suydam, R.","contributorId":243090,"corporation":false,"usgs":false,"family":"Suydam","given":"R.","email":"","affiliations":[{"id":48637,"text":"North Slope Borough","active":true,"usgs":false}],"preferred":false,"id":833170,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70200417,"text":"70200417 - 2018 - Floristic and climatic reconstructions of two Lower Cretaceous successions from Peru","interactions":[],"lastModifiedDate":"2018-10-17T11:02:05","indexId":"70200417","displayToPublicDate":"2018-10-01T11:02:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3006,"text":"Palynology","active":true,"publicationSubtype":{"id":10}},"title":"Floristic and climatic reconstructions of two Lower Cretaceous successions from Peru","docAbstract":"<p><span>Climate during the Early Cretaceous in tropical South America has often been reconstructed as arid. However, some areas seem to have been humid. We reconstructed the floristic composition of two tropical stratigraphic successions in Peru using quantitative palynology (rarefied species richness and abundance), and used the abundance of aridity vs. humidity indicator species to infer the predominant climate conditions of this region. The Berriasian to Hauterivian La Merced succession was dominated by fern spores and was predominantly humid. The Albian Aguas Frias succession yielded rich palynofloras, with 127 species, and also indicates predominantly humid conditions. These results support the hypothesis that the west margin of South America was humid during the Early Cretaceous, thus improving the tropical climate reconstructions during the Cretaceous severe global warming episodes.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01916122.2017.1373310","usgsCitation":"Mejia-Velasquez, P.J., Manchester, S.R., Jaramillo, C.A., Quiroz, L., and Fortini, L.B., 2018, Floristic and climatic reconstructions of two Lower Cretaceous successions from Peru: Palynology, v. 42, no. 3, p. 420-433, https://doi.org/10.1080/01916122.2017.1373310.","productDescription":"14 p.","startPage":"420","endPage":"433","ipdsId":"IP-090469","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":490054,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/Floristic_and_climatic_reconstructions_of_two_Lower_Cretaceous_successions_from_Peru/5501638","text":"External Repository"},{"id":358476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","volume":"42","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"5c10a931e4b034bf6a7e5088","contributors":{"authors":[{"text":"Mejia-Velasquez, Paula J.","contributorId":209758,"corporation":false,"usgs":false,"family":"Mejia-Velasquez","given":"Paula","email":"","middleInitial":"J.","affiliations":[{"id":37977,"text":"University of Hawaii – Leeward Community College","active":true,"usgs":false}],"preferred":false,"id":748747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manchester, Steven R.","contributorId":209759,"corporation":false,"usgs":false,"family":"Manchester","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":37978,"text":"Florida Museum of Natural History and Biology Department, University of Florida","active":true,"usgs":false}],"preferred":false,"id":748748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaramillo, Carlos A.","contributorId":209760,"corporation":false,"usgs":false,"family":"Jaramillo","given":"Carlos","email":"","middleInitial":"A.","affiliations":[{"id":12671,"text":"Smithsonian Tropical Research Institute","active":true,"usgs":false}],"preferred":false,"id":748749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quiroz, Luiz","contributorId":209761,"corporation":false,"usgs":false,"family":"Quiroz","given":"Luiz","email":"","affiliations":[{"id":37979,"text":"Dept. of Geological Sciences, University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":748750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fortini, Lucas B. 0000-0002-5781-7295 lfortini@usgs.gov","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":4645,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas","email":"lfortini@usgs.gov","middleInitial":"B.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":748746,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202476,"text":"70202476 - 2018 - Long-term rehabilitation of Delavan Lake, Wisconsin, USA","interactions":[],"lastModifiedDate":"2020-10-22T20:31:25.916752","indexId":"70202476","displayToPublicDate":"2018-10-01T10:53:57","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Long-term rehabilitation of Delavan Lake, Wisconsin, USA","docAbstract":"<p>No abstract available.&nbsp;</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lake restoration handbook: A New Zealand perspective","largerWorkSubtype":{"id":13,"text":"Handbook"},"language":"English","publisher":"Springer","usgsCitation":"Robertson, D.M., 2018, Long-term rehabilitation of Delavan Lake, Wisconsin, USA, chap. <i>of</i> Lake restoration handbook: A New Zealand perspective, p. 131-133.","productDescription":"3 p.","startPage":"131","endPage":"133","ipdsId":"IP-081276","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379664,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.springer.com/gp/book/9783319930428"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Delavan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.58345031738281,\n              42.614885927918685\n            ],\n            [\n              -88.56353759765625,\n              42.63635819687411\n            ],\n            [\n              -88.57709884643555,\n              42.633074682541015\n            ],\n            [\n              -88.58551025390624,\n              42.627896481020855\n            ],\n            [\n              -88.58551025390624,\n              42.62435990071571\n            ],\n            [\n              -88.60061645507812,\n              42.62688605000682\n            ],\n            [\n              -88.62550735473633,\n              42.614633268911696\n            ],\n            [\n              -88.61623764038086,\n              42.610843260801005\n            ],\n            [\n              -88.60679626464844,\n              42.61551757095158\n            ],\n            [\n              -88.6098861694336,\n              42.610337908960524\n            ],\n            [\n              -88.61726760864258,\n              42.6064212931765\n            ],\n            [\n              -88.6270523071289,\n              42.60010365202599\n            ],\n            [\n              -88.65365982055664,\n              42.59214251204963\n            ],\n            [\n              -88.63409042358398,\n              42.578871685346364\n            ],\n            [\n              -88.59477996826172,\n              42.601367231506835\n            ],\n            [\n              -88.58345031738281,\n              42.614885927918685\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Hamilton, D.","contributorId":54316,"corporation":false,"usgs":true,"family":"Hamilton","given":"D.","affiliations":[],"preferred":false,"id":759050,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Collier, K.","contributorId":214062,"corporation":false,"usgs":false,"family":"Collier","given":"K.","affiliations":[],"preferred":false,"id":759051,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Quinn, J.","contributorId":214063,"corporation":false,"usgs":false,"family":"Quinn","given":"J.","affiliations":[],"preferred":false,"id":759052,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Howard-Williams, C.","contributorId":214064,"corporation":false,"usgs":false,"family":"Howard-Williams","given":"C.","affiliations":[],"preferred":false,"id":759053,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":204668,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758765,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70200423,"text":"70200423 - 2018 - Juke Box trench: A valuable archive of late Pleistocene and Holocene stratigraphy in the Bonneville basin, Utah","interactions":[],"lastModifiedDate":"2018-10-17T10:52:03","indexId":"70200423","displayToPublicDate":"2018-10-01T10:51:57","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5627,"text":"Miscellaneous Publication","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"18-1","title":"Juke Box trench: A valuable archive of late Pleistocene and Holocene stratigraphy in the Bonneville basin, Utah","docAbstract":"<p>A backhoe trench in deposits of Pleistocene Lake Bonneville and Holocene wetlands below the mouth of Juke Box Cave, near Wendover, Utah, provides an excellent view of the late Pleistocene and Holocene geologic history of the area. The following stratigraphic units are exposed (ascending): preBonneville gravel (fluvial or lacustrine) and oolitic sand (ages greater than 30,000 yr B.P.); Lake Bonneville marl (30,000 to ~13,000 yr B.P.); an unconformity stratigraphically above the Bonneville marl marked by lacustrine gravel of probable Gilbert-episode age (~11,500 yr B.P.); and poorly sorted sand and carbonate mud deposited in post-Bonneville spring-fed wetlands. The wetland deposits include layers of poorly sorted sand, peat composed of bulrush remains and other organic-rich muds, and the Mazama volcanic ash (~7600 yr B.P.). Four calibrated 14C ages suggest the wetland deposits span nearly the entire Holocene, from about 10,700 to at least 1200 yr B.P. The spring and wetland are now dry. </p>","language":"English","publisher":"Utah Geological Survey","usgsCitation":"Oviatt, C.G., Pigati, J.S., Madsen, D.B., Rhode, D.E., and Bright, J., 2018, Juke Box trench: A valuable archive of late Pleistocene and Holocene stratigraphy in the Bonneville basin, Utah: Miscellaneous Publication 18-1, 34 p.","productDescription":"34 p.","ipdsId":"IP-092966","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":358474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358473,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://ugspub.nr.utah.gov/publications/misc_pubs/mp-18-1.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Utah","otherGeospatial":"Bonneville Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.0333,\n              40.7333\n            ],\n            [\n              -113.9667,\n              40.7333\n            ],\n            [\n              -113.9667,\n              40.7667\n            ],\n            [\n              -114.0333,\n              40.7667\n            ],\n            [\n              -114.0333,\n              40.7333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a931e4b034bf6a7e508c","contributors":{"authors":[{"text":"Oviatt, Charles G.","contributorId":36580,"corporation":false,"usgs":false,"family":"Oviatt","given":"Charles","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":748768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":748767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madsen, David B.","contributorId":191727,"corporation":false,"usgs":false,"family":"Madsen","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":748769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rhode, David E.","contributorId":209765,"corporation":false,"usgs":false,"family":"Rhode","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":748770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bright, Jordon","contributorId":76010,"corporation":false,"usgs":true,"family":"Bright","given":"Jordon","affiliations":[],"preferred":false,"id":748796,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70199829,"text":"70199829 - 2018 - Induced earthquake and liquefaction hazards in Oklahoma, USA: Constraints from InSAR","interactions":[],"lastModifiedDate":"2018-10-01T10:48:46","indexId":"70199829","displayToPublicDate":"2018-10-01T10:48:42","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Induced earthquake and liquefaction hazards in Oklahoma, USA: Constraints from InSAR","docAbstract":"<p><span>Oklahoma experienced three&nbsp;earthquakes&nbsp;of M</span><sub>w</sub><span>5.0 or greater in 2016: the 13-Feb. Fairview earthquake (M</span><sub>w</sub><span>5.1), the 03-Sep. Pawnee earthquake (M</span><sub>w</sub><span>5.8), and the 07-Nov. Cushing earthquake (M</span><sub>w</sub><span>5.0). These events are the first earthquakes in the state exceeding M</span><sub>w</sub><span>5.0 since the 2011 M</span><sub>w</sub><span>5.7 Prague earthquake and likely result from wide-scale deep&nbsp;fluid-injection. We use interferometric&nbsp;synthetic aperture radar&nbsp;(InSAR) observations to quantify the magnitude and location of surface deformation associated with these three events, determine the depth ranges of&nbsp;fault slip, and assess the spatial relationship between fault slip and well-calibrated mainshock and&nbsp;aftershock&nbsp;locations. We also include newly reported, calibrated event locations for the Cushing earthquake. We find that the Pawnee earthquake ruptured within the crystalline basement with the shallowest slip occurring at depths of 3.1–4.3 km. We find a similar, though shallower, crystalline basement source for the Cushing earthquake with a minimum depth to slip of 1.6–2.3 km. Despite the smaller magnitude of the Cushing earthquake, it generated anomalously high&nbsp;ground motions&nbsp;and damage compared to the larger Pawnee and Fairview earthquakes. We postulate that the shallow source of the Cushing earthquakes provides one explanation for the higher than expected ground motions. The Fairview earthquake generated no detectable co-seismic displacements, which is consistent with a relatively deep earthquake source (~8.5 km). We do, however, identify a 16 km stretch of&nbsp;floodplain&nbsp;where widespread&nbsp;liquefaction&nbsp;occurred in response to the Fairview earthquake, and where 30&nbsp;gas production&nbsp;wells were exposed to surface displacements exceeding 5 cm. Consequently, the depth to crystalline basement, which limits the depth of injection-induced earthquakes in Oklahoma, and the potential for liquefaction are important factors in assessing shaking risk in the central United States.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2018.09.005","usgsCitation":"Barnhart, W., Yeck, W.L., and McNamara, D.E., 2018, Induced earthquake and liquefaction hazards in Oklahoma, USA: Constraints from InSAR: Remote Sensing of Environment, v. 218, p. 1-12, https://doi.org/10.1016/j.rse.2018.09.005.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-092651","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2018.09.005","text":"Publisher Index Page"},{"id":357942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100,\n              34\n            ],\n            [\n              -96,\n              34\n            ],\n            [\n              -96,\n              37\n            ],\n            [\n              -100,\n              37\n            ],\n            [\n              -100,\n              34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"218","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f84e4b0fc368eb53873","contributors":{"authors":[{"text":"Barnhart, William D. 0000-0003-0498-1697","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":192730,"corporation":false,"usgs":false,"family":"Barnhart","given":"William D.","affiliations":[],"preferred":false,"id":746822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":746823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70199808,"text":"70199808 - 2018 - Economics, helium, and the U.S. Federal Helium Reserve: Summary and outlook","interactions":[],"lastModifiedDate":"2018-10-01T10:44:29","indexId":"70199808","displayToPublicDate":"2018-10-01T10:44:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Economics, helium, and the U.S. Federal Helium Reserve: Summary and outlook","docAbstract":"<p><span>In 2017, disruptions in the global supply of helium reminded consumers, distributors, and policy makers that the global helium supply chain lacks flexibility, and that attempts to increase production from the U.S. Federal Helium Reserve (the FHR) may not be able to compensate for the loss of one of the few major producers in the world. Issues with U.S. and global markets for helium include inelastic demand, economic availability of helium only as a byproduct, only 4–5 major producers, helium’s propensity to escape earth’s crust, an ongoing absence of storage facilities comparable to the FHR, and a lack of consequences for the venting of helium. The complex combination of these economic, physical, and regulatory issues is unique to helium, and determining helium’s practical availability goes far beyond estimating the technically accessible volume of underground resources. Although most of these issues have been analyzed since helium was recognized to be a valuable mineral commodity in the early 1900s, very few economic models have been developed that adequately consider the unique characteristics of helium and helium markets. In particular, there is a notable lack of recent empirical work to estimate the responsiveness of helium demand, supply, prices, and trade patterns to the ongoing drawdown and sale of helium reserves stored in the FHR. In general, existing models of helium either do not account for an oligopoly controlling supply, or they do not evaluate potential helium extraction and storage programs based on an intertemporal maximization of the value of the resource. Such models could be of very limited use to decision makers. This review found only one working paper with a helium market model that has incorporated both of these vital considerations. That and other economic studies along similar lines could be very useful in helping inform current helium policy discussions and decisions.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11053-017-9359-y","usgsCitation":"Anderson, S.T., 2018, Economics, helium, and the U.S. Federal Helium Reserve: Summary and outlook: Natural Resources Research, v. 27, no. 4, p. 455-477, https://doi.org/10.1007/s11053-017-9359-y.","productDescription":"23 p.","startPage":"455","endPage":"477","ipdsId":"IP-080164","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":460835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-017-9359-y","text":"Publisher Index Page"},{"id":357940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-05","publicationStatus":"PW","scienceBaseUri":"5bc02f84e4b0fc368eb53875","contributors":{"authors":[{"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":746709,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70199815,"text":"70199815 - 2018 - Quantifying climate sensitivity and climate-driven change in North American amphibian communities","interactions":[],"lastModifiedDate":"2020-09-02T12:53:39.330782","indexId":"70199815","displayToPublicDate":"2018-10-01T10:43:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying climate sensitivity and climate-driven change in North American amphibian communities","docAbstract":"<p><span>Changing climate will impact species’ ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using &gt;500,000 time-series observations for 81 species across 86 North American study areas. The effect of climate on local colonization and persistence probabilities varies among eco-regions and depends on local climate, species life-histories, and taxonomic classification. We found that local species richness is most sensitive to changes in water availability during breeding and changes in winter conditions. Based on the relationships we measure, recent changes in climate cannot explain why local species richness of North American amphibians has rapidly declined. However, changing climate does explain why some populations are declining faster than others. Our results provide important insights into how amphibians respond to climate and a general framework for measuring climate impacts on species richness.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-06157-6","usgsCitation":"Miller, D., Campbell Grant, E.H., Muths, E.L., Amburgey, S.M., Adams, M.J., Joseph, M.B., Waddle, J.H., Johnson, P.T., Ryan, M.E., Schmidt, B.R., Calhoun, D.L., Davis, C.L., Fisher, R.N., Green, D.M., Hossack, B.R., Rittenhouse, T.A., Walls, S.C., Bailey, L.L., Cruickshank, S.S., Fellers, G.M., Gorman, T.A., Haas, C.A., Hughson, W., Pilliod, D.S., Price, S.J., Ray, A.M., Sadinski, W., Saenz, D., Barichivich, W.J., Brand, A.B., Brehme, C.S., Dagit, R., Delaney, K.S., Glorioso, B.M., Kats, L.B., Kleeman, P.M., Pearl, C., Rochester, C.J., Riley, S.P., Roth, M.F., and Sigafus, B., 2018, Quantifying climate sensitivity and climate-driven change in North American amphibian communities: Nature Communications, v. 9, 3926, 15 p., https://doi.org/10.1038/s41467-018-06157-6.","productDescription":"3926, 15 p.","ipdsId":"IP-075372","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-06157-6","text":"Publisher Index Page"},{"id":357937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-25","publicationStatus":"PW","scienceBaseUri":"5bc02f85e4b0fc368eb53877","contributors":{"authors":[{"text":"Miller, David A.W.","contributorId":198461,"corporation":false,"usgs":false,"family":"Miller","given":"David A.W.","affiliations":[],"preferred":false,"id":746731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":746732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amburgey, Staci M.","contributorId":152622,"corporation":false,"usgs":false,"family":"Amburgey","given":"Staci","email":"","middleInitial":"M.","affiliations":[{"id":12754,"text":"Penn State University Altoona","active":true,"usgs":false}],"preferred":false,"id":746733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, M. 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,{"id":70198898,"text":"ofr20181133 - 2018 - Delineation of contributing areas for 2017 pumping conditions to selected wells in Ingham County, Michigan","interactions":[],"lastModifiedDate":"2018-10-02T10:51:10","indexId":"ofr20181133","displayToPublicDate":"2018-10-01T10:15:00","publicationYear":"2018","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":"2018-1133","title":"Delineation of contributing areas for 2017 pumping conditions to selected wells in Ingham County, Michigan","docAbstract":"<p>As part of local wellhead protection area programs, areas<br>contributing water to production wells need to be periodically<br>updated because groundwater-flow paths depend in part on<br>the stresses to the groundwater-flow system. A steady-state<br>groundwater-flow model that was constructed in 2009 was<br>updated to reflect recent (2017) pumping conditions in the<br>Lansing and East Lansing area in the Tri-County region, Michigan.<br>For this current (2017) study, withdrawals from selected<br>production wells were updated, and the existing model calibration<br>under the new pumping conditions was checked. Results<br>of flow simulations indicate that 10-year time-of-travel areas<br>cover approximately 25 square miles and 40-year time-oftravel<br>areas cover approximately 51 square miles.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181133","collaboration":"Prepared in cooperation with the Lansing Board of Water and Light","usgsCitation":"Luukkonen, C.L., 2018, Delineation of contributing areas for 2017 pumping conditions to selected wells in Ingham County, Michigan: U.S. Geological Survey Open-File Report 2018–1133, 11 p., https://doi.org/10.3133/ofr20181133.","productDescription":"Report: v, 11 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-096742","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":357821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1133/ofr20181133.pdf","text":"Report","size":"1.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1133"},{"id":357822,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZY1H06","text":"USGS data release","description":"USGS data release"},{"id":357820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1133/coverthb.jpg"}],"country":"United States","state":"Michigan","county":"Ingham County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.0726318359375,\n              42.40115038362433\n            ],\n            [\n              -83.64990234375,\n              42.40115038362433\n            ],\n            [\n              -83.64990234375,\n              43.18114705939968\n            ],\n            [\n              -85.0726318359375,\n              43.18114705939968\n            ],\n            [\n              -85.0726318359375,\n              42.40115038362433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_mi@usgs.gov\" data-mce-href=\"mailto:dc_mi@usgs.gov\">Director</a>, <a href=\"https://mi.water.usgs.gov/\" data-mce-href=\"https://mi.water.usgs.gov/\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>6520 Mercantile Way Suite 5<br>Lansing, MI 48911</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description of Study Area</li><li>Groundwater-Flow Simulation</li><li>Model Assumptions and Limitations</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2018-10-01","noUsgsAuthors":false,"publicationDate":"2018-10-01","publicationStatus":"PW","scienceBaseUri":"5bc02f85e4b0fc368eb53879","contributors":{"authors":[{"text":"Luukkonen, Carol L. 0000-0001-7056-8599","orcid":"https://orcid.org/0000-0001-7056-8599","contributorId":207254,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol L.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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