{"pageNumber":"252","pageRowStart":"6275","pageSize":"25","recordCount":68813,"records":[{"id":70215559,"text":"70215559 - 2020 - Probabilistic categorical groundwater salinity mapping from airborne electromagnetic data adjacent to California’s Lost Hills and Belridge oil fields","interactions":[],"lastModifiedDate":"2020-10-23T14:06:56.145727","indexId":"70215559","displayToPublicDate":"2020-03-10T09:01:37","publicationYear":"2020","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":"Probabilistic categorical groundwater salinity mapping from airborne electromagnetic data adjacent to California’s Lost Hills and Belridge oil fields","docAbstract":"<div class=\"article-section__content en main\"><p>Growing water stress has led to emerging interest in protecting fresh and brackish groundwater as a potential supplement to water supplies and raised questions about factors that could affect the future quality of fresh and brackish aquifers. Limited well infrastructure, particularly in regions where elevated salinity has led to limited historical groundwater development, hinders traditional mapping of salinity distributions through groundwater sampling. This paper presents a quantitative salinity mapping approach of the upper 300&nbsp;m using high‐resolution, regionally comprehensive resistivity models derived from Bayesian inversion of an airborne electromagnetic survey adjacent to the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley of California. Using local water quality observations as an interpretational foundation, a probabilistic approach yields maps of fresh, saline, and brackish groundwater while quantifying joint uncertainty inherited from the geophysical data and interpretational relations. Saline and fresh regions are mapped with relatively high confidence in many locations, while areas of lower confidence, particularly at depth, can be mapped as their most probable salinity category while reflecting the relative uncertainty in the interpretation. These maps identify a stratified salinity structure, where saline water commonly occurs in the surficial aquifer overlying fresher groundwater in the Tulare aquifer, separated by regional confining clay layers. Downgradient of unlined surface water diversions, recharge of imported surface water results in relatively fresh groundwater throughout the depth of investigation.</p></div>","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026273","usgsCitation":"Ball, L.B., Davis, T., Minsley, B.J., Gillespie, J., and Landon, M.K., 2020, Probabilistic categorical groundwater salinity mapping from airborne electromagnetic data adjacent to California’s Lost Hills and Belridge oil fields: Water Resources Research, v. 56, no. 6, e2019WR026273, 20 p., https://doi.org/10.1029/2019WR026273.","productDescription":"e2019WR026273, 20 p.","ipdsId":"IP-111364","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":457439,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr026273","text":"Publisher Index Page"},{"id":437063,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90SWJAV","text":"USGS data release","linkHelpText":"Supporting groundwater salinity data used for salinity mapping adjacent to the Lost Hills and Belridge oil fields, Kern County, California"},{"id":437062,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G44PKR","text":"USGS data release","linkHelpText":"Airborne electromagnetic and magnetic survey, southwestern San Joaquin Valley near Lost Hills, California, 2016"},{"id":379689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.564208984375,\n              35.380092992092145\n            ],\n            [\n              -118.597412109375,\n              35.380092992092145\n            ],\n            [\n              -118.597412109375,\n              35.96022296929667\n            ],\n            [\n              -119.564208984375,\n              35.96022296929667\n            ],\n            [\n              -119.564208984375,\n              35.380092992092145\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":802731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":802733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":802734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802735,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209822,"text":"70209822 - 2020 - Dust deposited on snow cover in the San Juan Mountains, Colorado, 2011-2016: Compositional variability bearing on snow-melt effects","interactions":[],"lastModifiedDate":"2020-04-30T11:28:31.936528","indexId":"70209822","displayToPublicDate":"2020-03-10T06:21:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2308,"text":"Journal of Geological Research","active":true,"publicationSubtype":{"id":10}},"title":"Dust deposited on snow cover in the San Juan Mountains, Colorado, 2011-2016: Compositional variability bearing on snow-melt effects","docAbstract":"Light-absorbing particles in atmospheric dust deposited on snow cover (dust-on-snow, DOS) diminish albedo and accelerate the timing and rate of snow melt. Identification of these particles and their effects are relevant to snow-radiation modeling and thus water-resource management. Laboratory-measured reflectance of DOS samples from the San Juan Mountains (USA) were compared with DOS mass loading, particle sizes, iron mineralogy, carbonaceous matter type and content, and chemical compositions. Samples were collected each spring for water years 2011-2016, when individual dust layers had merged into one (all layers merged) at the snow surface. Average reflectance values of the six samples were 0.2153 (sd, 0.0331) across the visible wavelength region (0.4-0.7 µm) and 0.3570 (sd, 0.0498) over the full-measurement range (0.4-2.50 µm). Reflectance values correlated inversely to concentrations of ferric oxide, organic carbon (1.4-10 wt. %), magnetite (0.05-0.13 wt. %), and silt (PM63-3.9; median grain sizes averaged 21.4 µm) but lacked correspondence to total iron and PM10 contents.  Measurements of reflectance and Mössbauer spectra and magnetic properties indicated that microcrystalline hematite and nano-size goethite were primarily responsible for diminished visible reflectance. Positive correlations between organic carbon and metals attributed to fossil-fuel combustion, with observations from electron microscopy, indicated that some carbonaceous matter occurred as black carbon. Magnetite was a surrogate for related light-absorbing minerals, dark rock particles, and contaminants.  Similar analyses of DOS from other areas would help evaluate the influences of varied dust sources, wind-storm patterns, and anthropogenic inputs on snow melt and water resources in and beyond the Colorado River basin.","language":"English","publisher":"Wiley","doi":"10.1029/2019JD032210","collaboration":"","usgsCitation":"Reynolds, R.L., Goldstein, H.L., Moskowitz, B.M., Kokaly, R.F., Munson, S.M., Solheid, P., Breit, G.N., Lawrence, C.R., and Derry, J., 2020, Dust deposited on snow cover in the San Juan Mountains, Colorado, 2011-2016: Compositional variability bearing on snow-melt effects: Journal of Geological Research, v. 125, no. 7, e2019JD032210, 24 p., https://doi.org/10.1029/2019JD032210.","productDescription":"e2019JD032210, 24 p.","ipdsId":"IP-114213","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457449,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jd032210","text":"Publisher Index Page"},{"id":437065,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RGQ9KX","text":"USGS data release","linkHelpText":"Data for Dust deposited on snow cover in the San Juan Mountains, Colorado, 2011-2016: Compositional variability bearing on snow-melt effects"},{"id":374391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.5888671875,\n              37.020098201368114\n            ],\n            [\n              -105.908203125,\n              37.020098201368114\n            ],\n            [\n              -105.908203125,\n              38.58252615935333\n            ],\n            [\n              -108.5888671875,\n              38.58252615935333\n            ],\n            [\n              -108.5888671875,\n              37.020098201368114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":139068,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":788163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":807,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":788164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moskowitz, Bruce M.","contributorId":191599,"corporation":false,"usgs":false,"family":"Moskowitz","given":"Bruce","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":788165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":788166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":788167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Solheid, Peat","contributorId":224401,"corporation":false,"usgs":false,"family":"Solheid","given":"Peat","email":"","affiliations":[{"id":40874,"text":"Institute for Rock Magnetism, Department of Earth and Environmental Sciences, University of Minnesota, Minneapolis","active":true,"usgs":false}],"preferred":false,"id":788168,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":788169,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":788170,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Derry, Jeff","contributorId":224402,"corporation":false,"usgs":false,"family":"Derry","given":"Jeff","email":"","affiliations":[{"id":40875,"text":"Center for Snow and Avalanche Studies","active":true,"usgs":false}],"preferred":false,"id":788171,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70209115,"text":"70209115 - 2020 - Post-release monitoring of a stranded and rehabilitated short-finned pilot whale (Globicephala macrorhynchus) reveals current-assisted travel","interactions":[],"lastModifiedDate":"2020-03-17T15:59:21","indexId":"70209115","displayToPublicDate":"2020-03-09T15:56:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":869,"text":"Aquatic Mammals","active":true,"publicationSubtype":{"id":10}},"title":"Post-release monitoring of a stranded and rehabilitated short-finned pilot whale (Globicephala macrorhynchus) reveals current-assisted travel","docAbstract":"A subadult female short-finned pilot whale (Globicephala macrorhynchus), stranded on the northeastern Gulf of Mexico coast of Florida in June 2017, was rehabilitated for 38 days and then monitored with a satellite-linked, time-depth recording tag for 32 days after being released off the West Florida Shelf.  The individual, “Gale,” appeared to regularly use ocean currents to facilitate a southeastward movement around Florida, and then a northward movement along the continental shelf break to the waters off Cape Hatteras, North Carolina.  Indeed, 57% of her travel along the coast of Florida was at speeds consistent with the surface speed and direction of the Gulf Stream.  Overall, current-assisted travel contributed to a 19% increase in distance traveled (4,152 km), and to an average rate of travel (130 km·day-1) that was higher than previously reported for Globicephala spp.  Gale’s dive behavior was typical of other short-finned pilot whale observations, with average dive depths (243 ± 136 m, max = 712 m) and durations (7.9 ± 2.2 min, max = 16.0 min) within the range of reported values for Globicephala spp.  Gale also occupied habitats known to be used by pilot whales, and her movements and behaviors were consistent with those observed in other short-finned pilot whales in the Gulf of Mexico and northwestern Atlantic Ocean.  The information presented here contributes to a better understanding of short-finned pilot whales, and to the assessment of rehabilitation and release protocols.","language":"English","publisher":"Aquatic Mammals ","doi":"10.1578/AM.46.2.2020.200","usgsCitation":"Tyson Moore, R.B., Douglas, D., Nollens, H.H., and Wells, R.S., 2020, Post-release monitoring of a stranded and rehabilitated short-finned pilot whale (Globicephala macrorhynchus) reveals current-assisted travel: Aquatic Mammals, v. 46, no. 2, p. 200-214, https://doi.org/10.1578/AM.46.2.2020.200.","productDescription":"14 p.","startPage":"200","endPage":"214","ipdsId":"IP-106503","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":373327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.978515625,\n              30.372875188118016\n            ],\n            [\n              -86.044921875,\n              26.352497858154024\n            ],\n            [\n              -80.33203125,\n              23.96617587126503\n            ],\n            [\n              -78.486328125,\n              25.562265014427492\n            ],\n            [\n              -75.322265625,\n              28.536274512989916\n            ],\n            [\n              -74.00390625,\n              33.063924198120645\n            ],\n            [\n              -75.234375,\n              36.24427318493909\n            ],\n            [\n              -76.9921875,\n              35.17380831799959\n            ],\n            [\n              -82.001953125,\n              32.24997445586331\n            ],\n            [\n              -87.978515625,\n              30.372875188118016\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tyson Moore, Reny B","contributorId":223405,"corporation":false,"usgs":false,"family":"Tyson Moore","given":"Reny","email":"","middleInitial":"B","affiliations":[{"id":37712,"text":"Chicago Zoological Society’s Sarasota Dolphin Research Program","active":true,"usgs":false}],"preferred":false,"id":784970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":784969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nollens, Hendrik H.","contributorId":223406,"corporation":false,"usgs":false,"family":"Nollens","given":"Hendrik","email":"","middleInitial":"H.","affiliations":[{"id":40712,"text":"SeaWorld of California","active":true,"usgs":false}],"preferred":false,"id":784971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wells, Randall S.","contributorId":208091,"corporation":false,"usgs":false,"family":"Wells","given":"Randall","email":"","middleInitial":"S.","affiliations":[{"id":37712,"text":"Chicago Zoological Society’s Sarasota Dolphin Research Program","active":true,"usgs":false}],"preferred":false,"id":784972,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70211211,"text":"70211211 - 2020 - Life-history plasticity and water-use trade-offs associated with drought resistance in a clade of California jewelflowers","interactions":[],"lastModifiedDate":"2020-07-20T12:53:35.734273","indexId":"70211211","displayToPublicDate":"2020-03-09T13:50:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5500,"text":"The American Naturalist","onlineIssn":"1537-5323","printIssn":" 0003-014","active":true,"publicationSubtype":{"id":10}},"title":"Life-history plasticity and water-use trade-offs associated with drought resistance in a clade of California jewelflowers","docAbstract":"<p><span>Water limitation is a primary driver of plant geographic distributions and individual plant fitness. Drought resistance is the ability to survive and reproduce despite limited water, and numerous studies have explored its physiological basis in plants. However, it is unclear how drought resistance and trade-offs associated with drought resistance evolve within plant clades. We quantified the relationship between water availability and fitness for 13 short-lived plant taxa in the&nbsp;</span><i>Streptanthus</i><span>&nbsp;clade that vary in their phenology and the availability of water in the environments where they occur. We derived two parameters from these relationships: plant fitness when water is not limiting and the water inflection point (WIF), the watering level at which additional water is most efficiently turned into fitness. We used phylogenetic comparative methods to explore trade-offs related to drought resistance and trait plasticity and the degree to which water relationship parameters are conserved. Taxa from drier climates produced fruits at the lowest water levels, had a lower WIF, flowered earlier, had shorter life spans, had greater plastic water-use efficiency (WUE), and had lower fitness at nonlimiting water. In contrast, later-flowering&nbsp;</span><i>Streptanthus</i><span>&nbsp;taxa from less xeric climates experienced high fitness at nonlimiting water but had no fitness at the lowest water levels. Across the clade, we found a trade-off between drought resistance and fitness at high water, though a single ruderal species was an outlier in this relationship. Our results suggest that drought escape trades off with maximal fitness under nonlimiting water, and both are tied to phenology. We also found that variation in trait plasticity determines how different plant species produce fitness over a water gradient.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/707371","usgsCitation":"Pearse, I.S., Aguilar, J., and Strauss, S., 2020, Life-history plasticity and water-use trade-offs associated with drought resistance in a clade of California jewelflowers: The American Naturalist, v. 195, p. 691-704, https://doi.org/10.1086/707371.","productDescription":"14 p.","startPage":"691","endPage":"704","ipdsId":"IP-106442","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":376486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70206443,"text":"sir20195126 - 2020 - Quantification of trace element loading in the upper Tenmile Creek drainage basin near Rimini, Montana, September 2011","interactions":[],"lastModifiedDate":"2022-04-25T19:23:41.910347","indexId":"sir20195126","displayToPublicDate":"2020-03-09T11:14:43","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5126","displayTitle":"Quantification of Trace-Element Loading in the Upper Tenmile Creek Drainage Basin near Rimini, Montana, September 2011","title":"Quantification of trace element loading in the upper Tenmile Creek drainage basin near Rimini, Montana, September 2011","docAbstract":"<p>The principle sources of trace elements entering upper Tenmile Creek, Montana, during September 2011, four trace metals and the metalloid arsenic, were identified and quantified by combining and analyzing streamflow data determined from tracer injection with trace-element concentrations and related water-quality data determined from synoptic sampling. The study reach was along upper Tenmile Creek, beginning downstream from the city of Helena’s diversion and extending 5,020 feet downstream. Results from the 2011 study, completed by the U.S. Geological Survey in cooperation with the Montana Department of Environmental Quality, were compared to results from a similar study conducted in 1998 to assess the effectiveness of mine reclamation and remediation work to reduce trace-element loading to upper Tenmile Creek, which has been ongoing throughout the drainage basin.</p><p>Main-stem concentrations of most trace elements analyzed were generally greater in 1998 than in 2011. However, the State of Montana human-health criteria for total-recoverable cadmium and arsenic were exceeded in parts of upper Tenmile Creek, and concentrations of cadmium and zinc exceeded the acute aquatic-life criteria at all main-stem sites during both studies. Total-recoverable copper concentrations observed in 2011 exceeded the chronic aquatic-life criterion upstream from the Lee Mountain adit, whereas, in 1998, all sites exceeded the acute aquatic-life criteria.</p><p>Direct comparison of loads from the 1998 and 2011 tracer studies were complicated by the differences in hydrologic conditions. Streamflow in 1998 was about 10 percent of the 2011 streamflow. The Lee Mountain Mine and Susie Lode adit were identified as major contributors of trace elements to upper Tenmile Creek in both studies. However, trace-element loading from the Lee Mountain Mine area was substantially reduced between 1998 and 2011. Total-recoverable loads of all trace elements showed substantial loss in 1998 but increased in 2011 downstream from the Susie Lode adit to the end of the study reach. This reach was one of the primary sources of trace-element loading to upper Tenmile Creek in 2011. This difference indicated that the streambed may act as a sink or a source for trace elements, depending on hydrologic conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195126","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"Cleasby, T., and Eldridge, S.L.C., 2020, Quantification of trace element loading in the upper Tenmile Creek drainage basin near Rimini, Montana, September 2011: U.S. Geological Survey Scientific Investigations Report 2019–5126, 40 p., https://doi.org/10.3133/sir20195126.","productDescription":"Report: vii, 40 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-043897","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":399607,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109755.htm"},{"id":372808,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System database","linkHelpText":"– USGS water data for the Nation"},{"id":372807,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5126/sir20195126.pdf","text":"Report","size":"6.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5126"},{"id":372806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5126/coverthb.jpg"}],"country":"United States","state":"Montana","county":"Lewis and Clark County","city":"Rimini","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.2533,\n              46.4808\n            ],\n            [\n              -112.2444,\n              46.4808\n            ],\n            [\n              -112.2444,\n              46.5008\n            ],\n            [\n              -112.2533,\n              46.5008\n            ],\n            [\n              -112.2533,\n              46.4808\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/wy-mt-water\" href=\"https://www.usgs.gov/centers/wy-mt-water\">Wyoming-Montana Water Science Center</a><br>U.S. Geological Survey<br>3162 Bozeman Avenue<br>Helena, MT 59601<br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Quality Assurance/Quality Control</li><li>Quantification of Trace-Element Loading</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-03-09","noUsgsAuthors":false,"publicationDate":"2020-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Cleasby, Tom 0000-0003-0694-1541 tcleasby@usgs.gov","orcid":"https://orcid.org/0000-0003-0694-1541","contributorId":1137,"corporation":false,"usgs":true,"family":"Cleasby","given":"Tom","email":"tcleasby@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":774563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell Eldridge, Sara L. 0000-0001-8838-8940 seldridge@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-8940","contributorId":4981,"corporation":false,"usgs":true,"family":"Caldwell Eldridge","given":"Sara","email":"seldridge@usgs.gov","middleInitial":"L.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":774564,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208134,"text":"ofr20201003 - 2020 - Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama","interactions":[],"lastModifiedDate":"2022-04-21T20:32:11.498263","indexId":"ofr20201003","displayToPublicDate":"2020-03-09T09:04:23","publicationYear":"2020","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":"2020-1003","displayTitle":"Predicting Barrier Island Habitats and Oyster and Seagrass Habitat Suitability for Various Restoration Measures and Future Conditions for Dauphin Island, Alabama","title":"Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama","docAbstract":"<p>Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors.</p><p>Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case.</p><p>The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201003","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and in collaboration with the State of Alabama and the National Fish and Wildlife Foundation","usgsCitation":"Enwright, N.M., Wang, H., Dalyander, P.S., and Godsey, E., eds., 2020, Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama: U.S. Geological Survey Open-File Report 2020–1003, 99 p.,  https://doi.org/10.3133/ofr20201003.","productDescription":"Report: x, 99 p.; 3 Data Releases","numberOfPages":"114","onlineOnly":"Y","ipdsId":"IP-113342","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":372971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1003/ofr20201003.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1003"},{"id":372973,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O30XMZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Oyster habitat suitability modeling for the Alabama Barrier Island restoration assessment at Dauphin Island"},{"id":399449,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109756.htm"},{"id":372974,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B32VTE","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Seagrass habitat suitability modeling for the Alabama Barrier Island restoration assessment at Dauphin Island"},{"id":372972,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PK0EH0","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Landscape position-based habitat modeling for the Alabama Barrier Island feasibility assessment at Dauphin Island"},{"id":372970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1003/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.341064453125,\n              30.166500980766052\n            ],\n            [\n              -88.0389404296875,\n              30.166500980766052\n            ],\n            [\n              -88.0389404296875,\n              30.311245603935003\n            ],\n            [\n              -88.341064453125,\n              30.311245603935003\n            ],\n            [\n              -88.341064453125,\n              30.166500980766052\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc\" data-mce-href=\"https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc\">Wetland and Aquatic Research Center</a> <br>U.S. Geological Survey <br>700 Cajundome Blvd. <br>Lafayette, LA 70506</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Chapter A. Landscape-Position-Based Habitat Modeling for the Alabama Barrier Island Restoration Feasibility Assessment at Dauphin Island</li><li>Chapter B. Oyster Habitat Suitability Modeling for the Alabama Barrier Island Restoration Feasibility Assessment at Dauphin Island</li><li>Chapter C. Seagrass Habitat Suitability Modeling for the Alabama Barrier Island Restoration Feasibility Assessment at Dauphin Island</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-03-09","noUsgsAuthors":false,"publicationDate":"2020-03-09","publicationStatus":"PW","contributors":{"editors":[{"text":"Enwright, Nicholas  M. 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":202150,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas  M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":784073,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":215073,"corporation":false,"usgs":false,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":784074,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872 sdalyander@usgs.gov","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":141015,"corporation":false,"usgs":true,"family":"Dalyander","given":"P.","email":"sdalyander@usgs.gov","middleInitial":"Soupy","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":784075,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Godsey, Elizabeth 0000-0003-4621-7857","orcid":"https://orcid.org/0000-0003-4621-7857","contributorId":222094,"corporation":false,"usgs":false,"family":"Godsey","given":"Elizabeth","email":"","affiliations":[{"id":34200,"text":"Army Corp of Engineers","active":true,"usgs":false}],"preferred":false,"id":784076,"contributorType":{"id":2,"text":"Editors"},"rank":4}]}}
,{"id":70227752,"text":"70227752 - 2020 - A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin","interactions":[],"lastModifiedDate":"2022-04-15T16:17:24.763904","indexId":"70227752","displayToPublicDate":"2020-03-06T11:02:45","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9366,"text":"CCAST Case Study on Actionable Science","active":true,"publicationSubtype":{"id":1}},"title":"A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin","docAbstract":"<p dir=\"ltr\"><span>Management of water resources in the transboundary Rio Grande/Río Bravo Basin (the Basin) presents challenges for state and Federal entities in the United States and Mexico making management decisions on shared water resources. Damming, channelization, water availability, and allocation are governed by water rights and water-sharing agreements. Data and information sharing are important aspects of transboundary cooperation, but differences in format, content, spatial and temporal resolution, and language hinder collaboration. In addition, data on the kinds and geographic distribution of water governance and management institutions across the Basin have not been consistently documented. Existing data disparities parallel the hydrological and social fragmentation of the Basin.</span></p><p><span>Seeking to underscore the interdependence between social and environmental processes in the Basin, anthropologists and modelers collaborated to develop a socio-environmental geodatabase. This geodatabase is a first step in modeling the social components of decision making and their connectivity to environmental processes across the Basin. The geodatabase is available in an open-access domain and contains geospatial data related to water and land governance, hydrology, water use and hydraulic infrastructure, socioeconomics, and the biophysical environment necessary to advance the understanding of basin dynamics. Having these data documented and compiled in a central location serves as a resource to help decision makers better understand upstream and downstream social-environmental characteristics. This knowledge is useful for developing sustainable water management policies in a region where water resources are increasingly under pressure from climatic, environmental, and human-related changes.</span></p>","language":"English","publisher":"Collaborative Conservation and Adaptation Strategy Toolbox (CCAST)","usgsCitation":"Villa, J., 2020, A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin: CCAST Case Study on Actionable Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123961","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":398832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395033,"type":{"id":15,"text":"Index Page"},"url":"https://arcg.is/0bava9"}],"country":"Mexico, United States","state":"Chihuahua, New Mexico, Texas","otherGeospatial":"Rio Grande/Río Bravo basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.12493896484374,\n              31.421631960419596\n            ],\n            [\n              -105.90545654296875,\n              31.421631960419596\n            ],\n            [\n              -105.90545654296875,\n              32.58384932565662\n            ],\n            [\n              -107.12493896484374,\n              32.58384932565662\n            ],\n            [\n              -107.12493896484374,\n              31.421631960419596\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Villa, Jennifer 0000-0002-4774-7166","orcid":"https://orcid.org/0000-0002-4774-7166","contributorId":245824,"corporation":false,"usgs":true,"family":"Villa","given":"Jennifer","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832043,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208975,"text":"70208975 - 2020 - Storm impacts on phytoplankton community dynamics in lakes","interactions":[],"lastModifiedDate":"2020-09-01T13:54:15.589491","indexId":"70208975","displayToPublicDate":"2020-03-05T18:33:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Storm impacts on phytoplankton community dynamics in lakes","docAbstract":"In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15033","usgsCitation":"Stockwell, J.D., Doubek, J.P., Adrian, R., Anneville, O., Carey, C.C., Carvalho, L., Frassl, M.A., Domis, L.N., Grossart, H., Dur, G., Ibelings, B.W., Lajeunesse, M.J., Lewandowska, A.M., Llames, M.E., Matsuzaki, S.S., Nodine, E., Noges, P., Patil, V.P., Pomati, F., Rinke, K., Rudstam, L.G., Rusak, J.A., Salmaso, N., Seltmann, C.T., Straile, D., Thackeray, S.J., Thiery, W., Urrutia-Cordero, P., Venail, P., Verburg, P., Woolway, R., Zohary, T., Andersen, M., Bhattacharya, R., Hejzlar, J., Janatian, N., Kpodonu, A.T., Williamson, T.J., and Wilson, H., 2020, Storm impacts on phytoplankton community dynamics in lakes: Global Change Biology, v. 26, no. 5, p. 2756-2784, https://doi.org/10.1111/gcb.15033.","productDescription":"29 p.","startPage":"2756","endPage":"2784","ipdsId":"IP-110107","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":457484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15033","text":"Publisher Index Page"},{"id":373036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":784246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doubek, Jonathan P.","contributorId":223151,"corporation":false,"usgs":false,"family":"Doubek","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":784291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adrian, Rita 0000-0002-6318-7189","orcid":"https://orcid.org/0000-0002-6318-7189","contributorId":166831,"corporation":false,"usgs":false,"family":"Adrian","given":"Rita","email":"","affiliations":[{"id":24542,"text":"Department of Ecosystem Research, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 301, D- 12587 Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":784292,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anneville, Orlane","contributorId":166833,"corporation":false,"usgs":false,"family":"Anneville","given":"Orlane","email":"","affiliations":[{"id":24544,"text":"National Institute for Agricultural Research (INRA), UMR Centre Alpin de Recherche sur les Réseaux Trophiques des Ecosystèmes Limniques (CARRTEL), 74200 Thonon-Les-Bains, France","active":true,"usgs":false}],"preferred":false,"id":784293,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":784294,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carvalho, Laurence","contributorId":197238,"corporation":false,"usgs":false,"family":"Carvalho","given":"Laurence","email":"","affiliations":[],"preferred":false,"id":784295,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Frassl, Marieke A.","contributorId":223153,"corporation":false,"usgs":false,"family":"Frassl","given":"Marieke","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":784298,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Domis, Lisette N. De Senerpont","contributorId":71448,"corporation":false,"usgs":true,"family":"Domis","given":"Lisette","email":"","middleInitial":"N. De Senerpont","affiliations":[],"preferred":false,"id":784296,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dur, Gael","contributorId":223152,"corporation":false,"usgs":false,"family":"Dur","given":"Gael","email":"","affiliations":[],"preferred":false,"id":784297,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ibelings, Bas W","contributorId":130973,"corporation":false,"usgs":false,"family":"Ibelings","given":"Bas","email":"","middleInitial":"W","affiliations":[{"id":7189,"text":"Institut F.A. 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Michele all’Adige (Trento), Italy","active":true,"usgs":false}],"preferred":false,"id":784396,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Seltmann, Christian T.","contributorId":223157,"corporation":false,"usgs":false,"family":"Seltmann","given":"Christian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":784397,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Straile, Dietmar","contributorId":150309,"corporation":false,"usgs":false,"family":"Straile","given":"Dietmar","email":"","affiliations":[{"id":17983,"text":"Department of Biology, Universitat Konstanz, Konstanz, Germany","active":true,"usgs":false}],"preferred":false,"id":784398,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Thackeray, Stephen J.","contributorId":197253,"corporation":false,"usgs":false,"family":"Thackeray","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":784399,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Thiery, Wim","contributorId":223158,"corporation":false,"usgs":false,"family":"Thiery","given":"Wim","email":"","affiliations":[],"preferred":false,"id":784400,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Urrutia-Cordero, Pablo","contributorId":223159,"corporation":false,"usgs":false,"family":"Urrutia-Cordero","given":"Pablo","email":"","affiliations":[],"preferred":false,"id":784401,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Venail, Patrick","contributorId":48806,"corporation":false,"usgs":true,"family":"Venail","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":784402,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Verburg, Piet","contributorId":150311,"corporation":false,"usgs":false,"family":"Verburg","given":"Piet","email":"","affiliations":[{"id":17985,"text":"National Institute of Water and Atmospheric Research, Hamilton, New Zealand","active":true,"usgs":false}],"preferred":false,"id":784403,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Woolway, R. 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,{"id":70206596,"text":"pp1863 - 2020 - Groundwater characterization and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole","interactions":[],"lastModifiedDate":"2022-04-22T19:10:54.810814","indexId":"pp1863","displayToPublicDate":"2020-03-05T09:14:28","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1863","displayTitle":"Groundwater Characterization and Effects of Pumping in the Death Valley Regional Groundwater Flow System, Nevada and California, with Special Reference to Devils Hole","title":"Groundwater characterization and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole","docAbstract":"<p class=\"p1\">Groundwater flow and development were characterized <span class=\"s1\">in four groundwater basins of the Death Valley regional </span>flow system in Nevada and California with calibrated, groundwater-flow models. Natural groundwater discharges <span class=\"s1\">in the Furnace Creek, Lower Amargosa, and Saratoga </span>Spring areas were defined and distributed consistently with a revised hydrogeologic framework. This simplified <span class=\"s1\">hydrogeologic framework was limited to four hydraulically </span>unique, hydrogeologic units: (1) basin fill; (2) carbonate rocks; (3) volcanic rocks; and (4) low-permeability granitic and siliciclastic rocks. Hydrogeologic units and division of carbonate and volcanic rocks between shallow and deep were supported by results from 271 aquifer tests and specific-capacity estimates. Greater than 90 percent of field-estimated transmissivity occurred within 1,600 feet (ft) of the water table. Pumping in the study area from 1960 to 2010 averaged <span class=\"s1\">46,000 acre-feet per year (acre-ft/yr), which is 80 percent of </span>the predevelopment discharge. The central Amargosa Desert <span class=\"s1\">and Pahrump Valley were the two primary pumping centers </span>and measurably affected water levels across 900 square miles <span class=\"s1\">in 2018.</span></p><p class=\"p1\">Water levels in <i>Devils Hole </i><span class=\"s1\">were a special focus because </span>endangered Devils Hole pupfish (<i>Cyprinodon diabolis</i><span class=\"s1\">) are </span>affected by water-level declines. Pumping 42,100 acre-ft by <span class=\"s1\">Cappaert Enterprises, formerly Spring Meadows, Inc., caused </span>a 2.3-ft water-level decline in <i>Devils Hole</i><span class=\"s1\">, which temporarily </span>reduced habitat of Devils Hole pupfish by 85 percent in 1972. If no pumping occurred, water levels in <i>Devils Hole </i><span class=\"s1\">would </span>have risen naturally about 1 ft between 1973 and 2018 from temporal variations in recharge. The 2.6-ft range of measured water-level changes in <i>Devils Hole </i><span class=\"s1\">was simulated with a root-mean-square error of 0.2 ft during the 70-year period of </span>record. Simulated water-level declines from pumping totaled <span class=\"s1\">1.4 ft in 2018, with 25 and 34 percent attributed to pumping by Cappaert Enterprises and the central Amargosa Desert, </span>respectively. Water levels in <i>Devils Hole </i><span class=\"s1\">will decline at rates of 0.1–0.2 ft per decade if pumping from Ash Meadows groundwater basin and the central Amargosa Desert </span>continue at current rates. Effects of future natural water-level fluctuations remain unknown.</p><p class=\"p2\">Ash Meadows and Alkali Flat–Furnace Creek Ranch groundwater basins are hydraulically connected near well <span class=\"s2\"><i>AD-4</i></span>, about 5 miles south of the town of Amargosa Valley, <span class=\"s2\">Nevada. About 40 percent of the discharge from the Furnace </span>Creek area is recharged in the Ash Meadows groundwater <span class=\"s2\">basin. Basin fill in the central Amargosa Desert hydraulically </span>connects carbonate rocks east of well <span class=\"s2\"><i>AD-4 </i></span>with saturated carbonate rocks in the Funeral Range. About 7 percent of the 960,000 acre-ft pumped from Ash Meadows and Alkali Flat–Furnace Creek Ranch groundwater basins prior to 2019 was captured discharge from springs and phreatophytes. Greater than 40 percent of the 2,080,000 acre-ft pumped from Pahrump Valley between 1910 and 2019 was capture that primarily discharged from <span class=\"s2\"><i>Bennetts and Manse </i></span>Springs.</p><p class=\"p3\">Simulated advective-flow distances and velocities from underground nuclear tests are within the range of advective transport calculations from tritium data and previous radionuclide transport investigations. Boundary conditions and flow rates from the regional model in this study are plausible for local-scale flow and radionuclide transport models. Simulated 165-year groundwater-flow paths do not extend into pumping areas and effects of regional pumping on advective transport are negligible.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1863","collaboration":"Prepared in cooperation with the U.S. Department of Energy Office of Environmental Management, National Nuclear Security Administration, Nevada Site Office, under Interagency Agreement DE-EM0004969","usgsCitation":"Halford, K.J., and Jackson, T.R., 2020, Groundwater characterization and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole: U.S. Geological Survey Professional Paper 1863, 178 p., https://doi.org/10.3133/pp1863.","productDescription":"Report: xvi, 178 p.; Data Release","ipdsId":"IP-105994","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":372815,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HIYVG2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005 model and supplementary data used to characterize groundwater flow and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole"},{"id":399508,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109738.htm"},{"id":372814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1863/pp1863.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1863"},{"id":372813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1863/coverthb2.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley, Devils Hole","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117,\n              35.6464\n            ],\n            [\n              -115.0611,\n              35.6464\n            ],\n            [\n              -115.0611,\n              37.7214\n            ],\n            [\n              -117,\n              37.7214\n            ],\n            [\n              -117,\n              35.6464\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br>U.S. Geological Survey<br>2730 N. Deer Run Road<br>Carson City, Nevada 89701</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Geology</li><li>Interbasin Flow Between Groundwater Basins</li><li>Predevelopment Groundwater Flow</li><li>Groundwater Development</li><li>Integrated Estimation of Recharge and Hydraulic-Property Distributions with Numerical Models</li><li>Simulated Predevelopment Groundwater Flow</li><li>Effects of Groundwater Development</li><li>Potential Effects of Future Groundwater Development</li><li>Groundwater-Basin Boundary Uncertainty</li><li>Evaluation of Advective Flow from Corrective Action Units</li><li>Model Limitations</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-03-05","noUsgsAuthors":false,"publicationDate":"2020-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Halford, Keith J. 0000-0002-7322-1846 khalford@usgs.gov","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":1374,"corporation":false,"usgs":true,"family":"Halford","given":"Keith","email":"khalford@usgs.gov","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, Tracie R. 0000-0001-8553-0323 tjackson@usgs.gov","orcid":"https://orcid.org/0000-0001-8553-0323","contributorId":150591,"corporation":false,"usgs":true,"family":"Jackson","given":"Tracie","email":"tjackson@usgs.gov","middleInitial":"R.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":775092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70249715,"text":"70249715 - 2020 - Fundamental hydraulics of cross sections in natural rivers: Preliminary analysis of a large data set of acoustic doppler flow measurements","interactions":[],"lastModifiedDate":"2023-10-25T12:14:01.11108","indexId":"70249715","displayToPublicDate":"2020-03-05T07:07:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11438,"text":"Water Resource Research","active":true,"publicationSubtype":{"id":10}},"title":"Fundamental hydraulics of cross sections in natural rivers: Preliminary analysis of a large data set of acoustic doppler flow measurements","docAbstract":"<div class=\"article-section__content en main\"><p>We have assembled a comprehensive and publicly accessible U.S. Geological Survey (USGS) streamflow measurement data set, called HYDRoSWOT, from a USGS National Water Information System archive of acoustic Doppler current profiler river discharge measurements collected from a wide range of rivers throughout the United States. The data set provides a wealth of information on the range of hydraulic characteristics of river cross sections in the United States. Preliminary exploration of the data set, filtered for quality control, indicates that rivers tend toward consistent and predictable forms as discharge increases. The ratio of maximum-to-mean depth is highly predictable and is remarkably consistent across all river sizes and discharges. Distributions of hydraulic characteristics provide a large-scale perspective on the general hydraulic characteristics of rivers. The data set affords the opportunity to analyze hydraulic relations for individual rivers as a function of stage, geomorphic setting, and energy environments and, combined with additional information contained in this data set, might yield predictive relations that could help constrain and parameterize river hydraulic models.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025986","usgsCitation":"Bjerklie, D.M., Fulton, J.W., Dingman, S.L., Canova, M.G., Minear, J.T., and Moramarco, T., 2020, Fundamental hydraulics of cross sections in natural rivers: Preliminary analysis of a large data set of acoustic doppler flow measurements: Water Resource Research, v. 56, no. 3, e2019WR025986, 8 p., https://doi.org/10.1029/2019WR025986.","productDescription":"e2019WR025986, 8 p.","ipdsId":"IP-108842","costCenters":[{"id":466,"text":"New England Water Science 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,{"id":70208487,"text":"sir20205012 - 2020 - Estimates of water use associated with continuous oil and gas development in the Williston Basin, North Dakota and Montana, 2007–17","interactions":[],"lastModifiedDate":"2022-04-25T21:42:26.20684","indexId":"sir20205012","displayToPublicDate":"2020-03-04T14:44:16","publicationYear":"2020","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":"2020-5012","displayTitle":"Estimates of Water Use Associated with Continuous Oil and Gas Development in the Williston Basin, North Dakota and Montana, 2007–17","title":"Estimates of water use associated with continuous oil and gas development in the Williston Basin, North Dakota and Montana, 2007–17","docAbstract":"<p>This study of water use associated with development of continuous oil and gas resources in the Williston Basin is intended to provide a preliminary model-based analysis of water use in major regions of production of continuous oil and gas resources in the United States. Direct, indirect, and ancillary water use associated with development of continuous oil and gas resources in the Williston Basin was estimated in North Dakota and Montana from 2007 to 2017. Water-use data were aggregated by county and year, which were the sampling units used in this analysis. Linear and quantile regression models of water use in relation to the number of oil and gas wells developed were fit for the direct, indirect, and ancillary water-use categories for each State. A 95-percent confidence interval for each parameter estimate from the linear regression models was computed as a measure of uncertainty. Additional information on uncertainty can be gained from modeling other distribution parameters, so quantile regression models of the 5th, 50th, and 95th percentiles also were fit. To assess uncertainty in the estimates from the regression models of direct, indirect, and ancillary water use, leave-one-out cross-validation was used. Model performance was evaluated with three goodness-of-fit metrics used to compare the estimates and observations of water use.</p><p>Mean annual direct and indirect water use for development of continuous oil and gas resources in North Dakota was estimated at 4,512 million gallons (Mgal) per year (Mgal/yr), with a 95-percent confidence interval of 4,021–5,152 Mgal/yr, and in Montana was estimated at 196 Mgal/yr, with a 95-percent confidence interval of 189–203 Mgal/yr. Ancillary water use (for domestic and public supply) had an estimated annual mean of 2,753 Mgal/yr in North Dakota and 396 Mgal/yr in Montana. The coefficient from the linear regression model of direct water use was 3.86 Mgal per well and hydraulic fracturing water use was 3.70 Mgal per well for North Dakota. The mean estimate of direct water use had a 95-percent confidence interval of 3.48–4.23 Mgal per well. For North Dakota, the coefficient from the linear regression model of indirect water use was 0.453 Mgal per well, with a 95-percent confidence interval of 0.415–0.492 Mgal per well. Direct and indirect water use had a mean estimate of about 4.31 Mgal per well in North Dakota. The mean estimate of ancillary water use (for domestic and public supply) in North Dakota was 2.03 Mgal per well, with a 95-percent confidence interval of 1.76–2.31 Mgal per well. For Montana, the linear regression model of hydraulic fracturing water use had a mean estimate of 2.04 Mgal per well. The 95-percent confidence interval for the mean estimate was 1.80–2.28 Mgal per well. Direct and indirect water use in Montana had a mean estimate of 2.49 Mgal per well. The mean estimate of ancillary water use (for domestic and public supply) in Montana was 2.43 Mgal per well, with a 95-percent confidence interval of 1.76–3.11 Mgal per well.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205012","collaboration":"Water Availability and Use Science Program","usgsCitation":"McShane, R.R., Barnhart, T.B., Valder, J.F., Haines, S.S., Macek-Rowland, K.M., Carter, J.M., Delzer, G.C., and Thamke, J.N., 2020, Estimates of water use associated with continuous oil and gas development in the Williston Basin, North Dakota and Montana, 2007–17: U.S. Geological Survey Scientific Investigations Report 2020–5012, 26 p., https://doi.org/10.3133/sir20205012","productDescription":"Report: vii, 26 p.; 2 Appendixes; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112448","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":399633,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109737.htm"},{"id":372867,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5012/sir20205012_appendix2.zip","text":"Appendix 2","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2020–5012 Appendix 2","linkHelpText":"– Water-Use Estimates and Coefficients"},{"id":372866,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5012/sir20205012_appendix1.zip","text":"Appendix 1","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2020–5012 Appendix 1","linkHelpText":"– R Scripts"},{"id":372864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5012/coverthb2.jpg"},{"id":372868,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPKRLW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data to Estimate Water Use Associated with Continuous Oil and Gas Development, Williston Basin, United States, 1980-2017 (ver. 2.0, September 2019)"},{"id":372865,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5012/sir20205012.pdf","text":"Report","size":"2.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5012"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.8333,\n              44.8333\n            ],\n            [\n              -99,\n              44.8333\n            ],\n            [\n              -99,\n              49\n            ],\n            [\n              -106.8333,\n              49\n            ],\n            [\n              -106.8333,\n              44.8333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/wy-mt-water/\" href=\"https://www.usgs.gov/centers/wy-mt-water/\">Wyoming-Montana Water Science Center</a><br>U.S. Geological Survey<br>3162 Bozeman Avenue<br>Helena, MT 59601</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods for Analyzing Water Use</li><li>Results of Water-Use Analysis</li><li>Comparisons to Water-Use Estimates from Other Studies</li><li>Limitations of Water-Use Analysis for the Williston Basin</li><li>Summary</li><li>References Cited</li><li>Appendix 1. R Scripts</li><li>Appendix 2. Water-Use Estimates and Coefficients</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-03-04","noUsgsAuthors":false,"publicationDate":"2020-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"McShane, Ryan R. 0000-0002-3128-0039","orcid":"https://orcid.org/0000-0002-3128-0039","contributorId":219009,"corporation":false,"usgs":true,"family":"McShane","given":"Ryan R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":219010,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore","email":"","middleInitial":"B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":220912,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Macek-Rowland, Kathleen M.  0000-0003-2526-6860","orcid":"https://orcid.org/0000-0003-2526-6860","contributorId":219012,"corporation":false,"usgs":true,"family":"Macek-Rowland","given":"Kathleen M. ","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carter, Janet M. 0000-0002-6376-3473","orcid":"https://orcid.org/0000-0002-6376-3473","contributorId":40660,"corporation":false,"usgs":true,"family":"Carter","given":"Janet M.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delzer, Gregory C. 0000-0002-7077-4963","orcid":"https://orcid.org/0000-0002-7077-4963","contributorId":203448,"corporation":false,"usgs":true,"family":"Delzer","given":"Gregory","email":"","middleInitial":"C.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782099,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thamke, Joanna N. 0000-0002-6917-1946 jothamke@usgs.gov","orcid":"https://orcid.org/0000-0002-6917-1946","contributorId":1012,"corporation":false,"usgs":true,"family":"Thamke","given":"Joanna N.","email":"jothamke@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782100,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70208886,"text":"70208886 - 2020 - Changing suspended sediment in United States rivers and streams: Linking sediment trends to changes in land use/cover, hydrology and climate","interactions":[],"lastModifiedDate":"2020-03-04T15:26:04","indexId":"70208886","displayToPublicDate":"2020-03-03T15:25:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Changing suspended sediment in United States rivers and streams: Linking sediment trends to changes in land use/cover, hydrology and climate","docAbstract":"<p><span>Sediment is one of the leading pollutants in rivers and streams across the United States (US) and the world. Between 1992 and 2012, concentrations of annual mean suspended sediment decreased at over half of the 137 stream sites assessed across the contiguous US. Increases occurred at less than 25 % of the sites, and the direction of change was uncertain at the remaining 25 %. Sediment trends were characterized using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model, and decreases in sediment ranged from&nbsp;</span><span class=\"inline-formula\">−95</span><span> % to&nbsp;</span><span class=\"inline-formula\">−8.5</span><span> % of the 1992 concentration. To explore potential drivers of these changes, the sediment trends were (1)&nbsp;parsed into two broad contributors of change, changes in land management versus changes in the streamflow regime, and (2)&nbsp;grouped by land use of the watershed and correlated to concurrent changes in land use or land cover (land use/cover), hydrology and climate variables and static/long-term watershed characteristics. At 83 % of the sites, changes in land management (captured by changes in the concentration–streamflow relationship over time; C–Q relationship) contributed more to the change in the sediment trend than changes in the streamflow regime alone (i.e., any systematic change in the magnitude, frequency or timing of flows). However, at&nbsp;</span><span class=\"inline-formula\">&gt;50</span><span> % of the sites, changes in the streamflow regime contributed at least a 5 % change in sediment, and at 11 sites changes in the streamflow regime contributed over half the change in sediment, indicating that at many sites changes in streamflow were not the main driver of changes in sediment but were often an important supporting factor. Correlations between sediment trends and concurrent changes in land use/cover, hydrology and climate were often stronger at sites draining watersheds with more homogenous, human-related land uses (i.e., agricultural and urban lands) compared to mixed-use or undeveloped lands. At many sites, decreases in sediment occurred despite small-to-moderate increases in the amount of urban or agricultural land in the watershed, suggesting conservation efforts and best-management practices (BMPs) used to reduce sediment runoff to streams may be successful, up to a point, as lands are converted to urban and agricultural uses.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-24-991-2020","usgsCitation":"Murphy, J.C., 2020, Changing suspended sediment in United States rivers and streams: Linking sediment trends to changes in land use/cover, hydrology and climate: Hydrology and Earth System Sciences, v. 24, p. 991-1010, https://doi.org/10.5194/hess-24-991-2020.","productDescription":"20 p.","startPage":"991","endPage":"1010","ipdsId":"IP-105905","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":457510,"rank":0,"type":{"id":40,"text":"Open Access Publisher 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,{"id":70209057,"text":"70209057 - 2020 - Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database","interactions":[],"lastModifiedDate":"2020-03-12T12:52:37","indexId":"70209057","displayToPublicDate":"2020-03-03T12:46:56","publicationYear":"2020","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":"Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database","docAbstract":"The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001-2016.  For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001-2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this time. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4,778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001-2006 at twice the rate of 2011-2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database.","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2020.02.019","usgsCitation":"Homer, C.G., Dewitz, J., Jin, S., Xian, G.Z., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., Stehman, S., Auch, R.F., and Riitters, K.H., 2020, Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database: ISPRS Journal of Photogrammetry and Remote Sensing, v. 162, p. 184-199, https://doi.org/10.1016/j.isprsjprs.2020.02.019.","productDescription":"16 p.","startPage":"184","endPage":"199","ipdsId":"IP-113469","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gass, Leila 0000-0002-3436-262X lgass@usgs.gov","orcid":"https://orcid.org/0000-0002-3436-262X","contributorId":3770,"corporation":false,"usgs":true,"family":"Gass","given":"Leila","email":"lgass@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":784657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Funk, Michelle 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auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784664,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Riitters, Kurt H. 0000-0003-3901-4453","orcid":"https://orcid.org/0000-0003-3901-4453","contributorId":139788,"corporation":false,"usgs":false,"family":"Riitters","given":"Kurt","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":784665,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70210746,"text":"70210746 - 2020 - Legacy and current‐use contaminants in sediments alter macroinvertebrate communities in southeastern US Streams","interactions":[],"lastModifiedDate":"2020-06-23T14:52:36.144242","indexId":"70210746","displayToPublicDate":"2020-03-03T09:48:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Legacy and current‐use contaminants in sediments alter macroinvertebrate communities in southeastern US Streams","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Sediment contamination of freshwater streams in urban areas is a recognized and growing concern. As a part of a comprehensive regional stream‐quality assessment, stream‐bed sediment was sampled from streams spanning a gradient of urban intensity in the Piedmont ecoregion of the southeastern United States. We evaluated relations between a broad suite of sediment contaminants (metals, current‐use pesticides, organochlorine pesticides, polychlorinated biphenyls, brominated diphenyl ethers, and polycyclic aromatic hydrocarbons), ambient sediment toxicity, and macroinvertebrate communities from 76 sites. Sediment toxicity was evaluated by conducting whole‐sediment laboratory toxicity testing with the amphipod<span>&nbsp;</span><i>Hyalella azteca<span>&nbsp;</span></i>(for 28 d) and the midge<span>&nbsp;</span><i>Chironomus dilutus<span>&nbsp;</span></i>(for 10 d). Approximately one‐third of the sediment samples were identified as toxic for at least one test species endpoint, although concentrations of contaminants infrequently exceeded toxicity benchmarks. Ratios of contaminant concentrations relative to their benchmarks, both individually and as summed benchmark quotients, were explored on a carbon‐normalized and a dry‐weight basis. Invertebrate taxa measures from ecological surveys tended to decline with increasing urbanization and with sediment contamination. Toxicity test endpoints were more strongly related to sediment contamination than invertebrate community measures were. Sediment chemistry and sediment toxicity provided moderate and weak, respectively, explanatory power for the similarity/dissimilarity of invertebrate communities. The results indicate that current single‐chemical sediment benchmarks may underestimate the effects from mixtures of sediment contaminants experienced by lotic invertebrates.<span>&nbsp;</span></p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/etc.4705","usgsCitation":"Moran, P.W., Kemble, N.E., Waite, I.R., Mahler, B., Nowell, L.H., and Van Metre, P.C., 2020, Legacy and current‐use contaminants in sediments alter macroinvertebrate communities in southeastern US Streams: Environmental Toxicology and Chemistry, v. 39, no. 6, p. 1219-1232, https://doi.org/10.1002/etc.4705.","productDescription":"14 p.","startPage":"1219","endPage":"1232","ipdsId":"IP-109079","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":375804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, South Carolina, North Carolina, Viriginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.9130859375,\n              32.21280106801518\n            ],\n            [\n              -82.44140625,\n              32.54681317351514\n            ],\n            [\n              -79.5849609375,\n              34.30714385628804\n            ],\n            [\n              -77.0361328125,\n              36.94989178681327\n            ],\n            [\n              -76.9482421875,\n              38.75408327579141\n            ],\n            [\n              -78.3984375,\n              38.44498466889473\n            ],\n            [\n              -80.595703125,\n              36.70365959719456\n            ],\n            [\n              -83.3203125,\n              34.813803317113155\n            ],\n            [\n              -85.78125,\n              33.87041555094183\n            ],\n            [\n              -87.5390625,\n              33.358061612778876\n            ],\n            [\n              -87.36328125,\n              32.509761735919426\n            ],\n            [\n              -85.9130859375,\n              32.21280106801518\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kemble, Nile E. 0000-0002-3608-0538 nkemble@usgs.gov","orcid":"https://orcid.org/0000-0002-3608-0538","contributorId":2626,"corporation":false,"usgs":true,"family":"Kemble","given":"Nile","email":"nkemble@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":791220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791223,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791224,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209416,"text":"70209416 - 2020 - Sea turtle conservation: Priorities for environmental education efforts","interactions":[],"lastModifiedDate":"2020-04-09T15:04:04.292551","indexId":"70209416","displayToPublicDate":"2020-03-03T09:45:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5946,"text":"EDIS","active":true,"publicationSubtype":{"id":10}},"title":"Sea turtle conservation: Priorities for environmental education efforts","docAbstract":"<p><span>All five species of sea turtle that occur in Florida are in danger of extinction.&nbsp; Many of the reasons these turtles are declining are a result of people’s actions on beaches and in shallow waters. Environmental education is needed to increase awareness and appreciation for sea turtles, and to teach about the potential harmful impacts human behaviors can have on these animals. This document describes topics that are frequently misunderstood and discusses common human actions that are harmful to sea turtles, providing insight on which topics could be addressed during environmental education efforts.&nbsp;</span></p>","language":"English","publisher":"UFIFAS Extension","doi":"","collaboration":"","usgsCitation":"Swindall, J.E., Ober, H.K., Lamont, M., and Carthy, R.R., 2020, Sea turtle conservation: Priorities for environmental education efforts: EDIS, v. 2, no. 4, UW46500, 4 p., https://doi.org/.","productDescription":"UW46500, 4 p.","ipdsId":"IP-116612","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":373861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373768,"type":{"id":15,"text":"Index Page"},"url":"https://journals.flvc.org/edis/article/view/117285"}],"country":"United 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Research Center","active":true,"usgs":true}],"preferred":true,"id":786429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carthy, Raymond R. 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":223853,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","email":"","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":786430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217774,"text":"70217774 - 2020 - Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior","interactions":[],"lastModifiedDate":"2021-02-03T21:22:01.680529","indexId":"70217774","displayToPublicDate":"2020-03-03T06:56:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior","docAbstract":"<p><span>Several species of ciscoes&nbsp;</span><i>Coregonus</i><span>, subgenus&nbsp;</span><i>Leucichthys</i><span>&nbsp;that are native to the Laurentian Great Lakes are rare or extirpated. The restoration of&nbsp;</span><i>Coregonus</i><span>&nbsp;fishes is being actively pursued through stocking, and success may depend on the availability of unoccupied niche space. We described the spring–summer habitat occupancy and diets of three native cisco species (Bloater&nbsp;</span><i>Coregonus hoyi</i><span>, Cisco&nbsp;</span><i>C. artedi,</i><span>&nbsp;and Kiyi&nbsp;</span><i>C. Kiyi</i><span>) and invasive Rainbow Smelt&nbsp;</span><i>Osmerus mordax</i><span>&nbsp;in Lake Superior and measured niche overlap among these species for both small and large sizes. The potential habitat area was highest for Cisco and Kiyi, followed by Bloater and Rainbow Smelt. The probability of overlap in habitat occupation, as measured by bathymetric depth, fish capture depth, distance from shore, and fish capture water temperature was highest for small Rainbow Smelt and Cisco. Trophic overlap, as measured by stomach contents and stable isotopes, was highest between small Bloater and Cisco and between large Bloater and Kiyi. All of the species showed significant ontogenetic change in both habitat occupation and diet. The overall niche overlap in spring–summer habitat and diet was greatest between small Cisco and Rainbow Smelt and between large Bloater and Kiyi; however, differences in individual niche dimensions likely limit competition for both species pairs. Synthesizing the diet and habitat niche data revealed nuanced niches that allow these seemingly similar planktivorous species to coexist. Kiyi had the least niche overlap with other cisco species and Rainbow Smelt, so from an available niche perspective Kiyi would be a strong candidate for reintroduction into lakes from which they were extirpated.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10219","usgsCitation":"Rosinski, C.L., Vinson, M., and Yule, D.L., 2020, Niche partitioning among native ciscoes and nonnative Rainbow Smelt in Lake Superior: Transactions of the American Fisheries Society, v. 149, no. 2, p. 184-203, https://doi.org/10.1002/tafs.10219.","productDescription":"10 p.","startPage":"184","endPage":"203","ipdsId":"IP-113030","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":382868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Superior","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.11035156249999,\n              49.009050809382046\n            ],\n            [\n              -89.1650390625,\n              48.574789910928864\n            ],\n            [\n              -89.4287109375,\n              48.019324184801185\n            ],\n            [\n              -90.703125,\n              47.724544549099676\n            ],\n            [\n              -92.1533203125,\n              46.6795944656402\n            ],\n            [\n              -90.8349609375,\n              46.9502622421856\n            ],\n            [\n              -90.8349609375,\n              46.558860303117164\n            ],\n            [\n              -90,\n              46.76996843356982\n            ],\n            [\n              -88.9892578125,\n              47.07012182383309\n            ],\n            [\n              -87.978515625,\n              47.338822694822\n            ],\n            [\n              -88.505859375,\n              46.76996843356982\n            ],\n            [\n              -88.11035156249999,\n              46.9502622421856\n            ],\n            [\n              -87.451171875,\n              46.558860303117164\n            ],\n            [\n              -86.3525390625,\n              46.46813299215554\n            ],\n            [\n              -85.4736328125,\n              46.70973594407157\n            ],\n            [\n              -85.0341796875,\n              46.70973594407157\n            ],\n            [\n              -84.8583984375,\n              46.31658418182218\n            ],\n            [\n              -84.3310546875,\n              46.49839225859763\n            ],\n            [\n              -84.5068359375,\n              47.07012182383309\n            ],\n            [\n              -84.90234375,\n              47.989921667414194\n            ],\n            [\n              -85.95703125,\n              48.10743118848039\n            ],\n            [\n              -86.3525390625,\n              48.719961222646276\n            ],\n            [\n              -88.11035156249999,\n              49.009050809382046\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"149","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosinski, Caroline Lynn 0000-0003-3635-2748","orcid":"https://orcid.org/0000-0003-3635-2748","contributorId":248618,"corporation":false,"usgs":true,"family":"Rosinski","given":"Caroline","email":"","middleInitial":"Lynn","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70211932,"text":"70211932 - 2020 - Mercury export from Arctic great rivers","interactions":[],"lastModifiedDate":"2020-08-11T21:05:02.516262","indexId":"70211932","displayToPublicDate":"2020-03-02T16:04:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Mercury export from Arctic great rivers","docAbstract":"<p><span>Land–ocean linkages are strong across the circumpolar north, where the Arctic Ocean accounts for 1% of the global ocean volume and receives more than 10% of the global river discharge. Yet estimates of Arctic riverine mercury (Hg) export constrained from direct Hg measurements remain sparse. Here, we report results from a coordinated, year-round sampling program that focused on the six major Arctic rivers to establish a contemporary (2012–2017) benchmark of riverine Hg export. We determine that the six major Arctic rivers exported an average of 20 000 kg y</span><sup>–1</sup><span>&nbsp;of total Hg (THg, all forms of Hg). Upscaled to the pan-Arctic, we estimate THg flux of 37 000 kg y</span><sup>–1</sup><span>. More than 90% of THg flux occurred during peak river discharge in spring and summer. Normalizing fluxes to watershed area (yield) reveals higher THg yields in regions where greater denudation likely enhances Hg mobilization. River discharge, suspended sediment, and dissolved organic carbon predicted THg concentration with moderate fidelity, while suspended sediment and water yields predicted THg yield with high fidelity. These findings establish a benchmark in the face of rapid Arctic warming and an intensifying hydrologic cycle, which will likely accelerate Hg cycling in tandem with changing inputs from thawing permafrost and industrial activity.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.9b07145","usgsCitation":"Zolkos, S., Krabbenhoft, D.P., Suslova, A., Tank, S.E., McClelland, J.W., Spencer, R.G., Shiklomanov, A., Zhulidov, A.V., Gurtovaya, T., Zimov, N., Zimov, S., Mutter, E., Kutny, L., Amos, E., and Holmes, R.M., 2020, Mercury export from Arctic great rivers: Environmental Science & Technology, v. 54, no. 7, p. 4140-4148, https://doi.org/10.1021/acs.est.9b07145.","productDescription":"9 p.","startPage":"4140","endPage":"4148","ipdsId":"IP-115773","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":377394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","volume":"54","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Zolkos, Scott 0000-0001-9945-6945","orcid":"https://orcid.org/0000-0001-9945-6945","contributorId":238024,"corporation":false,"usgs":false,"family":"Zolkos","given":"Scott","email":"","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":795852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":795853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suslova, Anya","contributorId":238025,"corporation":false,"usgs":false,"family":"Suslova","given":"Anya","email":"","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":795854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tank, Suzanne E. 0000-0002-5371-6577","orcid":"https://orcid.org/0000-0002-5371-6577","contributorId":238026,"corporation":false,"usgs":false,"family":"Tank","given":"Suzanne","email":"","middleInitial":"E.","affiliations":[{"id":47684,"text":"Department of Biological Sciences, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":795855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McClelland, James W. 0000-0001-9619-8194","orcid":"https://orcid.org/0000-0001-9619-8194","contributorId":238027,"corporation":false,"usgs":false,"family":"McClelland","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":47685,"text":"Marine Science Institute, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":795856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Robert G. M. 0000-0003-0777-0748","orcid":"https://orcid.org/0000-0003-0777-0748","contributorId":238028,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert","email":"","middleInitial":"G. M.","affiliations":[{"id":47686,"text":"Department of Earth, Ocean and Atmospheric Science, Florida State University","active":true,"usgs":false}],"preferred":false,"id":795857,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shiklomanov, Alexander","contributorId":238029,"corporation":false,"usgs":false,"family":"Shiklomanov","given":"Alexander","affiliations":[{"id":47687,"text":"Institute for the Study of Earth, Oceans, and Space, University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":795858,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhulidov, Alexander V.","contributorId":238030,"corporation":false,"usgs":false,"family":"Zhulidov","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":47688,"text":"South Russia Centre for Preparation and Implementation of International Projects, Rostov-on-Don, Russia","active":true,"usgs":false}],"preferred":false,"id":795859,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gurtovaya, Tatiana","contributorId":238031,"corporation":false,"usgs":false,"family":"Gurtovaya","given":"Tatiana","email":"","affiliations":[{"id":47688,"text":"South Russia Centre for Preparation and Implementation of International Projects, Rostov-on-Don, Russia","active":true,"usgs":false}],"preferred":false,"id":795860,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zimov, Nikita","contributorId":238032,"corporation":false,"usgs":false,"family":"Zimov","given":"Nikita","email":"","affiliations":[{"id":47689,"text":"Northeast Science Station, Far Eastern Branch of Russian Academy of Science, Chersky, Russia","active":true,"usgs":false}],"preferred":false,"id":795861,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zimov, Sergey","contributorId":238033,"corporation":false,"usgs":false,"family":"Zimov","given":"Sergey","email":"","affiliations":[{"id":47689,"text":"Northeast Science Station, Far Eastern Branch of Russian Academy of Science, Chersky, Russia","active":true,"usgs":false}],"preferred":false,"id":795862,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mutter, Edda A.","contributorId":238034,"corporation":false,"usgs":false,"family":"Mutter","given":"Edda A.","affiliations":[{"id":47690,"text":"˚Yukon River Inter-Tribal Watershed Council, Anchorage, Alaska","active":true,"usgs":false}],"preferred":false,"id":795863,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kutny, Les","contributorId":238035,"corporation":false,"usgs":false,"family":"Kutny","given":"Les","email":"","affiliations":[{"id":47691,"text":"Western Arctic Research Centre, Inuvik, Northwest Territories, Canada","active":true,"usgs":false}],"preferred":false,"id":795864,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Amos, Edwin","contributorId":238036,"corporation":false,"usgs":false,"family":"Amos","given":"Edwin","email":"","affiliations":[{"id":47691,"text":"Western Arctic Research Centre, Inuvik, Northwest Territories, Canada","active":true,"usgs":false}],"preferred":false,"id":795865,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Holmes, Robert M.","contributorId":178901,"corporation":false,"usgs":false,"family":"Holmes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":795866,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70208879,"text":"70208879 - 2020 - Gas hydrate petroleum systems: What constitutes the “seal”?","interactions":[],"lastModifiedDate":"2020-06-04T16:58:08.036025","indexId":"70208879","displayToPublicDate":"2020-03-02T15:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Gas hydrate petroleum systems: What constitutes the “seal”?","docAbstract":"The gas hydrate petroleum system (GHPS) approach, which has been used to characterize gas hydrates in nature, utilizes three distinct components: a methane source, a methane migration pathway, and a reservoir that not only contains gas hydrate, but also acts as a seal to prevent methane loss. Unlike GHPS, a traditional petroleum system (PS) approach further distinguishes between the reservoir, a unit with generally coarser sediment grains, and a separate overlying seal unit with generally finer sediment grains. Adopting this traditional PS distinction in the GHPS approach facilitates assessments of reservoir growth and production potential. The significance of the seal for the formation of a gas hydrate reservoir as well as for the efficiency in methane extraction from the reservoir as an energy resource is evident in the findings from recent offshore field expeditions, such as India’s second National Gas Hydrate Program expedition (NGHP-02). In regards to gas hydrate-bearing reservoir formation, the NGHP-02 gas chemistry data indicate a primarily microbial methane source. Fine-grained seal sediment in contact with coarser-grained reservoir sediment can facilitate that microbial methane production. Logging-while-drilling and sediment core data also indicate that the overlying fine-grained seal sediment is less permeable than the underlying, highly gas hydrate-saturated reservoir sediment. The overlying seal’s capacity to act as a low-permeability boundary is important not only for preventing methane migration out of the reservoir over time, but for also preventing water invasion into the reservoir during methane extraction from the reservoir. Ultimately, the presence of an overlying, fine-grained, low-permeability “Seal”? influences how gas hydrate initially forms in a coarse-grained reservoir and dictates how efficiently methane can be extracted as an energy resource from the gas hydrate reservoir via depressurization.","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/int-2019-0026.1","usgsCitation":"Jang, J., Waite, W., and Stern, L.A., 2020, Gas hydrate petroleum systems: What constitutes the “seal”?: Interpretation, v. 8, no. 2, p. T231-T248, https://doi.org/10.1190/int-2019-0026.1.","productDescription":"18 p.","startPage":"T231","endPage":"T248","ipdsId":"IP-104479","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Bay of Bengal","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              84.44091796875,\n              18.47960905583197\n            ],\n            [\n              82.41943359375,\n              17.11979250078707\n            ],\n            [\n              82.44140625,\n              16.720385051694\n            ],\n            [\n              82.1337890625,\n              16.172472808397515\n            ],\n            [\n              81.40869140625,\n              16.25686733062344\n            ],\n            [\n              81.10107421874999,\n              15.665354182093287\n            ],\n            [\n              82.90283203125,\n              14.817370620155254\n            ],\n            [\n              86.396484375,\n              17.434510551522894\n            ],\n            [\n              84.44091796875,\n              18.47960905583197\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jang, Junbong 0000-0001-5500-7558 jjang@usgs.gov","orcid":"https://orcid.org/0000-0001-5500-7558","contributorId":189400,"corporation":false,"usgs":true,"family":"Jang","given":"Junbong","email":"jjang@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Laura A. 0000-0003-3440-5674","orcid":"https://orcid.org/0000-0003-3440-5674","contributorId":212238,"corporation":false,"usgs":true,"family":"Stern","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":783812,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209070,"text":"70209070 - 2020 - Wind River subbasin restoration: Annual report of US..Geological Survey activities, January 2018 through December 2018","interactions":[],"lastModifiedDate":"2020-03-16T17:06:02","indexId":"70209070","displayToPublicDate":"2020-03-02T14:40:52","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Wind River subbasin restoration: Annual report of US..Geological Survey activities, January 2018 through December 2018","docAbstract":"<p>We sampled juvenile wild Steelhead <i>Oncorhynchus mykiss</i> in headwater streams of the Wind River, WA, to characterize populations and investigate life-history metrics, particularly migratory patterns. We used Passive Integrated Transponder (PIT)-tagging and a series of instream PIT-tag interrogation systems (PTISs) to track juveniles. The Wind River subbasin is considered a wild Steelhead refuge by Washington Department of Fish and Wildlife (WDFW). No hatchery Steelhead have been planted in the Wind River subbasin since 1997, and hatchery adults are estimated to be less than one percent of spawners in most years (pers comm. Thomas Buehrens, Washington Department of Fish and Wildlife). Our repeated headwater sampling of consistent sites in the Wind River subbasin has also allowed us to track relative abundance of Brook Trout, a non-native species to the Wind River. Our work is contributing to understanding of Steelhead population response to numerous restoration actions in the subbasin, including removal of Hemlock Dam from Trout Creek in 2009, where our PTISs are helping to quantify adult response. </p><p>Data from our study, and companion work by Washington Department of Fish and Wildlife, are contributing to Bonneville Power Administration’s (BPA) Research Monitoring and Evaluation (RM&amp;E) Program Strategy of Fish Population Status Monitoring (www.cbfish.org/ProgramStrategy.mvc/ViewProgramStrategySummary/1). Specifically this work addresses the sub-strategies of: 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and to Uncertainties Research regarding differing life histories of a wild Steelhead population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives. Our headwaters parr PIT tagging, WDFW parr, smolt, and adult tagging and our instream PTISs are providing data on movements and life histories of parr, smolt, and adult Steelhead. </p><p>During summer 2018, we PIT-tagged 1,592 age-0 and age-1 Steelhead parr in headwater areas of the Wind River subbasin to characterize population traits and investigate life-history diversity, including growth and pre-smolt downstream movement. Repeat headwater sampling and smolt trap operations provide opportunities for recapture, and instream PTISs and Columbia River infrastructure provide opportunity for detection of PIT-tagged fish. Throughout the year, we maintained a series of six instream PTISs to monitor movement of tagged Steelhead parr, smolts, and adults. </p><p>Detections at the instream PTISs have demonstrated trends of age-0 and age-1 parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. Substantial numbers of parr make downstream movements as age-1 fish. We have estimated that from 15 to 33 percent of parr tagged as age-0 fish make downstream migrations at age-1 for additional rearing. We have estimated that from 1 to 27 percent of parr tagged as age-1 fish make downstream migrations during fall. These findings raise many questions about parr rearing strategies, habitat use, and success of these migrants and suggest a need for broader monitoring of juvenile Steelhead in some river systems to fully document juvenile production. Long-term monitoring of PIT-tagged fish is providing information on contribution of various life-history strategies to smolt production and adult returns. </p><p>Movements of PIT-tagged adult Steelhead were recorded at instream PTISs. These data have allowed assessment of adult returns to tributary watersheds within the Wind River subbasin. Detection efficiency of adult PIT-tagged Steelhead at our primary adult-monitoring PTIS in Trout Creek has been greater than 92 percent during 6 of the past 7 years. This is providing excellent data to estimate adult returns to this watershed.&nbsp;Determination of adult use of tributary watersheds is providing data to help evaluate the efficacy of the removal of Hemlock Dam on Trout Creek. Hemlock Dam, located at rkm 2.0 of Trout Creek, was removed in summer 2009. The dam contributed to hydrologic impairment of Trout Creek and had potential negative effects on Steelhead. The improvements made to the upper Wind River PTIS (site code WRU at rkm 28.3; better site characteristics and grid power) during 2016 and 2017, and a planned new site in the Mine Reach of the upper Wind River, will allow estimates of subbasin adult escapement like those in Trout Creek. </p><p>During 2018, we also completed planning and permitting with U.S. Forest Service for a new PTIS site at rkm 36 of the Wind River (the Mine Reach, mentioned above). This site will replace two sites (one in Paradise Creek and one at rkm 41 of the Wind River), which had operational challenges due to lack of adequate solar power and winter difficulties. The new Mine Reach PTIS site at rkm 36, will have better solar exposure, fewer winter operations difficulties, and provide opportunity to detect fish from juvenile sampling sites that were downstream of the previous two PTISs. The more consistent operation of the new Mine Reach PTIS site will increase our ability to estimate migrant abundance as all the juveniles tagged upstream of it will be subject to the same potential detection history, instead of three different potential detection histories as before. Additionally, with the new Mine Reach PTIS site lower in the watershed, it will subject more PIT-tagged adult Steelhead to detection and provide ability to generate a nonbiased adult-detection efficiency estimate for the WRU PTIS at rkm 28.3 of the Wind River. This will provide the opportunity to estimate yearly adult Steelhead abundance to the upper Wind watershed area. Permitting is complete and some supplies have been purchased to build and install this new site in 2019. </p><p>Repeat sampling at consistent locations in the subbasin has allowed investigation into juvenile Steelhead growth patterns. Growth rates (relative change in weight) of age-0 PIT-tagged parr during summer are similar across the subbasin, but lower for age-1 parr in the Trout Creek watershed than the upper Wind River watershed. Yearly growth for parr tagged at age-0 is similar across the subbasin. Yearly growth for parr tagged at age-1 is lowest in Martha Creek, but similar elsewhere. </p><p>Non-native Brook Trout are present in portions of the subbasin, chiefly the Trout Creek watershed, and repeat sampling has allowed us to index their prevalence. Percentage of catch that is Brook Trout at each of four sample sites in Trout Creek have declined from the period 1998 – 2003 to the period 2011 – 2018. There was a pattern of decline in percent of catch and number of Brook Trout at the Trout Creek sites from 2011 through 2016, though a slight upward trend during 2017 and 2018 has been evident.&nbsp;</p><p>Evaluating and planning restoration efforts are of interest to many managers and agencies to ensure efficient use of resources. The evaluation of various life-histories of Steelhead within the Wind River subbasin will provide information to better track populations, and to direct habitat restoration and water allocation planning. Movement of Steelhead parr raises many questions regarding estimating juvenile abundance, origin, and habitat use within watersheds. Improved PTISs and focused PIT tagging of age-0 and age-1 Steelhead parr are increasingly allowing us to investigate such questions. Increasingly detailed Viable Salmonid Population information, such as that provided by PIT-tagging and instream PTISs networks like those in the Wind River subbasin, provide data to inform policy and management, as life-history strategies and production bottlenecks are identified and understood. </p>","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Jezorek, I.G., 2020, Wind River subbasin restoration: Annual report of US..Geological Survey activities, January 2018 through December 2018, 74 p.","productDescription":"74 p.","ipdsId":"IP-115314","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373226,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/Viewer/P170098"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River subbasin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.34374999999999,\n              45.69083283645816\n            ],\n            [\n              -120.62988281249999,\n              45.69083283645816\n            ],\n            [\n              -120.62988281249999,\n              46.649436163350245\n            ],\n            [\n              -122.34374999999999,\n              46.649436163350245\n            ],\n            [\n              -122.34374999999999,\n              45.69083283645816\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian G. 0000-0002-3842-3485 ijezorek@usgs.gov","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":3572,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","email":"ijezorek@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784716,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70205095,"text":"sir20195080 - 2020 - Assessment of bridge scour countermeasures at selected bridges in the United States, 2014–18","interactions":[],"lastModifiedDate":"2022-04-22T21:26:12.93031","indexId":"sir20195080","displayToPublicDate":"2020-03-02T10:35:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5080","displayTitle":"Assessment of Bridge Scour Countermeasures at Selected Bridges in the United States, 2014–18","title":"Assessment of bridge scour countermeasures at selected bridges in the United States, 2014–18","docAbstract":"<p>Erosion of the streambed, known also as scour, around pier 3 of the New York State Thruway bridge over Schoharie Creek caused the pier to fail, which ultimately resulted in bridge failure during the flooding event of April 5, 1987. The Federal Highway Administration (FHWA) responded to the need for better guidance on the evaluation of bridge scour and the selection and installation of scour countermeasures with the release of several Hydraulic Engineering Circulars. Although this information has been available, used, and updated over the years, an evaluation of the current conditions of scour countermeasures has not been performed. Therefore, the U.S. Geological Survey, in cooperation with the FHWA, began a study in 2013 to assess the current conditions of bridge scour countermeasures at selected sites around the country. The bridge scour countermeasure site assessments included reviewing countermeasure design plans, field inspections, traditional surveys, motion-compensated terrestrial light detection and ranging technology (lidar), high-resolution multi-beam bathymetry scanning, underwater video imaging, and a review of the peak and daily streamflow history for the associated river or stream. A total of 34 bridge scour countermeasure sites were selected in 11 states for this study. The types of countermeasures installed at the bridge scour study sites ranged from riprap, the most common countermeasure in the study, to A-Jacks and cabled-concrete mattresses.</p><p>The installed countermeasures were generally exposed to hydraulic forces from floods that equaled or exceeded the 1-percent, and even the 0.2-percent, annual exceedance probability at some of the study sites, but not all. The field inspections and countermeasure evaluations identified areas of shifting, slumping, and some scour holes and damage or washouts to the countermeasures, but generally most remained in place. The high-resolution laser scanner data, photo imaging and traditional survey data, and field notes were provided to the FHWA for expert evaluation of the bridge scour countermeasure performance.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195080","collaboration":"Prepared in cooperation with the Federal Highway Administration","usgsCitation":"Suro, T.P., Huizinga, R.J., Fosness, R.L., and Dudunake, T.J., 2020, Assessment of bridge scour countermeasures at selected bridges in the United States, 2014–18: U.S. Geological Survey Scientific Investigations Report 2019–5080, 29 p., https://doi.org/10.3133/sir20195080.","productDescription":"Report: ix, 29 p.; 2 Data Releases","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-108279","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science 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,{"id":70208410,"text":"fs20203010 - 2020 - Water-quality comparison of the Gulf Coast aquifer system at various scales in Texas from National Water-Quality Assessment groundwater studies, 2013–15","interactions":[],"lastModifiedDate":"2022-04-20T18:28:36.153077","indexId":"fs20203010","displayToPublicDate":"2020-03-02T09:09:58","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3010","displayTitle":"Water-Quality Comparison of the Gulf Coast Aquifer System at Various Scales in Texas From National Water-Quality Assessment Groundwater Studies, 2013–15","title":"Water-quality comparison of the Gulf Coast aquifer system at various scales in Texas from National Water-Quality Assessment groundwater studies, 2013–15","docAbstract":"<p>One of the objectives of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Project is to assess groundwater quality in aquifers that are important sources of drinking water such as the coastal lowlands aquifer system, which is often referred to in Texas as the “Gulf Coast aquifer system.” The Gulf Coast aquifer system extends from Louisiana to Mexico and is a source of groundwater for several cities&nbsp;including Houston, Tex. The NAWQA groundwater studies in Texas in 2013–15 that assessed the Gulf Coast aquifer system included Principal Aquifer Surveys (PAS), Major Aquifer Studies (MAS), and Land Use Studies (LUS). These three study types are based on sampling networks of wells distributed in an area of interest. The PAS networks typically consist of public-supply wells that are relatively deep, the MAS networks typically consist of domestic-supply wells that are intermediate in depth, and the LUS networks typically consist of monitoring wells that are relatively shallow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203010","collaboration":"U.S. Geological Survey National Water-Quality Assessment","usgsCitation":"Ging, P.B., 2020, Water-quality comparison of the Gulf Coast aquifer system at various scales in Texas from National Water-Quality Assessment groundwater studies, 2013–15: U.S. Geological Survey Fact Sheet 2020–3010, 4 p., https://doi.org/10.3133/fs20203010.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-111987","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399200,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109733.htm"},{"id":372712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3010/fs20203010.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3010"},{"id":372711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3010/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Gulf Coast aquifer system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.5,\n              25.8378\n            ],\n            [\n              -93.5069,\n              25.8378\n            ],\n            [\n              -93.5069,\n              31.333\n            ],\n            [\n              -98.5,\n              31.333\n            ],\n            [\n              -98.5,\n              25.8378\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/tx-water%20\" href=\"https://www.usgs.gov/centers/tx-water%20\">Oklahoma-Texas Water Science Center</a> <br>U.S. Geological Survey<br>1505 Ferguson Lane <br>Austin, TX 78754–4501<br></p>","tableOfContents":"<ul><li>Overview of Water-Quality Sampling and Benchmarks for Evaluating Groundwater Quality</li><li>Water-Quality Results for the Gulf Coast Aquifer System</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-03-02","noUsgsAuthors":false,"publicationDate":"2020-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Ging, Patricia B. 0000-0001-5491-8448","orcid":"https://orcid.org/0000-0001-5491-8448","contributorId":222263,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia","email":"","middleInitial":"B.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781770,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70208261,"text":"ofr20201001 - 2020 - Application of decadal modeling approach to forecast barrier island evolution, Dauphin Island, Alabama","interactions":[],"lastModifiedDate":"2022-04-21T20:26:12.784524","indexId":"ofr20201001","displayToPublicDate":"2020-03-02T08:30:00","publicationYear":"2020","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":"2020-1001","displayTitle":"Application of Decadal Modeling Approach to Forecast Barrier Island Evolution, Dauphin Island, Alabama","title":"Application of decadal modeling approach to forecast barrier island evolution, Dauphin Island, Alabama","docAbstract":"<p>Forecasting barrier island evolution provides coastal managers and stakeholders the ability to assess the resiliency of these important coastal environments that are home to both established communities and existing natural habitats. 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Soupy  0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":222095,"corporation":false,"usgs":false,"family":"Dalyander","given":"P. Soupy ","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":781177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez, Victor 0000-0003-1463-4891","orcid":"https://orcid.org/0000-0003-1463-4891","contributorId":222096,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Victor","email":"","affiliations":[{"id":34200,"text":"Army Corp of Engineers","active":true,"usgs":false}],"preferred":false,"id":781178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Joseph W. 0000-0003-2912-1992","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":219235,"corporation":false,"usgs":false,"family":"Long","given":"Joseph","email":"","middleInitial":"W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":781181,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781180,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":781182,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70211597,"text":"70211597 - 2020 - Interaction of bacterial communities and indicators of water quality in shoreline sand, sediment, and water of Lake Michigan","interactions":[],"lastModifiedDate":"2020-08-05T13:48:48.631087","indexId":"70211597","displayToPublicDate":"2020-03-02T07:41:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Interaction of bacterial communities and indicators of water quality in shoreline sand, sediment, and water of Lake Michigan","docAbstract":"<p><span>Shoreline sand harbors high concentrations of fecal indicator bacteria (FIB) that may be resuspended into the water column through washing and resuspension. Studies have explored coastal processes that influence this sand-water flux for FIB, but little is known about how microbial markers of contamination or the bacterial community interact in the sand-water interface. In this study, we take a three-tiered approach to explore the relationship between bacteria in sand, sediment, and overlying water at three shoreline sites and two associated rivers along an extended freshwater shoreline. Samples were collected over two years and analyzed for FIB, two microbial source tracking (MST) markers (</span><i>Catellicoccus marimammalium,</i><span>&nbsp;Gull2;&nbsp;</span><i>Bacteroides</i><span>&nbsp;HF183), and targeted metagenomic 16S rRNA gene analysis. FIB was much higher in sand than in water at all three sites. Gull2 marker was abundant in shoreline sand and water while HF183 marker was mostly present in rivers. Overall bacterial communities were dissimilar between sand/sediment and water, indicating little interaction. Sediment composition was generally unfavorable to bacterial resuspension. Results show that FIB and MST markers were effective estimates of short-term conditions at these locations, and bacterial communities in sand and sediment reflected longer-term conditions. Findings are useful for locating contamination sources and targeting restoration by evaluating scope of shoreline degradation.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.115671","usgsCitation":"Nevers, M., Byappanahalli, M., Nakatsu, C., Kinzelman, J.L., Phanikumar, M.S., Shively, D., and Spoljaric, A., 2020, Interaction of bacterial communities and indicators of water quality in shoreline sand, sediment, and water of Lake Michigan: Water Research, v. 178, 115671, 11 p., https://doi.org/10.1016/j.watres.2020.115671.","productDescription":"115671, 11 p.","ipdsId":"IP-112926","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457529,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2020.115671","text":"Publisher Index Page"},{"id":437074,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NFKBEB","text":"USGS data release","linkHelpText":"Microbial communities and bacterial indicators for shoreline sand, sediment, and water in Racine, Wisconsin; Chicago, Illinois; and East Chicago, Indiana; 2016-2017"},{"id":377002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.3740234375,\n              41.47566020027821\n            ],\n            [\n              -84.6826171875,\n              41.47566020027821\n            ],\n            [\n              -84.6826171875,\n              46.28622391806706\n            ],\n            [\n              -88.3740234375,\n              46.28622391806706\n            ],\n            [\n              -88.3740234375,\n              41.47566020027821\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"178","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nakatsu, Cindy H.","contributorId":236943,"corporation":false,"usgs":false,"family":"Nakatsu","given":"Cindy H.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":794761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinzelman, Julie L.","contributorId":236944,"corporation":false,"usgs":false,"family":"Kinzelman","given":"Julie","email":"","middleInitial":"L.","affiliations":[{"id":37612,"text":"City of Racine Health Department","active":true,"usgs":false}],"preferred":false,"id":794762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phanikumar, Mantha S.","contributorId":208872,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":794763,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794764,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spoljaric, Ashley 0000-0001-6262-030X","orcid":"https://orcid.org/0000-0001-6262-030X","contributorId":202887,"corporation":false,"usgs":true,"family":"Spoljaric","given":"Ashley","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794765,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209123,"text":"70209123 - 2020 - Analysis of nearshore placement of sediments at Ogden Dunes, Indiana","interactions":[],"lastModifiedDate":"2020-03-18T07:36:56","indexId":"70209123","displayToPublicDate":"2020-03-02T07:33:27","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"ERDC/CHL TR-20-4","title":"Analysis of nearshore placement of sediments at Ogden Dunes, Indiana","docAbstract":"The harbor structures/shoreline armoring on the southern Lake Michigan shoreline interrupt sand migration. Ogden Dunes, Indiana, and the nearby Indiana Dunes National Lakeshore observed shoreline erosion due to engineered structures associated with Burns Waterway Harbor, east of Ogden Dunes, impeding natural east to west sediment migration. To remedy this, USACE placed over 450,000 cubic meters, or m³, of dredged material post 2006 in the nearshore of Ogden Dunes. However, the effectiveness of nearshore placements for shoreline protection and littoral nourishment is not fully established. To improve nearshore placement effectiveness, USACE monitored the June/July 2016 placement and subsequent movement of 107,000 m³ of dredged material in the nearshore region at Ogden Dunes. This involved an extensive monitoring scheme of three bathymetry surveys, and two acoustic Doppler current profiler deployments, a Coastal Modeling System numerical model of the changes following placement, and a prediction of sediment transport direction using the Sediment Mobility Tool. The SMT predicted sediment migration direction was compared to observations. Observations indicated that between 10/11/2016 and 11/15/2016 the centroid of the sediment above the pre-placement survey moved 17 m onshore. These observations agreed with SMT predictions onshore migration under storm and typical wave conditions. CMS accurately reproduced the hydrodynamic features.","language":"English","publisher":"U.S. Coastal and Hydraulics Laboratory, U.S. Engineer Research and Development Center ","doi":"10.21079/11681/35853","collaboration":"USACE ERDC-CHL\nUSACE Chicago District","usgsCitation":"Young, D.L., Brutsche, K.E., Li, H., McFall, B.C., Maloney, E., McClain, K.E., Bucaro, D.F., LeRoy, J.Z., Duncker, J.J., Johnson, K.K., and Jackson, P.R., 2020, Analysis of nearshore placement of sediments at Ogden Dunes, Indiana, ix, 85 p., https://doi.org/10.21079/11681/35853.","productDescription":"ix, 85 p.","ipdsId":"IP-104560","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":457533,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21079/11681/35853","text":"Publisher Index Page"},{"id":373334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Ogden Dunes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.28363037109374,\n              41.63494664852403\n            ],\n            [\n              -87.26577758789062,\n              41.59182393372352\n            ],\n            [\n              -87.22457885742188,\n              41.6010669423553\n            ],\n            [\n              -87.11746215820312,\n              41.58771550500517\n            ],\n            [\n              -86.98699951171874,\n              41.612362155265984\n            ],\n            [\n              -86.86614990234375,\n              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E","contributorId":223415,"corporation":false,"usgs":false,"family":"Brutsche","given":"Katherine","email":"","middleInitial":"E","affiliations":[{"id":18947,"text":"USACE ERDC","active":true,"usgs":false}],"preferred":false,"id":784999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Honghai","contributorId":223416,"corporation":false,"usgs":false,"family":"Li","given":"Honghai","email":"","affiliations":[{"id":18947,"text":"USACE ERDC","active":true,"usgs":false}],"preferred":false,"id":785000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McFall, Brian C","contributorId":223417,"corporation":false,"usgs":false,"family":"McFall","given":"Brian","email":"","middleInitial":"C","affiliations":[{"id":18947,"text":"USACE ERDC","active":true,"usgs":false}],"preferred":false,"id":785001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Erin C","contributorId":223418,"corporation":false,"usgs":false,"family":"Maloney","given":"Erin C","affiliations":[{"id":40713,"text":"USACE Chicago District","active":true,"usgs":false}],"preferred":false,"id":785002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McClain, Kaitlyn E","contributorId":223419,"corporation":false,"usgs":false,"family":"McClain","given":"Kaitlyn","email":"","middleInitial":"E","affiliations":[{"id":40713,"text":"USACE Chicago District","active":true,"usgs":false}],"preferred":false,"id":785003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bucaro, David F.","contributorId":223420,"corporation":false,"usgs":false,"family":"Bucaro","given":"David","email":"","middleInitial":"F.","affiliations":[{"id":40713,"text":"USACE Chicago District","active":true,"usgs":false}],"preferred":false,"id":785004,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784997,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785005,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785006,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785007,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70217319,"text":"70217319 - 2020 - Testing the interactive effects of flooding and salinity on tidal marsh plant productivity","interactions":[],"lastModifiedDate":"2021-01-27T22:01:59.199443","indexId":"70217319","displayToPublicDate":"2020-03-02T07:15:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":861,"text":"Aquatic Botany","active":true,"publicationSubtype":{"id":10}},"title":"Testing the interactive effects of flooding and salinity on tidal marsh plant productivity","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\"><div id=\"abst0010\"><p id=\"spar0045\">Tidal wetlands support plant communities that facilitate carbon storage, accrete soil, and provide habitat for terrestrial and aquatic species. Climate change is likely to alter estuaries through sea-level rise and changing precipitation patterns, although the ecological responses are uncertain. We were interested in plant responses to physiological stress induced by elevated water salinity and flooding conditions, which may be more prevalent under climate change. . We used a greenhouse experiment and factorial flooding (1, 12, 24, and 48 % time) and salinity (0, 5, 15, 30 PSU) treatments to evaluate the productivity responses of three emergent herbaceous species (<i>Carex lyngbyei, Triglochin maritima,</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Argentina pacifica</i>) common to tidal marshes of the Pacific Northwest, USA. We measured weekly changes in plant height and final above and belowground biomass for all species after 10 weeks. Increased salinity reduced final above and belowground biomass significantly in all three species, with<span>&nbsp;</span><i>A. pacifica</i><span>&nbsp;</span>responding the most, followed by<span>&nbsp;</span><i>C. lyngbyei</i><span>&nbsp;</span>and<span>&nbsp;</span><i>T. maritima</i>. Increased flooding also reduced total biomass in<span>&nbsp;</span><i>A. pacifica</i><span>&nbsp;</span>and<span>&nbsp;</span><i>T. maritima</i>. There was a significant response in<span>&nbsp;</span><i>C. lyngbyei</i><span>&nbsp;</span>aboveground biomass and<span>&nbsp;</span><i>A. pacifica</i><span>&nbsp;</span>height to the flooding-salinity interaction. These results indicate emergent plant community composition may change in response to novel climate conditions in estuaries, driven by distinct physiological tolerances to salinity and flooding, and highlight the importance of considering multiple climate drivers when projecting ecosystem change. This may be especially true for estuaries that currently have prolonged freshwater phases like those in the Pacific Northwest.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquabot.2020.103231","usgsCitation":"Buffington, K., Goodman, A., Freeman, C.M., and Thorne, K., 2020, Testing the interactive effects of flooding and salinity on tidal marsh plant productivity: Aquatic Botany, v. 164, 103231, 8 p., https://doi.org/10.1016/j.aquabot.2020.103231.","productDescription":"103231, 8 p.","ipdsId":"IP-117117","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437075,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XV4XLQ","text":"USGS data release","linkHelpText":"Pacific Northwest tidal marsh plant biomass from a 2017 greenhouse experiment with flooding and salinity manipulations"},{"id":382248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodman, Arianna C","contributorId":247781,"corporation":false,"usgs":false,"family":"Goodman","given":"Arianna C","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":808339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}