The St. Marys River connects Lake Superior to Lake Huron, comprising the international border between Michigan, United States, and Ontario, Canada. This Great Lakes connecting channel naturally encompasses various habitats including lakes, wetlands, islands, tributaries, side channels, and main channels. The St. Marys River Rapids are shallow rock areas with high flow velocities (>1 m/s) in the upper river adjacent to the navigation locks and electric power generating stations, while the Little Rapids are shallow, recently restored rocky areas with lower velocities located about 7 km downstream. The St. Marys River Rapids provide important spawning habitat for several native and introduced fishes, but spawning by lake sturgeon (Acipenser fulvescens) was not previously documented. We sampled for lake sturgeon eggs and larvae in both locations during June and July 2018–2019 using weekly benthic egg mat lifts and overnight D-frame larval fish drift nets. Viable lake sturgeon eggs (11 in 2018, 45 in 2019) were collected in the tailrace of a hydroelectric power facility adjacent to the St. Marys River Rapids. Larval lake sturgeon (21 in 2018, 1 in 2019) were collected in the same area as the eggs. Neither lake sturgeon eggs nor larvae were collected at Little Rapids in either year. Our results are the first documentation of successful lake sturgeon spawning and larval drift in the upper St. Marys River. While our observations showed spawning in a human-made tailrace area, the fate of larvae produced here is unknown and warrants further research.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.07.005","usgsCitation":"Roseman, E., Adams, E.J., DeBruyne, R.L., Gostiaux, J., Harrington, H., Kapuscinski, K., Moerke, A., and Olds, C., 2020, Lake sturgeon (Acipenser fulvescens) spawn in the St. Marys River Rapids, Michigan: Journal of Great Lakes Research, v. 46, no. 5, p. 1479-1484, https://doi.org/10.1016/j.jglr.2020.07.005.","productDescription":"6 p.","startPage":"1479","endPage":"1484","ipdsId":"IP-115133","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436842,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJMIPO","text":"USGS data release","linkHelpText":"Fish eggs collected in the St. Clair, Detroit, and St. Marys rivers, 2005-2018"},{"id":382461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Marys River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.49722290039062,\n 46.44069599413034\n ],\n [\n -84.1827392578125,\n 46.44069599413034\n ],\n [\n -84.1827392578125,\n 46.54091587805394\n ],\n [\n -84.49722290039062,\n 46.54091587805394\n ],\n [\n -84.49722290039062,\n 46.44069599413034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Eric John 0000-0001-9695-9483","orcid":"https://orcid.org/0000-0001-9695-9483","contributorId":248219,"corporation":false,"usgs":true,"family":"Adams","given":"Eric","email":"","middleInitial":"John","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":808632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gostiaux, J.","contributorId":248221,"corporation":false,"usgs":false,"family":"Gostiaux","given":"J.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":808633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrington, H.","contributorId":248222,"corporation":false,"usgs":false,"family":"Harrington","given":"H.","email":"","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":808634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kapuscinski, K.","contributorId":247567,"corporation":false,"usgs":false,"family":"Kapuscinski","given":"K.","email":"","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":808635,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moerke, A.","contributorId":247569,"corporation":false,"usgs":false,"family":"Moerke","given":"A.","affiliations":[{"id":49581,"text":"Lake Superior State Univ.","active":true,"usgs":false}],"preferred":false,"id":808636,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Olds, C.","contributorId":248227,"corporation":false,"usgs":false,"family":"Olds","given":"C.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":808637,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70212762,"text":"70212762 - 2020 - Procedures for developing multi-period response spectra at non-conterminous United States sites","interactions":[],"lastModifiedDate":"2021-01-22T18:10:01.008346","indexId":"70212762","displayToPublicDate":"2020-08-01T11:57:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"P-2078","title":"Procedures for developing multi-period response spectra at non-conterminous United States sites","docAbstract":"This study complements proposals to the Provisions Update Committee of the Building Seismic Safety Council that would incorporate multi-period response spectra (MPRS) in the 2020 edition of the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures (2020 NEHRP Provisions) and related proposals to the ASCE 7-22 Seismic Subcommittee of the American Society of Civil Engineers for incorporation of MPRS in ASCE Standard, ASCE/SEI 7-22, Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE 7-22). Ultimately, the intent is that the proposed MPRS and related design requirements of ASCE 7-22 would be adopted, by reference, as part of the 2024 International Building Code.
The technical basis and associated methods herein enable the U.S. Geological Survey (USGS) to develop MPRS for sites in non-conterminous U.S. regions for which seismic hazard analyses have not yet been updated by the USGS to fully define all 22 periods and eight site classes of interest in the MPRS related proposals for the 2020 NEHRP Provisions and ASCE 7-22. These regions include Alaska, Hawaii, Guam and the Northern Mariana Islands, Puerto Rico and the U.S. Virgin Islands, and American Samoa.
The methods developed can be used to derive MPRS using only the three currently available ground motion parameters SS, S1, and TL for all nonconterminous United States regions of interest. The methods include models that characterize generic shapes of Risk-Targeted Maximum Considered Earthquake (MCER) ground motions as a function of these three parameters. For deriving MPRS that represent probabilistic MCER ground motions, models are based on statistical analyses of large sample sets of probabilistic MCER response spectra for Western United States (WUS) and Cascadia sites in California, Oregon, Washington (including Puget Sound), Idaho, and Nevada. For deriving MPRS that represent deterministic MCER ground motions, models are based on sets of deterministic MCER response spectra calculated using WUS shallow crustal ground motion models for earthquake magnitudes and shaking levels typical of sites governed by deterministic
MCER ground motions.
Temporal and spatial distribution of niclosamide in the water column and sediment were evaluated after the application of granular Bayluscide in six lentic sea lamprey (Petromyzon marinus) larval assessment plots. Water and sediment were collected 0.25, 1, 3, 5, and 7 hours after application and were analyzed for niclosamide, the active ingredient in granular Bayluscide. Water samples were collected from five heights in the water column (1 cm, 13 cm, 26 cm, 1/2 water column, and water surface) at five locations inside and four locations 10 m outside of each assessment plot. Sediment was collected from 18 locations within each plot. Niclosamide water concentrations inside and outside of the plots did not vary by depth but did vary between plots and by time. Niclosamide water concentrations also varied by sampler location outside of the plots. Following granular Bayluscide applications the mean niclosamide concentration in water for all levels, within the plots, decreased from 0.12 mgL-1 (SD = 0.12 mgL-1) at 15 minutes to 0.061 mgL-1 (SD = 0.040 mgL-1) at hour 1. The mean niclosamide concentration in the top 4 cm of sediment was 2.9 mgkg-1 (SD = 2.4 mgkg-1) 15 minutes after application and was 1.3 mgkg-1 (SD = 1.8 mgkg-1) at hour 7. Concentrations in all sediment samples ranged from < 0.001 to 30.730 mgkg-1 and varied between the six plots. Niclosamide concentrations measured in sediment samples were more than 1 order of magnitude greater than in the water and varied spatially by over 4 orders of magnitude.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bernardy, J., Kaye, C., Schloesser, N., and Schueller, J., 2020, Distribution of niclosamide following granular Bayer applications in lentic environments: Project Completion Report, 30 p.","productDescription":"30 p.","ipdsId":"IP-107424","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377968,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/"}],"country":"United States","state":"Michigan, Wisconsin","county":"Mackinac County, Marinette County","otherGeospatial":"Hog Island Creek, Lake Michigan, Peshtigo Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.66952514648438,\n 44.96832008904543\n ],\n [\n -87.64514923095703,\n 44.96832008904543\n ],\n [\n -87.64514923095703,\n 44.98568481264677\n ],\n [\n -87.66952514648438,\n 44.98568481264677\n ],\n [\n -87.66952514648438,\n 44.96832008904543\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.28724074363708,\n 46.07139217240364\n ],\n [\n -85.28464436531067,\n 46.07139217240364\n ],\n [\n -85.28464436531067,\n 46.07282125858186\n ],\n [\n -85.28724074363708,\n 46.07282125858186\n ],\n [\n -85.28724074363708,\n 46.07139217240364\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bernardy, Jeffry 0000-0001-7443-1995","orcid":"https://orcid.org/0000-0001-7443-1995","contributorId":213528,"corporation":false,"usgs":true,"family":"Bernardy","given":"Jeffry","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaye, Cheryl","contributorId":167292,"corporation":false,"usgs":false,"family":"Kaye","given":"Cheryl","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":797470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":797472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228560,"text":"70228560 - 2020 - Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","interactions":[],"lastModifiedDate":"2022-02-15T12:22:36.066283","indexId":"70228560","displayToPublicDate":"2020-08-01T09:59:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States","docAbstract":"Investigating the spatiotemporal dynamics of contaminants in surface water is crucial to better understand how introduced chemicals are interacting with and potentially influencing aquatic organisms and environments. Within the Chesapeake Bay Watershed, USA, there are concerns about the potential role of contaminant exposure on fish health. Evidence suggests that exposure to contaminants in surface water is causing immunosuppression and intersex in freshwater fish species. Despite these concerns, there is a paucity of information regarding the complex dynamics of contaminant occurrence and co-occurrence in surface water across both space and time. To address these concerns, we applied a Bayesian hierarchical joint-contaminant model to describe the occurrence and co-occurrence patterns of 28 contaminants and total estrogenicity across six river sites and over three years. We found that seasonal occurrence patterns varied by contaminant, with the highest occurrence probabilities during the spring and summer months. Additionally, we found that the proportion of agricultural landcover in the immediate catchment, as well as stream discharge, did not have a significant effect on the occurrence probabilities of most compounds. Four pesticides (atrazine, metolachlor, fipronil and simazine) co-occurred across sites after accounting for environmental covariates. These results provide baseline information on the contaminant occurrence patterns of several classes of compounds within the Chesapeake Bay Watershed. Understanding the spatiotemporal dynamics of contaminants in surface water is the first step in investigating the effects of contaminant exposure on fisheries and aquatic environments.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.138765","usgsCitation":"McClure, C.M., Smalling, K., Blazer, V.S., Sperry, A., Schall, M.K., Kolpin, D., Phillips, P.J., Hladik, M.L., and Wagner, T., 2020, Spatiotemporal variation in occurrence and co-occurrence of pesticides, hormones, and other organic contaminants in rivers in the Chesapeake Bay Watershed, United States: Science of the Total Environment, v. 728, p. 1-13, https://doi.org/10.1016/j.scitotenv.2020.138765.","productDescription":"138765, 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-117478","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science 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snapping turtles in southwest Louisiana","interactions":[],"lastModifiedDate":"2021-03-05T21:31:13.265943","indexId":"70213082","displayToPublicDate":"2020-08-01T09:37:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A trapping survey targeting head-started alligator snapping turtles in southwest Louisiana","docAbstract":"The alligator snapping turtle Macrochelys temminckii is the largest freshwater turtle in North America and is sought after as a food source, primarily in Louisiana. Decades of intensive commercial harvest of alligator snapping turtles has been implicated in population declines. The Louisiana Department of Wildlife and Fisheries initiated a head-start program for alligator snapping turtles and released 53 head-started juveniles at seven sites along an approximately 5.7-km stretch of Bundick Creek in southwest Louisiana between November 2015 and October 2016. Before release, all alligator snapping turtles were measured, weighed, and marked with both an internal passive integrated transponder tag and a numbered external tag. In 2018, the U.S. Geological Survey initiated a turtle trapping survey at those seven release sites targeting the head-started alligator snapping turtles. In one week of trapping effort at each site, we recorded 69 turtle captures comprising seven species, including 15 alligator snapping turtles (representing 12 individuals). Of those 12 individuals, 8 were head-started juveniles and 4 were native to the creek. An additional head-started juvenile alligator snapping turtle was captured by a landowner during our trapping and measurements were taken before release. A minimum of 17% of head-started alligator snapping turtles survived since release, and most captured head-started individuals were trapped near their release site and exhibited growth consistent with other studies, indicating acclimatization to their new environment. Three head-started alligator snapping turtles had their external tags entangled in the net mesh, and two of these turtles drowned. An additional two head-started individuals lost their external tags in the natural environment prior to their capture in this study. The use of external tags was discontinued by the Louisiana Department of Wildlife and Fisheries based on our findings, as they were detrimental to the health of head-started turtles.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-009","usgsCitation":"Glorioso, B., Muse, L.J., Hillard, C.J., Maldonado, B.R., Streeter, J., Battaglia, C.D., and Waddle, J.H., 2020, A trapping survey targeting head-started alligator snapping turtles in southwest Louisiana: Journal of Fish and Wildlife Management, v. 11, no. 2, p. 572-582, https://doi.org/10.3996/JFWM-20-009.","productDescription":"11 p.","startPage":"572","endPage":"582","ipdsId":"IP-108013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455791,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-009","text":"Publisher Index Page"},{"id":436844,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G9BR1D","text":"USGS data release","linkHelpText":"Data from a turtle trapping effort at a release site of head-started alligator snapping turtles, 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Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous Δ47 and Δ48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.
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2020 - A fishery after the decline: The Susquehanna River Smallmouth Bass story","interactions":[],"lastModifiedDate":"2022-02-08T15:30:23.551832","indexId":"70228229","displayToPublicDate":"2020-08-01T09:04:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"A fishery after the decline: The Susquehanna River Smallmouth Bass story","docAbstract":"The Smallmouth Bass Micropterus dolomieu fishery in the Susquehanna River basin, Pennsylvania, is one of the most socioeconomically important fisheries in the region and has recently undergone considerable changes. These changes started in 2005, when disease was documented in young-of-the-year (age-0) Smallmouth Bass. Shortly thereafter, declines in abundance of both juveniles and adults were observed. These declines in abundance coincided with disease infections in age-0, intersex in adults, and concerns regarding contaminant exposure. Natural mortality rates, particularly for age-0, increased during this period (2005–2011), and there were concerns for the overall health of this world-class fishery. However, in recent years (2012–2017), there have been decreases in both mortality rates and external observations of disease and increases in abundance across multiple size-classes. Recent changes are encouraging for the future of the Smallmouth Bass fishery in the Susquehanna River. Yet, in light of the ever changing environmental, social, and anthropogenic influences on aquatic ecosystems, there remain concerns for Smallmouth Bass health and management. Because of this, ongoing research efforts are needed to monitor population and health changes and to conduct integrative research that considers complex relationships between organisms and their environments.
","language":"English","publisher":"Wiley","doi":"10.1002/fsh.10491","usgsCitation":"Schall, M., Smith, G., Blazer, V., Walsh, H.L., Li, Y., and Wagner, T., 2020, A fishery after the decline: The Susquehanna River Smallmouth Bass story: Fisheries Magazine, v. 45, no. 11, p. 576-584, https://doi.org/10.1002/fsh.10491.","productDescription":"9 p.","startPage":"576","endPage":"584","ipdsId":"IP-113869","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":395618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.629638671875,\n 39.73253798438173\n ],\n [\n -75.95947265625,\n 39.73253798438173\n ],\n [\n -76.102294921875,\n 40.65563874006118\n ],\n [\n -75.498046875,\n 41.3850519497068\n ],\n [\n -76.04736328125,\n 42.01665183556825\n ],\n [\n -77.750244140625,\n 42.01665183556825\n ],\n [\n -77.618408203125,\n 40.371658891506094\n ],\n [\n -76.629638671875,\n 39.73253798438173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Schall, Megan K.","contributorId":264767,"corporation":false,"usgs":false,"family":"Schall","given":"Megan K.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":833481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Geoffrey D.","contributorId":224595,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey D.","affiliations":[{"id":40898,"text":"Pennsylvania Fish & Boat Commission","active":true,"usgs":false}],"preferred":false,"id":833482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":833483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":833484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Yan","contributorId":264515,"corporation":false,"usgs":false,"family":"Li","given":"Yan","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":833485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833480,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211704,"text":"70211704 - 2020 - A global parasite conservation plan","interactions":[],"lastModifiedDate":"2020-10-12T17:14:18.229218","indexId":"70211704","displayToPublicDate":"2020-08-01T08:35:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A global parasite conservation plan","docAbstract":"Found throughout the tree of life and in every ecosystem, parasites are some of the most diverse, ecologically important animals on Earth—but in almost all cases, the least protected by wildlife or ecosystem conservation efforts. For decades, ecologists have been calling for research to understand parasites' important ecological role, and increasingly, to protect as many species from extinction as possible. However, most conservationists still work within priority systems for funding and effort that exclude or ignore parasites, or treat parasites as an obstacle to be overcome. Our working group identified 12 goals for the next decade that could advance parasite biodiversity conservation through an ambitious mix of research, advocacy, and management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108596","usgsCitation":"Carlson, C.J., Hopkins, S.R., Bell, K.C., Dona, J., Godfrey, S.S., Kwak, M.L., Lafferty, K.D., Moir, M.L., Speer, K., Strona, G., Torchin, M., and Wood, C.L., 2020, A global parasite conservation plan: Biological Conservation, v. 250, 108596, 12 p., https://doi.org/10.1016/j.biocon.2020.108596.","productDescription":"108596, 12 p.","ipdsId":"IP-117834","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2020.108596","text":"Publisher Index Page"},{"id":377168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"250","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Colin 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This basin is located within the Aleutian-Alaskan convergent margin region and is expected to show effects of regional subduction zone processes. Aeromagnetic data, when filtered to highlight anomalies associated with sources within the upper few kilometers, show numerous linear northeast-trending highs and some linear north-trending highs. Comparisons to seismic reflection and well data show that these highs correspond to areas where late Paleocene to early Eocene volcanic layers have been locally uplifted due to folding and/or faulting. The combined magnetic and seismic reflection data suggest that the linear highs represent northeast-trending folds and north-striking faults. Several lines of evidence suggest that the northeast-trending folds formed during the middle Eocene to early Miocene and may have continued to be active in the Pliocene. The north-striking faults, which in some areas appear to cut the northeast-trending folds, show evidence of Neogene and probable modern movement. Gravity data facilitate estimates of the shape and depth of the basin. This was accomplished by separating the observed gravity anomaly into two components—one representing low-density sedimentary fill within the basin and one representing density heterogeneities within the underlying crystalline basement. We then used the basin anomaly, seismic reflection data, and well data to estimate the depth of the basin. Together, the magnetic, gravity, and reflection seismic analyses reveal an asymmetric basin comprising sedimentary rock over 4 km thick with steep, fault-bounded sides to the southwest, west, and north and a mostly gentle rise toward the east. Relations to the broader tectonic regime are suggested by fold axis orientations within the Susitna basin and neighboring Cook Inlet basin, which are roughly parallel to the easternmost part of the Alaska-Aleutian trench and associated Wadati-Benioff zone as it trends from northeast to north-northeast to northeast. An alignment between forearc basin folds and the subduction zone trench has been observed at other convergent margins, attributed to strain partitioning generated by regional rheologic variations that are associated with the subducting plate and arc magmatism. The asymmetric shape of the basin, especially its gentle rise to the east, may reflect uplift associated with flat-slab subduction of the Yakutat microplate, consistent with previous work that suggested Yakutat influence on the nearby Talkeetna Mountains and western Alaska Range. Yakutat subduction may also have contributed to Neogene and later reverse slip along north-striking faults within the Susitna basin.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02165.1","usgsCitation":"Shah, A.K., Phillips, J., Lewis, K.A., Stanley, R.G., Haeussler, P., and Potter, C.J., 2020, Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data: Geosphere, v. 16, no. 4, p. 969-990, https://doi.org/10.1130/GES02165.1.","productDescription":"22 p.","startPage":"969","endPage":"990","ipdsId":"IP-103718","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":455808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02165.1","text":"Publisher Index Page"},{"id":380589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"South Central Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.775390625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 57.844750992891\n ],\n [\n -145.634765625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 62.71446210149774\n ],\n [\n -154.775390625,\n 57.844750992891\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":805107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":805108,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212896,"text":"70212896 - 2020 - Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA","interactions":[],"lastModifiedDate":"2020-10-28T15:59:41.808411","indexId":"70212896","displayToPublicDate":"2020-07-31T18:44:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5051,"text":"Virus Evolution","onlineIssn":"2057-1577","active":true,"publicationSubtype":{"id":10}},"title":"Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA","docAbstract":"Piscine orthoreovirus (PRV-1) is a segmented RNA virus which is commonly found in salmonids in the Atlantic and Pacific Oceans. PRV-1 causes the Heart and Skeletal Muscle Inflammation (HSMI) disease in Atlantic salmon and is associated with several other disease conditions. Previous phylogenetic studies of genome segment 1 (S1) identified four main genogroups of PRV-1 (S1 genogroups I – IV). The goal of the present study was to use Bayesian phylogenetic inference to expand our understanding of the spatial, temporal and host patterns of PRV-1 from the waters of the northeast Pacific. To that end, we determined the coding genome sequences of 14 PRV-1 samples that were selected to improve our knowledge of genetic diversity across a broader temporal, geographic and host range, including the first reported genome sequences from the northwest Atlantic (Eastern Canada). Nucleotide and amino acid sequences of the concatenated genomes and their individual segments revealed that established sequences from the northeast Pacific were monophyletic in all analyses. Bayesian inference phylogenetic trees of S1 sequences using BEAST and MrBayes also found that sequences from the northeast Pacific grouped separately from sequences from other areas. One PRV-1 sample (WCAN_BC17_AS_2017) from an escaped Atlantic salmon, collected in British Columbia but derived from Icelandic broodstock, grouped with other S1 sequences from Iceland. Our concatenated genome and S1 analysis demonstrated that PRV-1 from the northeast Pacific is genetically distinct but descended from PRV-1 from the North Atlantic. However, the analyses were inconclusive as to the timing and exact source of introduction into the northeast Pacific, either from eastern North America or European waters of the North Atlantic. There was no evidence that PRV-1 was evolving differently between free-ranging Pacific Salmon and farmed Atlantic Salmon. The northeast Pacific PRV-1 sequences fall within genogroup II based on the classification of Garseth et al. (2013), which also includes North Atlantic sequences from Eastern Canada, Iceland and Norway. The additional full genome sequences herein strengthen our understanding of phylogeographical patterns related to the northeast Pacific, but a more balanced representation of full PRV-1 genomes from across its range, as well additional sequencing of archived samples, are still needed to better understand global relationships including potential transmission links among regions.
","language":"English","publisher":"Oxford Academic Journals","doi":"10.1093/ve/veaa054","usgsCitation":"Siah, A., Breyta, B.R., Warheit, K.I., Gagne, N., Purcell, M.K., Morrison, D.B., Powell, J.F., and Johnson, S., 2020, Genomes reveal genetic diversity of Piscine orthoreovirus in farmed and free-ranging salmonids from Canada and USA: Virus Evolution, v. 6, no. 2, veaa054, 15 p., https://doi.org/10.1093/ve/veaa054.","productDescription":"veaa054, 15 p.","ipdsId":"IP-118186","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":455811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ve/veaa054","text":"Publisher Index Page"},{"id":378077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Chile, Norway, United States","otherGeospatial":"Faroe Islands","volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Siah, Ahmed","contributorId":149983,"corporation":false,"usgs":false,"family":"Siah","given":"Ahmed","email":"","affiliations":[{"id":17874,"text":"British Columbia Centre for Aquatic Health Sciences, BC Canada","active":true,"usgs":false}],"preferred":false,"id":797785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breyta, B. R.","contributorId":239729,"corporation":false,"usgs":false,"family":"Breyta","given":"B.","email":"","middleInitial":"R.","affiliations":[{"id":47991,"text":"University of Washington, School of Aquatic Fisheries Sciences, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":797786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warheit, K. I.","contributorId":239730,"corporation":false,"usgs":false,"family":"Warheit","given":"K.","email":"","middleInitial":"I.","affiliations":[{"id":47993,"text":"Washington Department of Fish and Wildlife, Olympia WA, USA","active":true,"usgs":false}],"preferred":false,"id":797787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gagne, N","contributorId":239731,"corporation":false,"usgs":false,"family":"Gagne","given":"N","email":"","affiliations":[{"id":47994,"text":"Fisheries & Oceans Canada, Gulf Fisheries Center, Moncton, NB, Canada","active":true,"usgs":false}],"preferred":false,"id":797788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":797789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, Diane B.","contributorId":149984,"corporation":false,"usgs":false,"family":"Morrison","given":"Diane","email":"","middleInitial":"B.","affiliations":[{"id":17875,"text":"Marine Harvest Canada, Campbell River, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":797790,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powell, J. F. F.","contributorId":239732,"corporation":false,"usgs":false,"family":"Powell","given":"J.","email":"","middleInitial":"F. F.","affiliations":[{"id":47996,"text":"British Columbia Centre for Aquatic Health Sciences, Campbell River BC, Canada","active":true,"usgs":false}],"preferred":false,"id":797791,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, S. C.","contributorId":239733,"corporation":false,"usgs":false,"family":"Johnson","given":"S. C.","affiliations":[{"id":47997,"text":"Fisheries & Oceans Canada, Nanaimo, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":797792,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211518,"text":"sir20205069 - 2020 - Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","interactions":[],"lastModifiedDate":"2020-08-05T18:38:22.157905","indexId":"sir20205069","displayToPublicDate":"2020-07-31T18:00:00","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":"2020-5069","displayTitle":"Incipient Bed-Movement and Flood-Frequency Analysis using Hydrophones to Estimate Flushing Flows on the Upper Colorado River, Colorado, 2019","title":"Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019","docAbstract":"In 2019, the U.S. Geological Survey, in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group, studied the magnitude and recurrence interval of streamflow (discharge) needed to initiate bed movement of gravel-sized and finer sediment in a segment of the Colorado River in Colorado to better understand sediment movement and its relation to flow regimes of the river. The study area extended from the confluence of the Blue and Colorado Rivers near Kremmling, Colorado, downstream to the confluence of the Eagle and Colorado Rivers near Dotsero, Colo. Bed movement occurred more frequently and at lower streamflows from State Bridge to Catamount Bridge compared to the study area upstream from State Bridge. As a result, the flushing flow was characterized in the study area using two definitions: the “upstream flushing flow” for locations above State Bridge and the “downstream flushing flow” for locations below State Bridge.
Acoustic data from stationary hydrophones continuously deployed in the spring and summer of 2019 and longitudinal hydrophone acoustic profiles manually collected in summer 2019 were used to identify the streamflow needed for incipient gravel-bed movement and establish flushing flows defined for this study. The upstream flushing flow was defined as 3,000 cubic feet per second (ft3/s) at streamgage 09058000 Colorado River near Kremmling, Colo. (the Kremmling streamgage) based on the underwater acoustic data from the downstream location at the Radium stationary site (2,950 ft3/s at the Kremmling streamgage which was rounded to 3,000 ft3/s). The downstream flushing flow was defined as 2,400 ft3/s at the Kremmling streamgage or 3,100 ft3/s at streamgage 09060799 Colorado River at Catamount Bridge, Colo. (the Catamount Bridge streamgage) based on the more conservative streamflow associated with the flushing flow defined using underwater acoustic data from the downstream location at the above Catamount Bridge stationary site (2,310 ft3/s at the Kremmling streamgage which was rounded to 2,400 ft3/s and 3,040 ft3/s at the Catamount Bridge streamgage which was rounded to 3,100 ft3/s).
The annual series of peak-streamflow data at the Kremmling streamgage were used to estimate annual exceedance probability (AEP) streamflows to compare to the flushing flow. Results from the Denver Water Platte and Colorado Simulation Model were used to generate daily peak-streamflows for a future conditions scenario provided for this report. The upstream flushing flow of approximately 3,000 ft3/s at the Kremmling streamgage has an AEP near 0.50 (2-year return period) depending on the period of historical record and an AEP near 0.43 (2.33-year return period) for the future period. The downstream flushing flow of approximately 2,400 ft3/s at the Kremmling streamgage has an AEP near 0.67 (1.5-year return period) depending on the period of historical record and an AEP near 0.67 (1.5-year return period) for the future period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205069","collaboration":"Prepared in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group and the Colorado River Water Conservation District","usgsCitation":"Kohn, M.S., Marineau, M.D., Hempel, L.A., and McDonald, R.R., 2020, Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5069, 39 p., https://doi.org/10.3133/sir20205069.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114386","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":376916,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J5L78O","text":"USGS data release","linkHelpText":"Acoustic, Spatial, and Sediment Size Data 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Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
The documentation of hybrids between distantly related taxa can illustrate an initial step to explain how genes might move between species that do not exhibit complete reproductive isolation. In birds, some of the most phylogenetically distant hybrid combinations occur between genera. Traditionally, morphological and plumage characters have been used to assign the identity of the parental species of a putative hybrid, although recently, nuclear introns also have been used. Here, we demonstrate how high-throughput short-read DNA sequence data can be used to identify the parentage of a putative intergeneric hybrid, in this case between a blue-winged warbler (Vermivora cyanoptera) and a cerulean warbler (Setophaga cerulea). This hybrid had mitochondrial DNA of a cerulean warbler, indicating the maternal parent. For hundreds of single nucleotide polymorphisms within six regions of the nuclear genome that differentiate blue-winged warblers and golden-winged warblers (Vermivora chrysoptera), the hybrid had roughly equal ancestry assignment to blue-winged and cerulean warblers, suggesting a blue-winged warbler as the paternal parent species and demonstrating that this was a first generation (F1) hybrid between these species. Unlike other recently characterized intergeneric warbler hybrids, this individual hybrid learned to song match its maternal parent species, suggesting that it might have been the result of an extra-pair mating and raised in a cerulean warbler nest.
","language":"English","publisher":"The Linnean Society of London","doi":"10.1093/biolinnean/blaa085","usgsCitation":"Toews, D.P., Kramer, G., Jones, A., Brennan, C.L., Cloud, B.E., Andersen, D.E., Lovette, I., and Streby, H., 2020, Genomic identification of intergeneric hybrids in New World wood-warblers (Aves: Parulidae): Biological Journal of the Linnean Society, v. 131, no. 1, p. 183-191, https://doi.org/10.1093/biolinnean/blaa085.","productDescription":"9 p.","startPage":"183","endPage":"191","ipdsId":"IP-117499","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":455813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biolinnean/blaa085","text":"Publisher Index Page"},{"id":395918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Toews, David","contributorId":276164,"corporation":false,"usgs":false,"family":"Toews","given":"David","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kramer, Gunnar R.","contributorId":276165,"corporation":false,"usgs":false,"family":"Kramer","given":"Gunnar R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":834621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Andrew W.","contributorId":276166,"corporation":false,"usgs":false,"family":"Jones","given":"Andrew W.","affiliations":[{"id":56931,"text":"Cleveland Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":834622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brennan, Courtney L.","contributorId":276167,"corporation":false,"usgs":false,"family":"Brennan","given":"Courtney","email":"","middleInitial":"L.","affiliations":[{"id":56931,"text":"Cleveland Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":834623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cloud, Benjamin E.","contributorId":276168,"corporation":false,"usgs":false,"family":"Cloud","given":"Benjamin","email":"","middleInitial":"E.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":834624,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834619,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lovette, Irby J.","contributorId":276169,"corporation":false,"usgs":false,"family":"Lovette","given":"Irby J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":834625,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Streby, Henry","contributorId":276170,"corporation":false,"usgs":false,"family":"Streby","given":"Henry","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":834626,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211568,"text":"ofr20201052 - 2020 - Calibration of the U.S. Geological Survey National Crustal Model","interactions":[],"lastModifiedDate":"2020-08-05T18:39:28.395394","indexId":"ofr20201052","displayToPublicDate":"2020-07-31T12:40:00","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":"2020-1052","displayTitle":"Calibration of the U.S. Geological Survey National Crustal Model","title":"Calibration of the U.S. Geological Survey National Crustal Model","docAbstract":"The U.S. Geological Survey National Crustal Model (NCM) is being developed to include spatially varying estimates of site response in seismic hazard assessments. Primary outputs of the NCM are continuous velocity and density profiles from the Earth’s surface to the mantle transition zone at 410-kilometer (km) depth for each location on a 1-km grid across the conterminous United States. Datasets used to produce the NCM may have a resolution of better than 1 km near the Earth’s surface in some regions, but, with increasing depth, NCM resolution decreases to tens to hundreds of kilometers in the mantle. Basic subsurface information is provided by the NCM geologic framework, thermal model, and petrologic and mineral physics database. In this report, the velocities and densities that can be extracted from the NCM are calibrated through the development of a porosity model based on Biot-Gassmann theory and more than 2,000 compressional- and (or) shear-wave velocity profiles less than 10 km deep from across the conterminous United States and southwestern Canada.
Sediment and rock porosities are derived from shear-wave velocity and are found to depend on effective pressure, rock type, and age (for sedimentary and extrusive volcanic deposits). Porosity-effective pressure functions are then estimated for each rock type (and age for sedimentary and extrusive volcanic deposits). Unconsolidated sediments are found to have higher porosities than consolidated units, which have higher porosities than unweathered igneous units; young sedimentary units (for example, Quaternary age units) tend to have higher porosities than older sedimentary units (for example, pre-Cenozoic age units); porosity decreases with increasing effective pressure; and porosities can decrease quickly through the weathered layer of intrusive rocks.
Comparing two Los Angeles area velocity models and the U.S. Geological Survey Bay Area velocity model with the NCM, the NCM does a better job on average of reproducing observed shear-wave velocities below 1 km per second because it has less bias and uncertainty. Approaching and above 1 km per second, the NCM tends to underpredict observed shear-wave velocity. Whereas several factors could contribute to this, the primary factor is probably bias in the NCM geologic framework. For example, the NCM will predict lower velocities in places where the depth to bedrock and basement appear shallower in the measured velocity profiles than specified in the NCM geologic framework. With regard to observed compressional-wave velocity and density, the NCM has significantly less bias than California models for the former, especially below 2 km per second, and all models tend to overpredict density for densities less than about 2,200 kilograms per cubic meter.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201052","usgsCitation":"Boyd, O.S., 2020, Calibration of the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2020–1052, 23 p., https://doi.org/10.3133/ofr20201052.","productDescription":"Report: vi, 23 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115717","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436847,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ5LNU","text":"USGS data release","linkHelpText":"GeoPhys"},{"id":376928,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1052/ofr20201052.pdf","text":"Report","size":"6.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1052"},{"id":376929,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GO3CP8","text":"USGS 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U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 10th international conference on gas hydrates (ICGH10)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"US Department of Energy – NETL Program","usgsCitation":"Okinaka, N., Boswell, R., Collett, T., Yamamoto, K., and Anderson, B., 2020, Progress toward the establishment of an extended-duration gas hydrate reservoir response test on the Alaska North Slope, in Proceedings of the 10th international conference on gas hydrates (ICGH10), 2 p.","productDescription":"2 p.","ipdsId":"IP-115391","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":382606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378298,"type":{"id":15,"text":"Index Page"},"url":"https://www.netl.doe.gov/node/10037"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -163.65234374999997,\n 67.55894799883033\n ],\n [\n -143.0419921875,\n 67.55894799883033\n ],\n [\n -143.0419921875,\n 71.55274065141299\n ],\n [\n -163.65234374999997,\n 71.55274065141299\n ],\n [\n -163.65234374999997,\n 67.55894799883033\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Okinaka, Norihiro","contributorId":240094,"corporation":false,"usgs":false,"family":"Okinaka","given":"Norihiro","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":798394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boswell, Ray","contributorId":240095,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":48085,"text":"United States Department of Energy","active":true,"usgs":false}],"preferred":false,"id":798395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220812,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":798396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yamamoto, Koji","contributorId":240096,"corporation":false,"usgs":false,"family":"Yamamoto","given":"Koji","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":798397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Brian","contributorId":240097,"corporation":false,"usgs":false,"family":"Anderson","given":"Brian","affiliations":[{"id":48085,"text":"United States Department of Energy","active":true,"usgs":false}],"preferred":false,"id":798398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217064,"text":"70217064 - 2020 - A synthesis of ten years of chemical contaminant monitoring data in National Park Service - Southeast and southwest Alaska networks","interactions":[],"lastModifiedDate":"2021-01-04T18:49:06.717694","indexId":"70217064","displayToPublicDate":"2020-07-31T09:37:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NOS/MCCOS 277","title":"A synthesis of ten years of chemical contaminant monitoring data in National Park Service - Southeast and southwest Alaska networks","docAbstract":"With the exception of PAHs and trace metals, which were detected at 100% of the sites, all of the other contaminants were detected at varying frequencies. PBBs, Mirex and Endosulfans were not detected in any of the samples and Chlorpyrifos was only detected in five samples across four sites. Chlordanes were present at 79% of the sites while Butyltins were only detected at 20% of the sites. Overall, the majority of the concentrations can be considered to be at background levels when compared to the long-term NOAA National Status and Trends (NS&T) monitoring data for blue mussels nationwide. The relatively high concentrations of cadmium, copper, and nickel in comparison to the NS&T national groups could be a combination of natural inputs and anthropogenic sources. The natural exposure and weathering of rocks in southern Alaska can contribute to elevated background concentrations of these metals. Sample concentrations, compositions and/or trends for Total DDT, Total Dieldrins and Total HCHs suggest that these contaminants are no longer bioaccumulating at detectable levels. Total Butyltin concentrations were low compared to the NS&T national concentrations, but the presence of tributyltin (TBT) in recent years at Sitka Visitor's Center (SITK) and Skagway Harbor (SKWY) indicates that fresh sources of Butyltin are still entering these environments, probably through vessel traffic at these sites. The PAH profiles and higher concentrations at SITK, SKWY and Nahku Bay East Side (NBES) suggest that these sites are receiving anthropogenic sources of PAH contamination.
The results included in this report help to provide a greater understanding of general background contamination in NPS SWAN and SEAN parks, as well as other monitoring sites, including range, trends and variability. Future monitoring should aim to continue analyzing the temporal trends of these contaminants on a regional scale through periodic sampling as well as focusing on areas of interest that could shed further insight on range and variation (see supplemental material).
","language":"English","publisher":"NOAA","doi":"10.25923/dbyq-7z17","usgsCitation":"Rider, M., Apeti, D., Jacob, A., Kimbrough, K.L., Davenport, E., Bower, M.R., Colletti, H.A., and Esler, D., 2020, A synthesis of ten years of chemical contaminant monitoring data in National Park Service - Southeast and southwest Alaska networks: NOAA Technical Memorandum NOS/MCCOS 277, 102 p., https://doi.org/10.25923/dbyq-7z17.","productDescription":"102 p.","ipdsId":"IP-119449","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":381801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -131.2646484375,\n 56.31653672211301\n ],\n [\n -135.5712890625,\n 59.734253447591364\n ],\n [\n -140.537109375,\n 60.673178565817715\n ],\n [\n -141.1962890625,\n 64.66151739623564\n ],\n [\n -144.8876953125,\n 65.31182925383723\n ],\n [\n -160.0927734375,\n 64.14895190024562\n ],\n [\n -166.4208984375,\n 61.60639637138628\n ],\n [\n -161.9384765625,\n 59.0405546167585\n ],\n [\n -157.5,\n 58.60833366077633\n ],\n [\n -164.13574218749997,\n 54.97761367069628\n ],\n [\n -152.75390624999997,\n 57.088515327886505\n ],\n [\n -149.2822265625,\n 59.734253447591364\n ],\n [\n -145.7666015625,\n 60.06484046010452\n ],\n [\n -136.494140625,\n 57.326521225217064\n ],\n [\n -132.8466796875,\n 55.10351605801967\n ],\n [\n -131.2646484375,\n 56.31653672211301\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rider, Mary","contributorId":245991,"corporation":false,"usgs":false,"family":"Rider","given":"Mary","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":807457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Apeti, Dennis","contributorId":245992,"corporation":false,"usgs":false,"family":"Apeti","given":"Dennis","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":807458,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacob, Annie","contributorId":245993,"corporation":false,"usgs":false,"family":"Jacob","given":"Annie","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":807459,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kimbrough, Kimani L.","contributorId":139223,"corporation":false,"usgs":false,"family":"Kimbrough","given":"Kimani","email":"","middleInitial":"L.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":807460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davenport, Erik","contributorId":245994,"corporation":false,"usgs":false,"family":"Davenport","given":"Erik","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":807461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bower, Michael R.","contributorId":198632,"corporation":false,"usgs":false,"family":"Bower","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":807462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Colletti, Heather A","contributorId":199047,"corporation":false,"usgs":false,"family":"Colletti","given":"Heather","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":807527,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":true,"id":807464,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220279,"text":"70220279 - 2020 - Quarterly wildlife mortality report July 2020","interactions":[],"lastModifiedDate":"2023-10-13T13:41:12.547149","indexId":"70220279","displayToPublicDate":"2020-07-31T07:53:17","publicationYear":"2020","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9359,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":30}},"title":"Quarterly wildlife mortality report July 2020","docAbstract":"The USGS National Wildlife Health Center (NWHC) Quarterly Mortality Report provides brief summaries of epizootic mortality and morbidity events by quarter. The write-ups, highlighting epizootic events and other wildlife disease topics of interest, are published in the Wildlife Disease Association quarterly newsletter. A link is provided in this WDA newsletter to the Wildlife Health Information Sharing Partnership event reporting system (WHISPers) so readers can view associated data.","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Ballmann, A., Bodenstein, B., Dusek, R.J., and Sleeman, J.M., 2020, Quarterly wildlife mortality report July 2020: Wildlife Disease Association Newsletter, p. 12-14.","productDescription":"3 p.","startPage":"12","endPage":"14","ipdsId":"IP-120249","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":385415,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385395,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":219535,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":815000,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223845,"text":"70223845 - 2020 - Population assessment and potential functional roles of native mussels in the Upper Hudson River","interactions":[],"lastModifiedDate":"2021-09-10T12:34:28.629538","indexId":"70223845","displayToPublicDate":"2020-07-31T07:30:09","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Population Assessment and Potential Functional Roles of Native Mussels in the Upper Hudson River","title":"Population assessment and potential functional roles of native mussels in the Upper Hudson River","docAbstract":"General Electric Company (GE) directly and indirectly released polychlorinated biphenyls (PCBs) into the Hudson River and the surrounding environment starting in the late 1940’s, making it one of the most PCB-contaminated rivers in North America. Source control at two GE plant sites was implemented in 2009 to stem the influx of PCBs into the river (NYSDEC 2004; Farrar 2013; NYSDEC 2015). The Hudson River, like many other rivers, contains populations of native freshwater mussels—a group of animals that perform vital functions in freshwater systems. While there was anecdotal evidence of mussels residing in the Upper Hudson River (north of Troy, NY; GE 2005, GE 2009), quantitative data on mussel assemblages was lacking. Systematic, quantitative surveys for native mussels were completed in 2013 and 2015 in a total of six pools of the Upper Hudson River including one reference pool (Feeder Dam) located upstream of the former GE plant sites and five contaminated pools downstream of the GE plant sites (Thompson Island, Fort Miller, Northumberland, Stillwater, and Upper Mechanicville). Surveys were designed to estimate species composition, relative abundance, population size, population structure, and ecological services (i.e., biomass and filtration) of mussel communities prior to and after remedial actions to remove PCB contaminated sediments (i.e., dredged and subsequently capped or backfilled). In most pools, the experimental design incorporated stratification on remediated (before or after remedial activities were completed) and non-remediated areas.\n... \n\n(access to the full abstract is restricted)","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Hudson River Natural Resource Damage Assessment","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Hudson River Natural Resource Trustees","collaboration":"Hudson River Natural Resource Trustees; National Oceanic and Atmospheric Administration; New York State Department of Environmental Conservation; US Department of the Interior","usgsCitation":"Mayer, D.A., Newton, T., and Rogala, J.T., 2020, Population assessment and potential functional roles of native mussels in the Upper Hudson River, x, 142 p.","productDescription":"x, 142 p.","ipdsId":"IP-094734","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":389053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389046,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/northeast/ecologicalservices/HudsonRiver/docs/Population_Assessment_and_Potential_Functional_Roles_of_Native_Mussels_in_the_Upper_Hudson_River_Finalw.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Upper Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.992919921875,\n 42.78733853171998\n ],\n [\n -73.564453125,\n 42.78733853171998\n ],\n [\n -73.564453125,\n 43.30119623257966\n ],\n [\n -73.992919921875,\n 43.30119623257966\n ],\n [\n -73.992919921875,\n 42.78733853171998\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mayer, Denise A.","contributorId":140296,"corporation":false,"usgs":false,"family":"Mayer","given":"Denise","email":"","middleInitial":"A.","affiliations":[{"id":13400,"text":"New York State Museum, Cambridge Field Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":822913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newton, Teresa J. 0000-0001-9351-5852","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":78696,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":822914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":822915,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227404,"text":"70227404 - 2020 - Radiocarbon dating of tsunami and storm deposits","interactions":[],"lastModifiedDate":"2022-01-14T14:13:31.416486","indexId":"70227404","displayToPublicDate":"2020-07-31T07:10:09","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"30","title":"Radiocarbon dating of tsunami and storm deposits","docAbstract":"Radiocarbon age determinations can be an expedient and accurate means to assign age to deposits of tsunami or storm origin. Essential to the process of incorporating radiocarbon age determinations in tsunami or coastal storm investigations is an awareness on the part of the investigator that a sample will always return an age from a laboratory, but only carefully selected samples inform deposit age. Samples that inform deposit age are of two fundamentally different sample types, in-growth-position samples and detrital samples. For both in-growth-position samples and detrital samples, stratigraphic context is the critical information needed to evaluate how well sample age can constrain deposit age. Well constrained deposit ages require bracketing samples collected to provide both maximum and minimum limiting ages for the deposit(s) of interest. Therefore, sampling should be carried out with the intention of multiple sample submissions for age in order to optimize the potential for acquiring closely limiting ages. If there are multiple age determinations within a stratigraphic sequence that contains tsunami or storm deposits, then the calibrated radiocarbon ages can be, and should be, framed within a Bayesian model structure to better constrain deposit ages. Such models can be further improved by the incorporation of independent stratigraphic age information.
The spatial-temporal evolution of intracontinental faults and the forces that drive their style, orientation, and timing are central to understanding tectonic processes. Intracontinental NW-striking dextral faults in the Gabbs Valley–Gillis Ranges (hereafter referred to as the GVGR), Nevada, define a structural domain known as the eastern Central Walker Lane located east of the western margin of the North American plate. To consider how changes in boundary type along the western margin of the North American plate influenced both the initiation and continued dextral fault slip to the present day in the GVGR, we combine our new detailed geologic mapping, structural studies, and 40Ar/39Ar geochronology with published geologic maps to calculate early to middle Miocene dextral fault-slip rates. In the GVGR, Mesozoic basement is nonconformably overlain by a late Oligocene to Miocene sequence dominated by tuffs, lavas, and sedimentary rocks. These rocks are cut and offset by four primary NW-striking dextral faults, from east to west the Petrified Spring, Benton Spring, Gumdrop Hills, and Agai Pah Hills–Indian Head faults. A range of geologic markers, including tuff- and lava-filled paleovalleys, the southern extent of lava flows, and a normal fault, show average dextral offset magnitudes of 9.6 ± 1.1 km, 7.0 ± 1.7 km, 9.7 ± 1.0 km, and 4.9 ± 1.1 km across the four faults, respectively. Cumulative dextral offset across the GVGR is 31.2 ± 2.3 km. Initiation of slip along the Petrified Spring fault is tightly bracketed between 15.99 ± 0.05 Ma and 15.71 ± 0.03 Ma, whereas slip along the other faults initiated after 24.30 ± 0.05 Ma to 20.14 ± 0.26 Ma. Assuming that slip along all four faults initiated at the same time as the Petrified Spring fault yields calculated dextral fault-slip rates of 0.4 ± 0.1–0.6 ± 0.1 mm/yr, 0.4 ± 0.1–0.5 ± 0.1 mm/yr, 0.6 ± 0.1 mm/yr, and 0.3 ± 0.1 mm/yr on the four faults, respectively. Middle Miocene initiation of dextral fault slip across the GVGR overlaps with the onset of normal slip along range-bounding faults in the western Basin and Range to the north and the northern Eastern California shear zone to the south. Based on this spatial-temporal relationship, we propose that dextral fault slip across the GVGR defines a kinematic link or accommodation zone between the two regions of extension. At the time of initiation of dextral slip across the GVGR, the plate-boundary setting to the west was characterized by subduction of the Farallon plate beneath the North American plate. To account for the middle Miocene onset of extension across the Basin and Range and dextral slip in the GVGR, we hypothesize that middle Miocene trench retreat drove westward motion of the Sierra Nevada and behind it, crustal extension across the Basin and Range and NW-dextral shear within the GVGR. During the Pliocene, the plate boundary to the west changed to NW-dextral shear between the Pacific and North American plates, which drove continued dextral slip along the same faults within the GVGR because they were fortuitously aligned subparallel to plate boundary motion.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/GES02240.1","usgsCitation":"Lee, J., Hoxey, A., Calvert, A.T., and Dubyoski, P., 2020, Plate boundary trench retreat and dextral shear drive intracontinental fault-slip histories: Neogene dextral faulting across the Gabbs Valley and Gillis Ranges, Central Walker Lane, Nevada: Geosphere, v. 16, no. 5, p. 1249-1275, https://doi.org/10.1130/GES02240.1.","productDescription":"27 p.","startPage":"1249","endPage":"1275","ipdsId":"IP-118599","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":487674,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02240.1","text":"Publisher Index Page"},{"id":482372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Staes","state":"Nevada","otherGeospatial":"Central Walker Lane, Gabbs Valley, Ranges,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.19526377053958,\n 38.901098488196595\n ],\n [\n -119.19526377053958,\n 38.00221464328254\n ],\n [\n -117.79785043469002,\n 38.00221464328254\n ],\n [\n -117.79785043469002,\n 38.901098488196595\n ],\n [\n -119.19526377053958,\n 38.901098488196595\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Jeffrey","contributorId":193437,"corporation":false,"usgs":false,"family":"Lee","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":928197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoxey, Andrew K.R.","contributorId":351219,"corporation":false,"usgs":false,"family":"Hoxey","given":"Andrew K.R.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":928198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":928199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dubyoski, Peter","contributorId":351220,"corporation":false,"usgs":false,"family":"Dubyoski","given":"Peter","affiliations":[{"id":26935,"text":"Central Washington University","active":true,"usgs":false}],"preferred":false,"id":928200,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70213241,"text":"70213241 - 2020 - The pervasive and multifaceted influence of biocrusts on water in the world’s drylands","interactions":[],"lastModifiedDate":"2020-09-24T16:21:19.257777","indexId":"70213241","displayToPublicDate":"2020-07-30T10:45:59","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":"The pervasive and multifaceted influence of biocrusts on water in the world’s drylands","docAbstract":"The capture and use of water are critically important in drylands, which collectively constitute Earth's largest biome. Drylands will likely experience lower and more unreliable rainfall as climatic conditions change over the next century. Dryland soils support a rich community of microphytic organisms (biocrusts), which are critically important because they regulate the delivery and retention of water. Yet despite their hydrological significance, a global synthesis of their effects on hydrology is lacking. We synthesized 2,997 observations from 109 publications to explore how biocrusts affected five hydrological processes (times to ponding and runoff, early [sorptivity] and final [infiltration] stages of water flow into soil, and the rate or volume of runoff) and two hydrological outcomes (moisture storage, sediment production). We found that increasing biocrust cover reduced the time for water to pond on the surface (−40%) and commence runoff (−33%), and reduced infiltration (−34%) and sediment production (−68%). Greater biocrust cover had no significant effect on sorptivity or runoff rate/amount, but increased moisture storage (+14%). Infiltration declined most (−56%) at fine scales, and moisture storage was greatest (+36%) at large scales. Effects of biocrust type (cyanobacteria, lichen, moss, mixed), soil texture (sand, loam, clay), and climatic zone (arid, semiarid, dry subhumid) were nuanced. Our synthesis provides novel insights into the magnitude, processes, and contexts of biocrust effects in drylands. This information is critical to improve our capacity to manage dwindling dryland water supplies as Earth becomes hotter and drier.
Botswana’s Okavango Delta is a World Heritage Site and biodiverse wilderness. In 2016–2018, following arrival of the annual flood of rainwater from Angola’s highlands, and using continuous oxygen logging, we documented profound aquatic hypoxia that persisted for 3.5 to 5 months in the river channel. Within these periods, dissolved oxygen rarely exceeded 3 mg/L and dropped below 0.5 mg/L for up to two weeks at a time. Although these dissolved oxygen levels are low enough to qualify parts of the Delta as a dead zone, the region is a biodiversity hotspot, raising the question of how fish survive. In association with the hypoxia, histological samples, collected from native Oreochromis andersonii (threespot tilapia), Coptodon rendalli (redbreast tilapia), and Oreochromis macrochir (greenhead tilapia), exhibited widespread hepatic and splenic inflammation with marked granulocyte infiltration, melanomacrophage aggregates, and ceroid and hemosiderin accumulations. It is likely that direct tissue hypoxia and polycythemia-related iron deposition caused this pathology. We propose that Okavango cichlids respond to extended natural hypoxia by increasing erythrocyte production, but with significant health costs. Our findings highlight seasonal hypoxia as an important recurring stressor, which may limit fishery resilience in the Okavango as concurrent human impacts rise. Moreover, they illustrate how fish might respond to hypoxia elsewhere in the world, where dead zones are becoming more common.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0235667","usgsCitation":"Edwards, T.M., Mosie, I.J., Moore, B.C., Lobjoit, G., Schiavone, K., Bachman, R.E., and Murray-Hudson, M., 2020, Low oxygen: A (tough) way of life for Okavango fishes: PLoS ONE, v. 15, no. 7, e0235667, 23 p., https://doi.org/10.1371/journal.pone.0235667.","productDescription":"e0235667, 23 p.","ipdsId":"IP-108304","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":455818,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0235667","text":"Publisher Index Page"},{"id":378907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Botswana","otherGeospatial":"Okavango Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 21.082763671875,\n -20.184879384574092\n ],\n [\n 24.114990234374996,\n -20.184879384574092\n ],\n [\n 24.114990234374996,\n -18.323240460443387\n ],\n [\n 21.082763671875,\n -18.323240460443387\n ],\n [\n 21.082763671875,\n -20.184879384574092\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Edwards, Thea M. 0000-0002-6176-2872","orcid":"https://orcid.org/0000-0002-6176-2872","contributorId":241635,"corporation":false,"usgs":true,"family":"Edwards","given":"Thea","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":799801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosie, Ineelo J.","contributorId":241637,"corporation":false,"usgs":false,"family":"Mosie","given":"Ineelo","email":"","middleInitial":"J.","affiliations":[{"id":48375,"text":"Okavango Research Institute, University of Botswana, Maun, Botswana","active":true,"usgs":false}],"preferred":false,"id":799802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Brandon C.","contributorId":241638,"corporation":false,"usgs":false,"family":"Moore","given":"Brandon","email":"","middleInitial":"C.","affiliations":[{"id":48377,"text":"University of the South, Sewanee, Tennessee","active":true,"usgs":false}],"preferred":false,"id":799803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lobjoit, Guy","contributorId":241639,"corporation":false,"usgs":false,"family":"Lobjoit","given":"Guy","email":"","affiliations":[{"id":48378,"text":"Guma Lagoon Camp, Etsha 13, Botswana","active":true,"usgs":false}],"preferred":false,"id":799804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schiavone, Kelsie","contributorId":241640,"corporation":false,"usgs":false,"family":"Schiavone","given":"Kelsie","email":"","affiliations":[{"id":48377,"text":"University of the South, Sewanee, Tennessee","active":true,"usgs":false}],"preferred":false,"id":799805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bachman, Robert E.","contributorId":241641,"corporation":false,"usgs":false,"family":"Bachman","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":48377,"text":"University of the South, Sewanee, Tennessee","active":true,"usgs":false}],"preferred":false,"id":799806,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray-Hudson, Mike","contributorId":241642,"corporation":false,"usgs":false,"family":"Murray-Hudson","given":"Mike","email":"","affiliations":[{"id":48375,"text":"Okavango Research Institute, University of Botswana, Maun, Botswana","active":true,"usgs":false}],"preferred":false,"id":799807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211444,"text":"ofr20201082 - 2020 - seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0","interactions":[],"lastModifiedDate":"2020-08-04T20:24:39.347599","indexId":"ofr20201082","displayToPublicDate":"2020-07-30T09:24:24","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":"2020-1082","displayTitle":"seawaveQ—An R Package Providing a Model and Utilities for Analyzing Trends in Chemical Concentrations in Streams with a Seasonal Wave (seawave) and Adjustment for Streamflow (Q) and Other Ancillary Variables, Version 2.0.0","title":"seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0","docAbstract":"The seawaveQ R package provides functionality and help to fit a parametric regression model, SEAWAVE-Q, to pesticide concentration data from stream-water samples to assess trends. The model incorporates the strong seasonality and high degree of censoring common in pesticide data, and users can incorporate numerous ancillary variables such as streamflow anomalies. The model is fitted to pesticide data using maximum likelihood methods for censored data and is robust in terms of pesticide, stream location, and degree of censoring of the concentration data. This R package standardizes this methodology for trend analysis, documents the code, and provides help and tutorial information.
In previous investigations, the SEAWAVE-Q model assumed a linear trend across the period analyzed. For short trend periods, this assumption of a linear trend is adequate. However, as the period of record analyzed becomes longer, the assumption of linearity is problematic because of changes in pesticide regulation and use, some of which can be abrupt. In this update to the model, a restricted cubic spline option was added for long trend periods. This option allows for more flexibility in the time component of the model. Bootstrap functionality is included to determine statistical significance. Model results with the new restricted cubic spline option are compared to the linear trend option for two pesticide-site combinations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201082","collaboration":"National Water Quality Program","usgsCitation":"Ryberg, K.R., and York, B.C., 2020, seawaveQ—An R package providing a model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables, version 2.0.0: U.S. Geological Survey Open-File Report 2020–1082, 25 p., https://doi.org/10.3133/ofr20201082.","productDescription":"Report: vi, 25; 3 Appendixes","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101011","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376796,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_1.pdf","text":"Appendix 1.","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 1","linkHelpText":"— Vignette for seawaveQ—An R Package Providing a Model and Utilities for Analyzing Trends in Chemical Concentrations in Streams with a Seasonal Wave (seawave) and Adjustment for Streamflow (Q) and Other Ancillary Variables"},{"id":376797,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_2.pdf","text":"Appendix 2.","size":"228 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 2","linkHelpText":"— R Documentation"},{"id":376798,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082_appendix_4.pdf","text":"Appendix 4.","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082 Appendix 4","linkHelpText":"— Model Comparisons Using seawaveQ"},{"id":376794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1082/coverthb.jpg"},{"id":376795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1082/ofr20201082.pdf","text":"Report","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1082"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD
Intraspecific variation in plant traits is a major cause of variation in herbivore feeding and performance. Plant defensive traits change as a plant grows, such that ontogeny may account for a substantial portion of intraspecific trait variation. We tested how the ontogenic stage of an individual plant, of an individual in the context of its neighboring plants, and of a patch of plants with mixed or uniform stages affect plant–herbivore interactions. To do this, we conducted an experimental study of the interactions between Lepidium draba, a perennial brassicaceous weed, and Plutella xylostella, a common herbivore of L. draba. We found that L. draba foliar glucosinolates, secondary metabolites often implicated in defense, decreased in concentration with plant age. In single-stage patches, herbivores performed similarly on L. draba plants of different ages. Furthermore, we found no difference in the cumulative performance of herbivores reared on mixed- or even-staged patches of L. draba. However, in mixed-stage patches, the damage experienced by a focal plant depended on the stage of neighboring plants, suggesting a preference hierarchy of the herbivore among plant stages. In our study, the amount of herbivory depended on the ontogenic neighborhood in which the plant grew. However, from the herbivore’s perspective, variation in plant ontogenic stage was unimportant to its success in terms of feeding rate and final weight.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-020-04702-z","usgsCitation":"Cope, O., Becker, Z., Ode, P.J., Ryan, P., and Pearse, I., 2020, Associational effects of plant ontogeny on damage by a specialist insect herbivore: Oecologia, v. 193, p. 593-602, https://doi.org/10.1007/s00442-020-04702-z.","productDescription":"10 p.","startPage":"593","endPage":"602","ipdsId":"IP-119811","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":436849,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UKSO98","text":"USGS data release","linkHelpText":"Greenhouse observations of plant herbivore interactions on Lepidium draba to test effects of ontogenic variability"},{"id":436848,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UKSO98","text":"USGS data release","linkHelpText":"Greenhouse observations of plant herbivore interactions on Lepidium draba to test effects of ontogenic variability"},{"id":382486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"193","noUsgsAuthors":false,"publicationDate":"2020-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Cope, Olivia 0000-0002-5559-8164","orcid":"https://orcid.org/0000-0002-5559-8164","contributorId":248270,"corporation":false,"usgs":false,"family":"Cope","given":"Olivia","email":"","affiliations":[{"id":49843,"text":"U Wisconsin","active":true,"usgs":false}],"preferred":false,"id":808716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Becker, Zoe","contributorId":248271,"corporation":false,"usgs":false,"family":"Becker","given":"Zoe","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":808717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ode, Paul J.","contributorId":197314,"corporation":false,"usgs":false,"family":"Ode","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":808718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Paul","contributorId":248272,"corporation":false,"usgs":false,"family":"Ryan","given":"Paul","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":808719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211224,"text":"sir20205055 - 2020 - Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system","interactions":[],"lastModifiedDate":"2021-07-02T13:31:15.859682","indexId":"sir20205055","displayToPublicDate":"2020-07-30T05:47:08","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":"2020-5055","displayTitle":"Estimating Streamflow and Base Flow Within the Nontidal Chesapeake Bay Riverine System","title":"Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system","docAbstract":"Daily mean streamflow was estimated for all the nontidal parts of the Chesapeake Bay riverine system with the Unit Flows in Networks of Channels computer application using measured streamflow at the most downstream gage of selected rivers. The streamflows estimated by the Unit Flows in Networks of Channels computer application were aggregated at the 12-digit Hydrologic Unit Code level, after which base flow was estimated by two hydrograph-separation methods. Based on six sites selected for comparison, modeled streamflows are typically within an order of magnitude of measured streamflows, and monthly mean streamflows are in better agreement than daily streamflows. For the six selected sites, the base-flow values calculated by the two hydrograph-separation methods were compared. The monthly base-flow values also were in better agreement than the daily base-flow values. The modeled data were animated to better visualize spatial and temporal variability of streamflow and base-flow index.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205055","usgsCitation":"Buffington, P.C., and Capel, P.D., 2020, Estimating streamflow and base flow within the nontidal Chesapeake Bay riverine system: U.S. Geological Survey Scientific Investigations Report 2020–5055, 26 p., https://doi.org/10.3133/sir20205055.","productDescription":"Report: v, 26 p.; Figure Animations: Figures 15–18; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098068","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":376516,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"— National Water Information System database"},{"id":376515,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P906K5GZ","text":"USGS data 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12201 Sunrise Valley Drive
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