Urban stormwater is an important but incompletely characterized contributor to surface‐water toxicity. The present study used 5 bioassays of 2 model organisms (Daphnia magnaand fathead minnow, Pimephales promelas) to investigate stormwater toxicity and mitigation by full‐scale iron‐enhanced sand filters (IESFs). Stormwater samples were collected from major stormwater conveyances and full‐scale IESFs during 4 seasonal events (winter snowmelt and spring, early summer, and late summer rainfalls) and analyzed for a diverse range of contaminants of emerging concern including pharmaceuticals, personal care products, industrial chemicals, and pesticides. Concurrently, stormwater samples were collected for toxicity testing. Seasonality appeared more influential and consistent than site type for most bioassays. Typically, biological consequences were least in early summer and greatest in late summer and winter. In contrast with the unimproved and occasionally reduced biological outcomes in IESF‐treated and late summer samples, water chemistry indicated that numbers and total concentrations of detected organic chemicals, metals, and nutrients were reduced in late summer and in IESF‐treated stormwater samples. Some potent toxicants showed more specific seasonality (e.g., high concentrations of polycyclic aromatic hydrocarbons and industrial compounds in winter, pesticides in early summer and spring, flame retardants in late summer), which may have influenced outcomes. Potential explanations for insignificant or unexpected stormwater treatment outcomes include confounding effects of complex stormwater matrices, IESF nutrient removal, and, less likely, unmonitored toxicants.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4227","usgsCitation":"Westerhoff, B.M., Fairbairn, D.J., Ferrey, M.L., Matilla, A., Kunkel, J., Elliott, S.M., Kiesling, R.L., Woodruff, D., and Schoenfuss, H.L., 2018, Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas: Environmental Toxicology and Chemistry, v. 37, no. 10, p. 2645-2659, https://doi.org/10.1002/etc.4227.","productDescription":"15 p.","startPage":"2645","endPage":"2659","ipdsId":"IP-095127","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":357842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53893","contributors":{"authors":[{"text":"Westerhoff, Benjamin M.","contributorId":208226,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fairbairn, David J.","contributorId":207455,"corporation":false,"usgs":false,"family":"Fairbairn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrey, Mark L.","contributorId":207457,"corporation":false,"usgs":false,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matilla, Adriana","contributorId":208227,"corporation":false,"usgs":false,"family":"Matilla","given":"Adriana","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunkel, Jordan","contributorId":208228,"corporation":false,"usgs":false,"family":"Kunkel","given":"Jordan","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746468,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woodruff, Dustin","contributorId":208230,"corporation":false,"usgs":false,"family":"Woodruff","given":"Dustin","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":746469,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746470,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70199755,"text":"70199755 - 2018 - Practical approaches to maximizing the resolution of sparker seismic reflection data","interactions":[],"lastModifiedDate":"2019-09-16T11:44:51","indexId":"70199755","displayToPublicDate":"2018-09-27T14:09:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2668,"text":"Marine Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Practical approaches to maximizing the resolution of sparker seismic reflection data","docAbstract":"Sparkers are a type of sound source widely used by the marine seismic community to provide high-resolution imagery of the shallow sub-bottom (i.e., < 1000 m). Although sparkers are relatively simple, inexpensive, and high-frequency (100–2500 Hz) sources, they have several potential pitfalls due to their complicated and unpredictable signature. In this study we quantify the source characteristics of several sparker systems and develop a suite of simple processing approaches for both single channel and multi-channel sparker data. In all cases, the results show improved vertical resolution and reflection coherency. Correcting for small static variations in multi-channel seismic (MCS) data is a critical first step to preserve the broad frequency content during stacking, and to reduce the shot-to-shot variability of outgoing and incoming signals. Application of predictive deconvolution to static-corrected, post-stack traces suppresses short-path multiples and restores the latent high-resolution reflection patterns. However, if shot-to-shot source signatures are recorded directly, pre-stack deterministic deconvolution followed by post-stack predictive deconvolution produces the most robust results. Processing sparker data without broadband techniques results in less confident or completely missed interpretations when compared to the broadband equivalent. If processed correctly, marine sparker data can provide exceptional sub-bottom imagery that rivals other more repeatable marine seismic sources (e.g., high-frequency air-guns).
","language":"English","publisher":"Springer","doi":"10.1007/s11001-018-9367-2","usgsCitation":"Kluesner, J.W., Brothers, D.S., Hart, P.E., Miller, N.C., and Hatcher, G.A., 2018, Practical approaches to maximizing the resolution of sparker seismic reflection data: Marine Geophysical Research, v. 40, no. 3, p. 279-301, https://doi.org/10.1007/s11001-018-9367-2.","productDescription":"12 p.","startPage":"279","endPage":"301","ipdsId":"IP-097450","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437739,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CV4FW6","text":"USGS data release","linkHelpText":"Minisparker and chirp seismic-reflection data of field activity 2014-645-FA collected in the outer Santa Barbara Channel, California, between 2014-11-12 to 2014-11-25 (ver. 2.0, March 2020)"},{"id":357841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-20","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53895","contributors":{"authors":[{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":746499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hatcher, Gerry A. 0000-0001-7705-1509 ghatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-7705-1509","contributorId":208239,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerry","email":"ghatcher@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746502,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198847,"text":"fs20183046 - 2018 - Williston Basin groundwater availability, United States and Canada","interactions":[],"lastModifiedDate":"2018-09-27T16:45:41","indexId":"fs20183046","displayToPublicDate":"2018-09-27T12:55:52","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3046","title":"Williston Basin groundwater availability, United States and Canada","docAbstract":"The Williston Basin contains important oil and gas resources for the Nation. Freshwater supplies are limited in this semiarid area, and oil and gas development can require large volumes of freshwater. Groundwater is the primary source of water for many water users in the Williston Basin, so to better understand these resources, the U.S. Geological Survey (USGS) assessed the groundwater availability in this area. The final phase of this assessment included a computer model that simulates how groundwater flows in the aquifer systems and simulates how changes in water use and natural conditions may affect the water resources. These results provide a tool for land and water-resource managers to determine how water can be used for multiple purposes in the Williston Basin. For additional information about this assessment and more in-depth descriptions and results, see Long and others (2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183046","collaboration":"Water Availability and Use Science Program","usgsCitation":"Thamke, J.N., Long, A.J., and Davis, K.W., 2018, Williston Basin groundwater availability, United States and Canada: U.S. Geological Survey Fact Sheet 2018-3046, 4 p., https://doi.org/10.3133/fs20183046.","productDescription":"Report: 4 p.; Data Releases","onlineOnly":"N","ipdsId":"IP-098105","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":357815,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3046/fs20183046.pdf","text":"Report","size":"3.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3046"},{"id":357816,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZDV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use data for hydraulic fracturing treatments in the Williston Basin, United States, 2000–2015"},{"id":357814,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3046/coverthb.jpg"},{"id":357817,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1841","text":"Professional Paper 1841","size":"18.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1841","linkHelpText":"Groundwater availability of the Williston Basin, United States and Canada"},{"id":357818,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FACTT3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of predictive simulations of groundwater response to selected scenarios in the Williston Basin, United States and Canada"}],"country":"Canada, United States","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 44\n ],\n [\n -98,\n 44\n ],\n [\n -98,\n 51\n ],\n [\n -108,\n 51\n ],\n [\n -108,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, Montana 59601
Outbreaks of plague, a flea‐vectored bacterial disease, occur periodically in prairie dog populations in the western United States. In order to understand the conditions that are conducive to plague outbreaks and potentially predict spatial and temporal variations in risk, it is important to understand the factors associated with flea abundance and distribution that may lead to plague outbreaks. We collected and identified 20,041 fleas from 6,542 individual prairie dogs of four different species over a 4‐year period along a latitudinal gradient from Texas to Montana. We assessed local climate and other factors associated with flea prevalence and abundance, as well as the incidence of plague outbreaks. Oropsylla hirsuta, a prairie dog specialist flea, and Pulex simulans, a generalist flea species, were the most common fleas found on our pairs. High elevation pairs in Wyoming and Utah had distinct flea communities compared with the rest of the study pairs. The incidence of prairie dogs with Yersinia pestis detections in fleas was low (n = 64 prairie dogs with positive fleas out of 5,024 samples from 4,218 individual prairie dogs). The results of our regression models indicate that many factors are associated with the presence of fleas. In general, flea abundance (number of fleas on hosts) is higher during plague outbreaks, lower when prairie dogs are more abundant, and reaches peak levels when climate and weather variables are at intermediate levels. Changing climate conditions will likely affect aspects of both flea and host communities, including population densities and species composition, which may lead to changes in plague dynamics. Our results support the hypothesis that local conditions, including host, vector, and environmental factors, influence the likelihood of plague outbreaks, and that predicting changes to plague dynamics under climate change scenarios will have to consider both host and vector responses to local factors.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4390","usgsCitation":"Russell, R.E., Abbott, R.C., Tripp, D.W., and Rocke, T.E., 2018, Local factors associated with on‐host flea distributions on prairie dog colonies: Ecology and Evolution, v. 8, no. 17, p. 8951-8972, https://doi.org/10.1002/ece3.4390.","productDescription":"22 p.; Data Release","startPage":"8951","endPage":"8972","ipdsId":"IP-098871","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460839,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4390","text":"Publisher Index Page"},{"id":357829,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418306,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM79CK"}],"volume":"8","issue":"17","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53899","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":746473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199749,"text":"70199749 - 2018 - Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","interactions":[],"lastModifiedDate":"2018-09-27T12:14:07","indexId":"70199749","displayToPublicDate":"2018-09-27T12:14:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","docAbstract":"Bioenergetics modeling was used to assess the relative importance of food availability and water temperature in determining walleye (Sander vitreus) growth. Temperature regimes experienced by both female and male adult walleye in three basins of Lake Huron and in Lake Erie were determined by use of surgically implanted temperature loggers and acoustic telemetry. Temperatures experienced by walleye were higher in Lake Erie than in Lake Huron. Walleye from Lake Erie grew at nearly double the rate of walleye from Lake Huron, and mass at age for adult females averaged about 50% greater than that for adult males in both lakes. Food consumption rate for an average adult walleye in Lake Erie was nearly twice as high as that in Lake Huron. Interbasin and interlake variability in temperature regimes accounted for a moderate degree of variability in walleye growth. We concluded that the driver for faster growth in Lake Erie compared with Lake Huron was higher food availability in Lake Erie compared with Lake Huron. The sex difference in temperature regimes explained 15% of the sex difference in Lake Erie walleye growth.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0280","usgsCitation":"Madenjian, C.P., Hayden, T., Peat, T.B., Vandergoot, C., Fielder, D.G., Gorman, A.M., Pothoven, S.A., Dettmers, J.M., Cooke, S., Zhao, Y., and Krueger, C., 2018, Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 10, p. 1573-1586, https://doi.org/10.1139/cjfas-2017-0280.","productDescription":"14 p.","startPage":"1573","endPage":"1586","ipdsId":"IP-081676","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":460841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2017-0280","text":"External 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Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":746478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":746480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":746481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhao, Yingming","contributorId":205147,"corporation":false,"usgs":false,"family":"Zhao","given":"Yingming","email":"","affiliations":[{"id":37034,"text":"Ontario Ministry of Natural Resources and Forestry, Aquatic Research and Monitoring Section","active":true,"usgs":false}],"preferred":false,"id":746482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krueger, Charles C.","contributorId":67821,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles C.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":746483,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70198658,"text":"ofr20181130 - 2018 - U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Haynesville Formation, U.S. Gulf Coast, 2016","interactions":[],"lastModifiedDate":"2018-09-27T15:15:32","indexId":"ofr20181130","displayToPublicDate":"2018-09-27T11:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1130","title":"U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Haynesville Formation, U.S. Gulf Coast, 2016","docAbstract":"In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Haynesville Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Haynesville Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for four assessment units (AUs): (1) Haynesville Western Shelf Carbonate Gas and Oil AU, (2) Haynesville Eastern Shelf Sandstone and Carbonate Oil and Gas AU, (3) Haynesville Shale Continuous Gas AU, and (4) Haynesville Shale Peripheral Continuous Gas AU. The revised assessment resulted in total estimated mean resources of 1.1 billion barrels of oil, 195.8 trillion cubic feet of gas, and 866 million barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Haynesville Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181130","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Haynesville Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1130, 62 p., https://doi.org/10.3133/ofr20181130.","productDescription":"iii, 62 p.","onlineOnly":"Y","ipdsId":"IP-098784","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1130/ofr20181130.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1130"},{"id":357709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1130/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey completed a geology-based assessment of undiscovered, technically recoverable oil and gas resources in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region. Haynesville Formation conventional oil and gas production began in the late 1930s, whereas Bossier Formation production began in the early 1970s. Production of continuous gas resources from both formations began in 2006–7. Most of the current activity is focused on natural gas production from Haynesville and Bossier shales using horizontal wells and hydraulic fracturing. In 2016, the U.S. Geological Survey assessed technically recoverable mean resources of 4 billion barrels of oil and 304.4 trillion cubic feet of gas in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181135","usgsCitation":"Paxton, S.T., 2018, Assessment of oil and gas resources in the Upper Jurassic Haynesville and Bossier Formations, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1135, 13 p., https://doi.org/10.3133/ofr20181135.","productDescription":"ii, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-098785","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1135/ofr20181135.pdf","text":"Report","size":"9.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1135"},{"id":357756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1135/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville and Bossier Formations","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Bossier Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Bossier Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for three assessment units (AUs): (1) Bossier Eastern Shelf Sandstone Gas and Oil AU, (2) Bossier Western Shelf Sandstone Gas AU, and (3) Bossier Shale Continuous Gas AU. A fourth assessment unit, the Upper Jurassic Downdip Continuous Gas AU, was also defined but was not quantitatively assessed because of limited well data within the extent of the AU. The revised assessment resulted in total estimated mean resources of 2.9 billion barrels of oil, 108.6 trillion cubic feet of gas, and 1.1 billion barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Bossier Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181134","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Bossier Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1134, 48 p., https://doi.org/10.3133/ofr20181134.","productDescription":"iii, 48 p.","onlineOnly":"Y","ipdsId":"IP-098783","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1134/coverthb.jpg"},{"id":357712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1134/ofr20181134.pdf","text":"Report","size":"960 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1134"}],"otherGeospatial":"Upper Jurassic Bossier Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The Williston Basin of the Northern Great Plains is a sedimentary basin—a geologic bowl-like structure filled with layered sedimentary rocks dating as far back as the Paleozoic age. The basin, which is nationally important for the production of energy resources, spans Montana, North Dakota, and South Dakota in the United States, and Manitoba and Saskatchewan in Canada. The three uppermost principal aquifer systems are the glacial, lower Tertiary, and Upper Cretaceous aquifer systems. As deep as 3,000 feet (ft) at the center of the basin, these are the most accessible aquifer systems in the basin and are the primary sources of potable groundwater in much of this area. The glacial aquifer system consists of Quaternary-age unconsolidated till, silt, clay, outwash sand and gravel, and occasional cobbles and boulders. The lower Tertiary and Upper Cretaceous aquifer systems consist primarily of sandstone, siltstone, mudstone, shale, and coal.
As energy demands have increased in the basin, horizontal drilling and hydraulic-fracturing have been used (especially since 2005) to develop previously inaccessible formations—namely, the Bakken and Three Forks Formations. The basin has yielded a large supply of domestic oil and natural gas since the 1950s, but the technologies required to extract those materials use large amounts of freshwater. The increasing freshwater demands of energy production in the Williston Basin, in addition to population growth, have led to a need for new tools to assess groundwater resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1841","collaboration":"Water Availability and Use Science Program","usgsCitation":"Long, A.J., Thamke, J.N., Davis, K.W., and Bartos, T.T., 2018, Groundwater availability of the Williston Basin, United States and Canada: U.S. Geological Survey Professional Paper 1841, 42 p., https://doi.org/10.3133/pp1841.","productDescription":"Report: viii, 42 p.; Data releases","onlineOnly":"Y","ipdsId":"IP-095100","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":357810,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZDV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use data for hydraulic fracturing treatments in the Williston Basin, United States, 2000–2015"},{"id":357812,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183046","text":"Fact Sheet 2018–3046","description":"FS 2018-3046"},{"id":357811,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FACTT3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of predictive simulations of groundwater response to selected scenarios in the Williston Basin, United States and Canada"},{"id":357808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1841/coverthb.jpg"},{"id":357809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1841/pp1841.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1841"}],"country":"Canada, United States","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 44\n ],\n [\n -98,\n 44\n ],\n [\n -98,\n 51\n ],\n [\n -108,\n 51\n ],\n [\n -108,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, Montana 59601
Variation in life‐history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among‐individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness‐related traits among otherwise‐identical individuals. An improved understanding of life‐history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33‐yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among‐individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non‐breeders. We detected age‐related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life‐history traits. We found that among‐individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life‐history theory, is the first to provide a thorough assessment of variation in important vital rates for a long‐lived, high‐latitude marine mammal while taking full advantage of recent developments in model evaluation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2481","usgsCitation":"Paterson, J.T., Rotella, J.J., Link, W.A., and Garrott, R.A., 2018, Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity: Ecology, v. 99, no. 10, p. 2385-2396, https://doi.org/10.1002/ecy.2481.","productDescription":"12 p.","startPage":"2385","endPage":"2396","ipdsId":"IP-099409","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2481","text":"Publisher Index Page"},{"id":357774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-12","publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538a9","contributors":{"authors":[{"text":"Paterson, J. Terrill","contributorId":206296,"corporation":false,"usgs":false,"family":"Paterson","given":"J.","email":"","middleInitial":"Terrill","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":740000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotella, Jay J.","contributorId":37271,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay","email":"","middleInitial":"J.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":740001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":740002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198476,"text":"70198476 - 2018 - Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","interactions":[],"lastModifiedDate":"2018-11-14T09:16:01","indexId":"70198476","displayToPublicDate":"2018-09-26T12:23:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","docAbstract":"The lateral export of carbon from coastal marshes via tidal exchange is a key component of the marsh carbon budget and coastal carbon cycles. However, the magnitude of this export has been difficult to accurately quantify due to complex tidal dynamics and seasonal cycling of carbon. In this study, we use in situ, high-frequency measurements of dissolved inorganic carbon (DIC) and water fluxes to estimate lateral DIC fluxes from a U.S. northeastern salt marsh. DIC was measured by a CHANnelized Optical Sensor (CHANOS) that provided an in situ concentration measurement at 15-min intervals, during periods in summer (July – August) and late fall (December). Seasonal changes in the marsh had strong effects on DIC concentrations, while tidally-driven water fluxes were the fundamental vehicle of marsh carbon export. Episodic events, such as groundwater discharge and mean sea water level changes, can impact DIC flux through altered DIC concentrations and water flow. Variability between individual tides within each season was comparable to mean variability between the two seasons. Estimated mean DIC fluxes based on a multiple linear regression (MLR) model of DIC concentrations and high-frequency water fluxes agreed reasonably well with those derived from CHANOS DIC measurements for both study periods, indicating that high-frequency, modeled DIC concentrations, coupled with continuous water flux measurements and a hydrodynamic model, provide a robust estimate of DIC flux. Additionally, an analysis of sampling strategies revealed that DIC fluxes calculated using conventional sampling frequencies (hourly to two-hourly) of a single tidal cycle are unlikely to capture a representative mean DIC flux compared to longer-term measurements across multiple tidal cycles with sampling frequency on the order of tens of minutes. This results from a disproportionately large amount of the net DIC flux occurring over a small number of tidal cycles, while most tides have a near-zero DIC export. Thus, high-frequency measurements (on the order of tens of minutes or better) over the time period of interest are necessary to accurately quantify tidal exports of carbon species from salt marshes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2018.08.005","usgsCitation":"Chu, S.N., Wang, Z., Gonneea Eagle, M., Kroeger, K.D., and Ganju, N., 2018, Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements: Marine Chemistry, v. 206, p. 7-18, https://doi.org/10.1016/j.marchem.2018.08.005.","productDescription":"12 p.","startPage":"7","endPage":"18","ipdsId":"IP-099810","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2018.08.005","text":"Publisher Index Page"},{"id":357773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538ab","contributors":{"authors":[{"text":"Chu, Sophie N.","contributorId":174603,"corporation":false,"usgs":false,"family":"Chu","given":"Sophie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":741590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Zhaohui Aleck","contributorId":174589,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui Aleck","affiliations":[{"id":13627,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":741591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":741592,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199711,"text":"70199711 - 2018 - A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","interactions":[],"lastModifiedDate":"2018-09-26T11:05:12","indexId":"70199711","displayToPublicDate":"2018-09-26T11:05:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","docAbstract":"Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2422","usgsCitation":"Cronin, J.P., and Schoolmaster, D., 2018, A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language: Ecosphere, v. 9, no. 9, p. 1-15, https://doi.org/10.1002/ecs2.2422.","productDescription":"e02422; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-066629","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2422","text":"Publisher Index Page"},{"id":357754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-17","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538b1","contributors":{"authors":[{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259473,"text":"70259473 - 2018 - McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","interactions":[],"lastModifiedDate":"2024-10-09T15:23:08.832201","indexId":"70259473","displayToPublicDate":"2018-09-26T10:16:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","docAbstract":"The McGee Till is an early Pleistocene glacial diamict as thick as 50 m, preserved over an area of 1.65 km2 on a relict low-relief Pliocene plateau that stands 900 m higher than mouths of its bounding canyons, on the rangefront of the Sierra Nevada. Although recognized 90 years ago as the oldest till in the Sierra, its age and relation to the next oldest Sierran till have remained uncertain, even controversial. This contribution seeks to clarify both. The McGee Till consists predominantly of grussy boulders and sandy-granular matrix derived largely from a distinctive Cretaceous granodiorite that walls McGee Creek canyon 4–8 km to the south. The till rests directly upon two different basaltic units that yield 40Ar/39Ar ages of 2.8 and 2.6 Ma and show little or no evidence of preglacial erosion. The basalts preserve a minimum of 165–255 m of relief on steep slopes that existed around the plateau margins at the time of their eruption. McGee Creek consists of two segments—a north-directed reach that confined the glacier that deposited the till and, now diverging at a right bend just upvalley from the till, a northeast-flowing reach that was incised later. The base of the McGee Till is at 3160 m elevation on the present-day rim of McGee Creek, 610 m above the bend. The base of the 130-ka Tahoe Till (MIS 6) is at 2550 m elevation directly downslope from the McGee Till and at 2300 m at the rangefront mouth of the canyon's northeast reach. The base of the 900–866 ka Sherwin Till (MIS 22) is at 2400 m at the nearby rangefront mouth of Rock Creek. As the canyons were cut to nearly modern depths before the Sherwin glaciation, the high-perched McGee Till is probably older than 2 Ma and possibly close in age to the 2.6 Ma basalt it overlies. Growth in rangefront relief since about 3.0–2.5 Ma owes to normal slip on the Hilton Creek and Round Valley Faults east of McGee Mountain as well as to the 767-ka collapse of Long Valley caldera to its north.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2018.08.008","usgsCitation":"Hildreth, W., Fierstein, J., and Calvert, A.T., 2018, McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment: Quaternary Science Reviews, v. 198, p. 242-265, https://doi.org/10.1016/j.quascirev.2018.08.008.","productDescription":"24 p.","startPage":"242","endPage":"265","ipdsId":"IP-097618","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2018.08.008","text":"Publisher Index Page"},{"id":462747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"McGill Till","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.34178096223278,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.90563417842898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith E. 0000-0001-8024-1426","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":329988,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915430,"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":915431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195563,"text":"fs20183008 - 2018 - Sediment Source Assessment Using Sediment Fingerprints","interactions":[],"lastModifiedDate":"2018-09-26T13:39:56","indexId":"fs20183008","displayToPublicDate":"2018-09-26T09:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3008","title":"Sediment Source Assessment Using Sediment Fingerprints","docAbstract":"Sediment is one of the most common causes of loss of stream-biologic integrity, whether in suspension in the water column, or as deposition on a stream or lake bottom. Fine-grained silts and clays are of particular concern because they can degrade habitat and often carry phosphorus and (or) other contaminants harmful to humans and aquatic life. Sediment-impaired water bodies, usually identified by fair to poor macroinvertebrate index scores, are placed on the 303(d) list of impaired waters, where a sediment Total Maximum Daily Load (TMDL) is developed under the Clean Water Act (https://www.epa.gov/tmdl). In order to effectively manage sediment, it is necessary to identify the sediment sources and locations of “hot spots” of erosion and deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183008","usgsCitation":"Gellis, A.C., Gorman Sanisaca, L.E., and Cashman, M.J., 2018, Sediment source assessment using sediment fingerprints: U.S. Geological Survey Fact Sheet 2018–3008, 2 p., https://doi.org/10.3133/fs20183008.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":206,"text":"Cooperative Water Program","active":false,"usgs":true}],"links":[{"id":351881,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3008/coverthb2.jpg"},{"id":351882,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3008/fs20183008.pdf","text":"Report","size":"577 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3008"}],"contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Geologists recognize lavas and ash deposits from about 60 past eruptions in the area around Mammoth Mountain and Devils Postpile, California. This raises the unanswerable question, “When will it erupt again?” An alternative, answerable, and informative question is, “How often has it erupted?”
In the Mammoth Lakes Sierra, geologists have mapped in great detail all the lavas and ash deposits produced by those 60 eruptions. They have dated almost all of them by laboratory methods, showing that eruptions have been repetitive and persistent, though not quite regular, over the last quarter-million years. For few volcanoes in the world is the long-term eruptive frequency so well calibrated as in the Mammoth Lakes Sierra.
Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The sensitivity of plant production to precipitation underlies the functioning of ecosystems. Studies that relate long-term mean annual precipitation and production across multiple sites(spatial relationship) or examine interannual linkages within a site (temporal relationship) can reveal biophysical controls over ecosystem function but have limited ability to infer responses to extreme changes in precipitation that may become more common under climate change. To overcome limitations of using a single approach, we integrated satellite- and ground-based estimates of production with a standardized, multi-site precipitation manipulation experiment across a grassland elevation gradient in the southwestern USA. The responsiveness of production to changes in precipitation followed the order: temporal (0.06–0.13 g m−2 mm−1) < spatial (0.21 g m−2 mm−1) < experimental relationship (0.25–0.42 g m−2 mm−1), suggesting that spatial and temporal relationships determined with satellite- and ground-based estimates cannot be extrapolated to determine the effect of extreme events. A strong production response to differences in mean annual precipitation across sites reinforces a regional control of water availability. Interannual sensitivity to precipitation was strongest at the low elevation grasslands, and the high elevation mixed conifer meadow had a large reduction in production in a drought year. Extreme experimental drought strongly reduced production in low elevation grasslands, but water addition had mixed effects. High elevation meadows were insensitive to both extreme drought and water addition. Our results highlight the importance of accounting for extreme climate regimes and site-level factors when scaling climate change effects up to regional and global scales.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-018-0296-3","usgsCitation":"Munson, S.M., Bunting, E., Bradford, J.B., Butterfield, B.J., and Gremer, J., 2018, Plant production responses to precipitation differ along an elevation gradient and are enhanced under extremes: Ecosystems, v. 22, no. 4, p. 699-708, https://doi.org/10.1007/s10021-018-0296-3.","productDescription":"10 p.","startPage":"699","endPage":"708","ipdsId":"IP-090212","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":357723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-11","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538b7","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":746196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunting, Erin L.","contributorId":208169,"corporation":false,"usgs":false,"family":"Bunting","given":"Erin L.","affiliations":[{"id":37758,"text":"Michigan State University, East Lansing, MI USA","active":true,"usgs":false}],"preferred":false,"id":746197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":746198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":746199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gremer, Jennifer R.","contributorId":181751,"corporation":false,"usgs":false,"family":"Gremer","given":"Jennifer R.","affiliations":[],"preferred":false,"id":746200,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199691,"text":"70199691 - 2018 - Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","interactions":[],"lastModifiedDate":"2018-11-14T09:17:48","indexId":"70199691","displayToPublicDate":"2018-09-25T16:29:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","title":"Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","docAbstract":"Aim
The aim of the study was to investigate postfire regeneration patterns of Araucaria‐Nothofagus forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio‐temporal scales.
Location
Araucanía region in the western Andean Range of south‐central Chile where fire occurred during the 2001–2002 season.
Methods
Sampling of prefire stand structure and postfire vegetation response was performed along a burn severity gradient a decade after the fire. We evaluated the relationship between field‐measured tree mortality and satellite‐derived burn severity using a generalized linear model. We fit zero‐inflated mixture models to regeneration data of each genus to assess the importance of abiotic variables, stand characteristics, and biotic interactions.
Results
The relative version of the delta Normalized Burn Ratio explained 85% of the variability in canopy mortality. Nearly 12,000 hectares burned; the majority at high severity (67%). Regeneration densities of both genera were lower at higher levels of burn severity and higher with greater total basal area (live, dead, and down trees). The relative effect size of burn severity on regeneration was nearly twice as large for Nothofagus, which suggests information legacies of Araucaria have cascading effects on postdisturbance material legacies.
Main conclusions
Araucaria‐Nothofagus mortality from wildfire can be readily mapped using satellite‐derived burn severity. Although environmental site characteristics and biotic interactions mediate regeneration, basal area, and burn severity are the main mechanisms controlling regeneration. Forest refugia and postfire regeneration are vulnerable to recurrent fire. Therefore, we expect future fire (either increased severity or frequency), driven by landscape level changes, as a potential mechanism that can reduce local resilience of these forests as initial postfire material legacies (e.g., refugia and regeneration) are removed from the landscape. Our findings highlight an approach to quantify important attributes of forest disturbance and refugia, and identify areas for monitoring postdisturbance regeneration as the forests throughout south‐central Chile and Argentina face a multitude of potential change agents.
Low‐temperature thermochronometry is widely used to measure the timing and rate of slip on normal faults. Rates are often derived from suites of footwall thermochronometer samples, but regression of age vs. structural depth fails to account for the trajectories of samples during fault slip. We demonstrate that in rotating fault blocks, regression of age‐depth data is susceptible to significant errors (>10%) in the identification of the initiation and rate of faulting. Advection of heat and topographic growth influence the thermal histories of exhumed particles, but for a range of geologically reasonable fault geometries and rates these effects produce Apatite (U‐Th)/He ages comparable to those derived from rotation through fixed isotherms. We apply the fixed‐isotherm model to published data from the Pine Forest Range and the East Range, Nevada, by incorporating field and thermochronologic constraints into a Markov chain Monte Carlo model. Modeled parameters for the Pine Forest Range are described by narrow ranges of geologically reasonable values. Compared to slip rates of 0.3‐0.8 km/Myr and an inititation of faulting ca. 11‐12 Ma derived from visual inspection, the model predicts an average slip rate of ~1.1 km/Myr and an onset of faulting ca. 9‐10 Ma. For the East Range fault block the model suggests faulting begain ~17 Ma with an extension rate of ~3 km/Myr and slowed to an extension rate of ~0.5 km/Myr at ~14 Ma. The absence of a preserved partial retention zone in the East Range sample set limits how well the model can predict fault block geometry.
","language":"English","publisher":"AGU","doi":"10.1029/2018TC005207","usgsCitation":"Johnstone, S., and Colgan, J.P., 2018, Interpretation of low‐temperature thermochronometer ages from tilted normal fault blocks: Tectonics, v. 37, no. 10, p. 3647-3667, https://doi.org/10.1029/2018TC005207.","productDescription":"21 p.","startPage":"3647","endPage":"3667","ipdsId":"IP-099026","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468370,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/an3fr/","text":"External Repository"},{"id":357721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538bb","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":746229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":746230,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199308,"text":"ofr20181149 - 2018 - 2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington","interactions":[],"lastModifiedDate":"2018-09-25T16:38:19","indexId":"ofr20181149","displayToPublicDate":"2018-09-25T09:22:44","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1149","title":"2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington","docAbstract":"On March 22, 2018, the Seattle Department of Construction and Inspections (SDCI) and the U.S. Geological Survey (USGS) convened a workshop of engineers and seismologists to provide guidance on incorporating sedimentary basin response into the design of tall buildings in Seattle. This workshop provided recommendations that build on those from a March 2013 workshop (Chang and others, 2014), primarily based on new results from 3-D simulations of magnitude (M) 9 Cascadia earthquakes (The M9 Project). Susan Chang, a geotechnical engineer with the Seattle Department of Construction and Inspections, organized and led the workshop; Art Frankel (USGS) assisted in constructing the agenda.
The workshop agenda and attendees are provided in the appendix. The attendees represented a wide range of expertise, including seismologists with expertise in ground motions and basin response, geotechnical engineers, and structural engineers. Their professional experience included working on local projects related to the design of long-period structures; peer reviewing ground motions for performance-based design of high-rises in Seattle; researching basin response in academic, government and industry settings; developing ground motion models; and representing local and national structural engineering organizations. In this report, we summarize the technical presentations, key discussion points, and recommendations from the workshop.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181149","usgsCitation":"Wirth, E.A., Chang, S.W., and Frankel, A.D., 2018, 2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington: U.S. Geological Survey Open-File Report 2018–1149, 19 p., https://doi.org/10.3133/ofr20181149.","productDescription":"iv, 19 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-099788","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":357679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1149/ofr20181149.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1149"},{"id":357678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1149/coverthb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5,\n 47.5\n ],\n [\n -122.2,\n 47.5\n ],\n [\n -122.2,\n 47.8\n ],\n [\n -122.5,\n 47.8\n ],\n [\n -122.5,\n 47.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center, Seattle Field Office
U.S. Geological Survey
University of Washington, Dept. of Earth and Space Sciences
Box 351310
Seattle, WA 98195
A series of 11 digital flood-inundation maps was developed for a 5.5-mile reach of the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut, by the U.S. Geological Survey (USGS) in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development. The coverage of the maps extends from downstream from the Ashaway River inflow at the State Border between Hopkinton and Westerly, Rhode Island, and North Stonington, Connecticut, to about 500 feet (ft) downstream from the U.S. Route 1/Broad Street bridge on the State border between Westerly, Rhode Island, and Stonington, Connecticut. A one-dimensional step-backwater hydraulic model created and calibrated for an ongoing (2018) Federal Emergency Management Agency Flood-Insurance Study for New London County, Connecticut and Washington County, Rhode Island was updated for this study. The hydraulic model reflects the removal of the White Rock dam during 2015–16, and was calibrated using the stage-discharge relation at the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and documented high-water marks from the March 30, 2010, flood, which had a peak flow slightly greater than the estimated 0.2-percent annual exceedance probability floodflow.
The hydraulic model was used to compute water-surface profiles for 11 flood stages at 1-ft intervals referenced to the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and ranging from 6.0 ft (3.32 ft, North American Vertical Datum of 1988), which is the National Weather Service Advanced Hydrologic Prediction Service flood category “action stage,” to 16.0 ft (13.32 ft, North American Vertical Datum of 1988), which is the maximum stage of the stage-discharge relation at the streamgage and exceeds the National Weather Service Advanced Hydrologic Prediction Service flood category “major flood stage” of 11.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 1.0-ft vertical accuracy to create flood-inundation maps. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to 11 selected flood stages at the streamgage. The flood-inundation maps depict only riverine flooding and do not depict any tidal backwater or coastal storm surge that could occur in the lower part of the river reach. The flood-inundation maps can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation. Near-real-time stages and discharges at the Pawcatuck River streamgage can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/. The National Weather Service Advanced Hydrologic Prediction Service provides flood forecast of stage for this site (WSTR1) at https://water.weather.gov/ahps/.
The availability of flood-inundation maps referenced to current and forecasted water levels at the USGS Pawcatuck River at Westerly, Rhode Island streamgage (01118500) can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during flood events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185112","collaboration":"Prepared in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development","usgsCitation":"Bent, G.C., and Lombard, P.J., 2018, Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5112, 16 p., https://doi.org/10.3133/sir20185112.","productDescription":"Report: vii, 16 p.; Application Site; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091691","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":357651,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":437742,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G0N0TN","text":"USGS data release","linkHelpText":"River Channel Survey Data, Redwood Creek, California, 1953-2013"},{"id":437741,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80","text":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":357652,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html ","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Inundation Mapper"},{"id":357649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5112/coverthb.jpg"},{"id":357650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5112/sir20185112.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5112"}],"country":"United States","state":"Connecticut, Rhode Island","city":"North Stonington, Stonington, Westerly","otherGeospatial":"Lower Pawcatuck River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.85,\n 41.3667\n ],\n [\n -71.7833,\n 41.3667\n ],\n [\n -71.7833,\n 41.425\n ],\n [\n -71.85,\n 41.425\n ],\n [\n -71.85,\n 41.3667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Groundwater quality in the North San Francisco Bay area Public-Supply and Shallow Aquifer Systems was investigated by the GAMA-PBP. The North San Francisco Bay Public-Supply Aquifer System study unit (NSF-PA) was sampled in 2004. The North San Francisco Bay Shallow Aquifer System study unit (NSF-SA) was sampled in 2012. The NSF-PA and NSF-SA largely coincide areally; however, they represent different parts of the aquifer system vertically. The NSF-PA examined deeper groundwater primarily used for public supply, whereas the NSF-SA examined relatively shallow groundwater primarily used for domestic supply. Both study units were divided into two study areas: (1) alluvium-filled groundwater basins called the Valleys and Plains study area and (2) volcanic, metamorphic, and ultramafic hard-rock highlands surrounding the Valleys and Plains called the Highlands study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183064","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Bennett, G.L., 2018, Comparing Public-Supply and Shallow Aquifer Groundwater Quality in the North San Francisco Bay Aquifers, California: U.S. Geological Survey Fact Sheet 2018-3064, 4 p., https://doi.org/10.3133/fs20183064.","productDescription":"4 p.","ipdsId":"IP-096675","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":357681,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3064/fs20183064.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3064"},{"id":357680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3064/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"North San Francisco Bay Aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.25,\n 38\n ],\n [\n -122,\n 38\n ],\n [\n -122,\n 39\n ],\n [\n -123.25,\n 39\n ],\n [\n -123.25,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Fanciful Fluorescence. Lurking Madness. Serene Expressions.
The titles of the images in this fifth edition of Earth As Art speak to the powerfully artistic qualities of Earth’s natural features when tinged with unnatural colors.
Art serves as a great partner in the communication of science, bringing emotion to the pursuit of understanding. The pieces in this collection look like abstract art but are actual satellite images.
Satellite imagery has long served the rational and disciplined approaches of science to better understand our Earth. But these images can also, with a bit of creativity, excite our imaginations with the beauty and art that surround us.
In this newest collection of Earth As Art, we continue to display the Earth as our eyes cannot see it—in creative combinations of visible and infrared light. Although beauty in art is often subjective, the science data provide objective views of the Earth’s changing land surface. However, we will let these images speak to you as art. Enjoy the latest additions to Earth As Art!
The images in the Earth As Art 5 collection can be downloaded for free from the Earth Resources Observation and Science (EROS) Center Image Gallery at
https://www.usgs.gov/centers/eros/science/earth-art-5.
Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD
This work used mercury injection capillary pressure (MICP) analyses of the Tuscaloosa Group in Mississippi, including the Tuscaloosa marine shale (TMS), to assess their efficacy and sealing capacity for geologic carbon dioxide (CO2) sequestration. Tuscaloosa Group porosity and permeability from MICP were evaluated to calculate CO2 column height retention. TMS and Lower Tuscaloosa shale samples have, respectively, Swanson permeability values less than 0.003 md and 0.00245 md; porosity from 3.86% to 9.86% and 1.34% to 7.96%; median pore throat sizes from 0.00342 to 0.0111 μm and 0.00311 to 0.017 μm; and pore radii from 0.0130 to 0.152 μm and 0.0132 to 0.149 μm. Mercury entry pressures for the TMS and Lower Tuscaloosa range from 4.9 to 57.1 MPa and 5.0 to 56.3 MPa, respectively. Calculated CO2 column heights that the TMS sample set can retain in the reservoir range from 23 to 255 m when the TMS is near 100% water saturation. Potential top seal leakage is more likely to be influenced by the numerous well penetrations through the confining system of the TMS rather than capillary failure. Results of this study demonstrate desirable sealing capacity of the TMS for geologic CO2 sequestration in reservoir sandstones of the Lower Tuscaloosa and could provide an analogue to other potential CO2 sequestration top seals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijggc.2018.09.006","usgsCitation":"Lohr, C., and Hackley, P.C., 2018, Using mercury injection pressure analyses to estimate sealing capacity of the Tuscaloosa marine shale in Mississippi, USA: Implications for carbon dioxide sequestration: International Journal of Greenhouse Gas Control, v. 78, p. 375-387, https://doi.org/10.1016/j.ijggc.2018.09.006.","productDescription":"13 p.","startPage":"375","endPage":"387","ipdsId":"IP-095213","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468371,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijggc.2018.09.006","text":"Publisher Index Page"},{"id":437743,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BC3XTK","text":"USGS data release","linkHelpText":"Mercury injection capillary pressure data in the U.S. Gulf Coast Tuscaloosa Group in Mississippi and Louisiana collected 2015 to 2017"},{"id":357684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 29.5\n ],\n [\n -89,\n 29.5\n ],\n [\n -89,\n 32.5\n ],\n [\n -92,\n 32.5\n ],\n [\n -92,\n 29.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f8ee4b0fc368eb538c5","contributors":{"authors":[{"text":"Lohr, Celeste D. 0000-0001-6287-9047 clohr@usgs.gov","orcid":"https://orcid.org/0000-0001-6287-9047","contributorId":3866,"corporation":false,"usgs":true,"family":"Lohr","given":"Celeste D.","email":"clohr@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":746118,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199631,"text":"70199631 - 2018 - Mangrove forests in a rapidly changing world: Global change impacts and conservation opportunities along the Gulf of Mexico coast","interactions":[],"lastModifiedDate":"2018-09-28T08:46:47","indexId":"70199631","displayToPublicDate":"2018-09-24T11:36:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Mangrove forests in a rapidly changing world: Global change impacts and conservation opportunities along the Gulf of Mexico coast","docAbstract":"Mangrove forests are highly-productive intertidal wetlands that support many ecosystem goods and services. In addition to providing fish and wildlife habitat, mangrove forests improve water quality, provide seafood, reduce coastal erosion, supply forest products, support coastal food webs, minimize flooding impacts, and support high rates of carbon sequestration. Despite their tremendous societal value, mangrove forests are threatened by many aspects of global change. Here, we examine the effects of global change on mangrove forests along the Gulf of Mexico coast, which is a valuable region for advancing understanding of global change impacts because the region spans multiple ecologically-relevant abiotic gradients that are representative of other mangrove transition zones across the world. We consider the historical and anticipated future responses of mangrove forests to the following aspects of global change: temperature change, precipitation change, accelerated sea-level rise, tropical cyclone intensification, elevated atmospheric carbon dioxide, eutrophication, invasive non-native species, and land use change. For each global change factor, we provide an initial global perspective but focus primarily on the three countries that border the Gulf of Mexico: United States, Mexico, and Cuba. The interactive effects of global change can have large ecological consequences, and we provide examples that highlight their importance. While some interactions between global change drivers can lead to mangrove mortality and loss, others can lead to mangrove expansion at the expense of other ecosystems. Finally, we discuss strategies for using restoration and conservation to maximize the adaptive capacity of mangrove forests to global change. To ensure that the ecosystem goods and services provided by mangrove forests continue to be available for future generations, there is a pressing need to better protect, manage, and restore mangrove forests as well as the adjacent ecosystems that provide opportunities for adaptation in response to global change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2018.09.006","usgsCitation":"Osland, M.J., Feher, L.C., Lopez-Portillo, J., Day, R.H., Suman, D.O., Guzman Menendez, J.M., and Rivera-Monroy, V.H., 2018, Mangrove forests in a rapidly changing world: Global change impacts and conservation opportunities along the Gulf of Mexico coast: Estuarine, Coastal and Shelf Science, v. 214, p. 120-140, https://doi.org/10.1016/j.ecss.2018.09.006.","productDescription":"21 p.","startPage":"120","endPage":"140","ipdsId":"IP-087566","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2018.09.006","text":"Publisher Index Page"},{"id":357669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"214","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f98e4b0fc368eb538cd","contributors":{"authors":[{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feher, Laura C. 0000-0002-5983-6190 lhundy@usgs.gov","orcid":"https://orcid.org/0000-0002-5983-6190","contributorId":176788,"corporation":false,"usgs":true,"family":"Feher","given":"Laura","email":"lhundy@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Portillo, Jorge","contributorId":208129,"corporation":false,"usgs":false,"family":"Lopez-Portillo","given":"Jorge","email":"","affiliations":[{"id":37732,"text":"Instituto de Ecología A.C., Red de Ecología Funcional, Xalapa, Veracruz, México","active":true,"usgs":false}],"preferred":false,"id":746029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suman, Daniel O.","contributorId":208131,"corporation":false,"usgs":false,"family":"Suman","given":"Daniel","email":"","middleInitial":"O.","affiliations":[{"id":37733,"text":"University of Miami, Department of Marine Ecosystems and Society, Miami, FL, USA","active":true,"usgs":false}],"preferred":false,"id":746031,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guzman Menendez, Jose Manuel","contributorId":208132,"corporation":false,"usgs":false,"family":"Guzman Menendez","given":"Jose","email":"","middleInitial":"Manuel","affiliations":[{"id":37734,"text":"Instituto de Ecología y Sistematica, Agencia de Medio Ambiente, Ministerio de Ciencia Tecnología y Medio Ambiente, La Habana, Cuba","active":true,"usgs":false}],"preferred":false,"id":746032,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":746033,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199627,"text":"70199627 - 2018 - Serum proteins in healthy and diseased Florida manatees (Trichechus manatus latirostris)","interactions":[],"lastModifiedDate":"2018-10-23T16:47:27","indexId":"70199627","displayToPublicDate":"2018-09-24T11:31:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5756,"text":"Comparative Clinical Pathology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Serum proteins in healthy and diseased Florida manatees (Trichechus manatus latirostris)","title":"Serum proteins in healthy and diseased Florida manatees (Trichechus manatus latirostris)","docAbstract":"A major goal of this study was to determine whether serum protein fractions of healthy Florida manatees differ with age, sex, or living environments (wild versus housed). A second goal was to determine which serum protein fractions vary in diseased versus healthy manatees. Serum protein fractions were determined using agarose gel electrophoresis. Healthy adults had slightly higher total serum protein and total globulin concentrations than younger animals. This largely resulted from an increase in gamma globulins with age. Total serum protein, albumin, alpha-1 globulin, beta globulin, and total globulin concentrations were slightly higher in housed manatees compared to wild manatees, but there was no significant difference in the albumin/globulin (A/G) ratio, suggesting a difference in hydration between these groups. No significant differences were attributable to sex or pregnancy. Serum albumin concentrations and A/G ratios were significantly lower for manatees with boat trauma, entanglements, emaciation, or cold stress compared to healthy manatees. Variable increases were seen in alpha-1globulins, alpha-2 globulins, beta globulins, and gamma globulins. These globulin fractions contain positive acute-phase proteins and immunoglobulins, and their increases may reflect acute or chronic active inflammation. Changes in serum protein fractions were not consistent enough to justify the use of serum protein electrophoresis as a routine diagnostic test for manatees. However, serum (or plasma) protein electrophoresis is required when accurate values for albumin and globulins are needed in manatees and in determining which protein fractions may account for a hyperproteinemia or hypoproteinemia reported in a clinical chemistry panel.
","language":"English","publisher":"Springer","doi":"10.1007/s00580-018-2797-z","usgsCitation":"Harvey, J.W., Harr, K.E., Murphy, D., Walsh, M.T., deWit, M., Deutsch, C.J., and Bonde, R.K., 2018, Serum proteins in healthy and diseased Florida manatees (Trichechus manatus latirostris): Comparative Clinical Pathology, v. 27, no. 6, p. 1707-1716, https://doi.org/10.1007/s00580-018-2797-z.","productDescription":"10 p.","startPage":"1707","endPage":"1716","ipdsId":"IP-087359","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":357668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-03","publicationStatus":"PW","scienceBaseUri":"5bc02f98e4b0fc368eb538cf","contributors":{"authors":[{"text":"Harvey, John W.","contributorId":208124,"corporation":false,"usgs":false,"family":"Harvey","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37728,"text":"University of Florida, College Veterinary Medicine","active":true,"usgs":false}],"preferred":false,"id":746009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harr, Kendall E.","contributorId":201901,"corporation":false,"usgs":false,"family":"Harr","given":"Kendall","email":"","middleInitial":"E.","affiliations":[{"id":36285,"text":"Urika Pathology, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":746010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, David","contributorId":208125,"corporation":false,"usgs":false,"family":"Murphy","given":"David","email":"","affiliations":[{"id":37729,"text":"Lowry Park Zoo","active":true,"usgs":false}],"preferred":false,"id":746011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Michael T.","contributorId":177177,"corporation":false,"usgs":false,"family":"Walsh","given":"Michael","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":746012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"deWit, Martina","contributorId":208126,"corporation":false,"usgs":false,"family":"deWit","given":"Martina","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":746013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Deutsch, Charles J.","contributorId":190249,"corporation":false,"usgs":false,"family":"Deutsch","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":746014,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746008,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}