The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement.
","language":"English","publisher":"CRC Press","isbn":"9781466582149","usgsCitation":"Hooten, M., Johnson, D., McClintock, B.T., and Morales, J.M., 2017, Animal movement: Statistical models for telemetry data, 306 p.","productDescription":"306 p.","ipdsId":"IP-075857","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350689,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Animal-Movement-Statistical-Models-for-Telemetry-Data/Hooten-Johnson-McClintock-Morales/p/book/9781466582149"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6c4c94e4b06e28e9cabafa","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":725947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McClintock, Brett T. 0000-0001-6154-4376","orcid":"https://orcid.org/0000-0001-6154-4376","contributorId":83785,"corporation":false,"usgs":true,"family":"McClintock","given":"Brett","email":"","middleInitial":"T.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":725948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":725949,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179745,"text":"70179745 - 2017 - Signals of impending change","interactions":[],"lastModifiedDate":"2017-01-17T10:20:53","indexId":"70179745","displayToPublicDate":"2017-01-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5263,"text":"Nature Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Signals of impending change","docAbstract":"Society has an increasing awareness that there are finite limits to what we can expect the planet to absorb and still provide goods and services at current rates1. Both historical reconstructions and contemporary events continue to remind us that ecological regime changes are often abrupt rather than gradual. This reality motivates researchers who seek to discover leading indicators for impending ecosystem change. Berdugo et al.2 report an important advance in our ability to anticipate the conversion of arid lands from self-organized, self-maintaining and productive ecosystems, to a state characterized by disorganization and low functionality. Such conversions have important implications for our understanding of ‘desertification’ — which is a shift from arid to desert-like conditions.
Theoretical studies have suggested that patterns in the patchiness of vegetation might indicate how close a system is to making an abrupt change to desert-like conditions3,4,5. Empirical studies, however, have tended to show instead that simply the total cover of vegetation, rather than its arrangement, often foretells the state of the system4,5,6,7,8,9. Berdugo et al.2 combine these competing ideas into one integrated perspective. They show how major environmental drivers, such as aridity, influence both vegetation cover and patchiness, as well as where self-organizing, stabilizing forces in the vegetation are likely to be found.
Endangered whooping cranes (Grus americana) of the Aransas-Wood Buffalo population migrate through the Great Plains twice each year. Although there is much interest in conservation and management for this species, information regarding characteristics of nocturnal roost sites used during migration has been limited and based largely on incidental observations. Using high-quality location data collected concurrently, we directed a companion field study designed to characterize sites used as roost or day-use sites to augment knowledge and assist the Platte River Recovery Implementation Program in identifying migration habitat for restoration, conservation, and management actions along the Platte River in central Nebraska. We collected data at 504 roost sites and 83 day-use sites used by marked whooping cranes in Texas, Oklahoma, Kansas, Nebraska, South Dakota, North Dakota, Minnesota, and Montana. Roost sites were located in emergent wetlands (50 percent), lacustrine wetlands (25 percent), rivers (20 percent), and dryland sites (5 percent). Most day-use sites were characterized as dryland sites (54 percent), with the balance in wetlands (45 percent) and rivers (1 percent). Habitat criteria thresholds initially derived by the Platte River Recovery Implementation Program to represent where 90 percent of whooping cranes used along the Platte River were different from those we measured over a larger section of the migration corridor. For most of the metrics, the Platte River Recovery Implementation Program’s initial habitat criteria thresholds would be considered more conservative than critical values estimated from our data; thus, whooping cranes were seemingly able to tolerate a wider range of these metrics than initially suspected. One exception was the metric distance to nearest disturbance feature, where our results suggest that whooping cranes may be less tolerant to nearby disturbances in a larger part of the migration corridor compared to the Platte River. We also determined correlations among some metrics and that using the criteria collectively lead to less than 50 percent of sites we measured being considered whooping crane habitat by the Platte River Recovery Implementation Program. A better understanding of how metrics function collectively may be useful for future efforts in defining habitat for migrating whooping cranes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161209","collaboration":"Prepared in cooperation with the Platte River Recovery Implementation Program and Crane Trust","usgsCitation":"Pearse, A.T., Harner, M.J., Baasch, D.M., Wright, G.D., Caven, A.J., and Metzger, K.L., 2017, Evaluation of nocturnal roost and diurnal sites used by whooping cranes in the Great Plains, United States: U.S. Geological Survey Open-File Report 2016–1209, 29 p., https://doi.org/10.3133/ofr20161209.","productDescription":"v, 29 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-078087","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":332999,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1209/ofr20161209.pdf","text":"Report","size":"6.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1209"},{"id":332998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1209/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67773437499999,\n 28.9600886880068\n ],\n [\n -104.67773437499999,\n 49.03786794532644\n ],\n [\n -94.7021484375,\n 49.03786794532644\n ],\n [\n -94.7021484375,\n 28.9600886880068\n ],\n [\n -104.67773437499999,\n 28.9600886880068\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12732","usgsCitation":"Pepin, K., Kay, S.L., Golas, B., Shriner, S.A., Gilbert, A.T., Miller, R.S., Graham, A.L., Riley, S., Cross, P.C., Samuel, M.D., Hooten, M., Hoeting, J.A., Lloyd-Smith, J., Webb, C.T., and Buhnerkempe, M.G., 2017, Inferring infection hazard in wildlife populations by linking data across individual and population scales: Ecology Letters, v. 20, no. 3, p. 275-292, https://doi.org/10.1111/ele.12732.","productDescription":"18 p.","startPage":"275","endPage":"292","ipdsId":"IP-079399","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470135,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.12732","text":"Publisher Index Page"},{"id":343590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-01-16","publicationStatus":"PW","scienceBaseUri":"5965b234e4b0d1f9f05b37e1","contributors":{"authors":[{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":704280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golas, Ben D.","contributorId":194478,"corporation":false,"usgs":false,"family":"Golas","given":"Ben D.","affiliations":[],"preferred":false,"id":704282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriner, Susan A.","contributorId":168690,"corporation":false,"usgs":false,"family":"Shriner","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":13407,"text":"Colorado State Univ.","active":true,"usgs":false}],"preferred":false,"id":704283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gilbert, Amy T.","contributorId":15093,"corporation":false,"usgs":true,"family":"Gilbert","given":"Amy","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":704284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":704285,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graham, Andrea L.","contributorId":194479,"corporation":false,"usgs":false,"family":"Graham","given":"Andrea","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704286,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Riley, Steven","contributorId":194480,"corporation":false,"usgs":false,"family":"Riley","given":"Steven","email":"","affiliations":[],"preferred":false,"id":704287,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":704288,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":704289,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":704290,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hoeting, Jennifer A.","contributorId":168403,"corporation":false,"usgs":false,"family":"Hoeting","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":704291,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lloyd-Smith, James O.","contributorId":31354,"corporation":false,"usgs":true,"family":"Lloyd-Smith","given":"James O.","affiliations":[],"preferred":false,"id":704292,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Webb, Colleen T.","contributorId":52471,"corporation":false,"usgs":true,"family":"Webb","given":"Colleen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":704293,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Buhnerkempe, Michael G.","contributorId":194481,"corporation":false,"usgs":false,"family":"Buhnerkempe","given":"Michael","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":704294,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70250956,"text":"70250956 - 2017 - Thermodynamic properties in the Fe(II)-Fe(III)-As(V)-HClO4–H2O and Fe(II)-Fe(III)-As(V)-HCl–H2O systems from 5 to 90 °C","interactions":[],"lastModifiedDate":"2024-01-16T12:17:08.51847","indexId":"70250956","displayToPublicDate":"2017-01-16T06:13:54","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Thermodynamic properties in the Fe(II)-Fe(III)-As(V)-HClO4–H2O and Fe(II)-Fe(III)-As(V)-HCl–H2O systems from 5 to 90 °C","docAbstract":"Fe-As mineral solubility and associated aqueous species have been intensively studied because of the environmental need to immobilize arsenic. The thermodynamic data for aqueous iron-arsenic species are inadequately characterized, however. The Gibbs free energy, enthalpy, entropy, and heat capacity and activity coefficients were refined in the Fe(II)-Fe(III)-As(V)-HClO4-H2O and Fe(II)-Fe(III)-As(V)-HCl-H2O systems using redox potential measurements from 5 to 90 °C. The association constants for FeHAsO4+ and FeH2AsO42 + at 25 °C were 1010.28 and 104.02 and the corresponding association reaction enthalpies and heat capacities were 25.74 and 8.73 kJ mol− 1 and 843.1 and − 529.6 J K −1mol− 1, respectively. Activity coefficients for H+, ClO4−, Fe2 +, Fe3 +, HAsO42 −, and H2AsO4− at 25 °C in the form of the Hückel equation were derived for ionic strengths up to 1 mol− 1 kg− 1. Newly derived activity coefficients and thermodynamic data were incorporated into PHREEQCI to calculate the Eh of laboratory solutions. The differences between calculated and measured Eh were all within 10 mV and relative differences were all lower than 1.5%.
The introduction of aquatic invasive species to non-native habitats can cause negative ecological effects and also billions of dollars in economic damage to governments and private industries. Once aquatic invasive species are introduced, eradication may be difficult without adversely affecting native species and habitats, urging resource managers to find preventative methods to protect non-invaded areas. The use of ozone (O3) as a non-physical barrier has shown promise as it is lethal to a wide range of aquatic taxa, requires a short contact time, and is relatively environmentally safe in aquatic systems when compared to other chemicals. However, before O3 can be considered as an approach to prevent the spread of aquatic invasive species, its effects on non-target organisms and already established aquatic invasive species must be fully evaluated. A review of the current literature was conducted to summarize data regarding the effects of O3 on aquatic taxa including fish, macroinvertebrates, zooplankton, phytoplankton, microbes, and pathogens. In addition, we assessed the practicality of ozone applications to control the movement of aquatic invasive species, and identified data gaps concerning the use of O3 as a non-physical barrier in field applications.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/mbi.2017.8.1.02","usgsCitation":"Buley, R., Hasler, C.T., Tix, J., Suski, C., and Hubert, T.D., 2017, Can ozone be used to control the spread of freshwater Aquatic Invasive Species?: Management of Biological Invasions, v. 8, no. 1, p. 13-24, https://doi.org/10.3391/mbi.2017.8.1.02.","productDescription":"12 p.","startPage":"13","endPage":"24","ipdsId":"IP-076249","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2017.8.1.02","text":"Publisher Index Page"},{"id":338813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699c9f","contributors":{"authors":[{"text":"Buley, Riley P.","contributorId":190149,"corporation":false,"usgs":false,"family":"Buley","given":"Riley P.","affiliations":[],"preferred":false,"id":687408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hasler, Caleb T.","contributorId":190150,"corporation":false,"usgs":false,"family":"Hasler","given":"Caleb","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":687409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tix, John A.","contributorId":126766,"corporation":false,"usgs":false,"family":"Tix","given":"John A.","affiliations":[{"id":6602,"text":"Great Lakes Science Center, Hammond Bay Biological Station","active":true,"usgs":false}],"preferred":false,"id":687410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suski, C. D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":687411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687412,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179654,"text":"sir20175001 - 2017 - Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in North Georgia","interactions":[],"lastModifiedDate":"2017-01-13T14:05:48","indexId":"sir20175001","displayToPublicDate":"2017-01-13T13:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5001","title":"Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in North Georgia","docAbstract":"The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division, developed regional regression equations for estimating selected low-flow frequency and mean annual flow statistics for ungaged streams in north Georgia that are not substantially affected by regulation, diversions, or urbanization. Selected low-flow frequency statistics and basin characteristics for 56 streamgage locations within north Georgia and 75 miles beyond the State’s borders in Alabama, Tennessee, North Carolina, and South Carolina were combined to form the final dataset used in the regional regression analysis. Because some of the streamgages in the study recorded zero flow, the final regression equations were developed using weighted left-censored regression analysis to analyze the flow data in an unbiased manner, with weights based on the number of years of record. The set of equations includes the annual minimum 1- and 7-day average streamflow with the 10-year recurrence interval (referred to as 1Q10 and 7Q10), monthly 7Q10, and mean annual flow. The final regional regression equations are functions of drainage area, mean annual precipitation, and relief ratio for the selected low-flow frequency statistics and drainage area and mean annual precipitation for mean annual flow. The average standard error of estimate was 13.7 percent for the mean annual flow regression equation and ranged from 26.1 to 91.6 percent for the selected low-flow frequency equations.
The equations, which are based on data from streams with little to no flow alterations, can be used to provide estimates of the natural flows for selected ungaged stream locations in the area of Georgia north of the Fall Line. The regression equations are not to be used to estimate flows for streams that have been altered by the effects of major dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, or wastewater discharges. The regression equations should be used only for ungaged sites with drainage areas between 1.67 and 576 square miles, mean annual precipitation between 47.6 and 81.6 inches, and relief ratios between 0.146 and 0.607; these are the ranges of the explanatory variables used to develop the equations. An attempt was made to develop regional regression equations for the area of Georgia south of the Fall Line by using the same approach used during this study for north Georgia; however, the equations resulted with high average standard errors of estimates and poorly predicted flows below 0.5 cubic foot per second, which may be attributed to the karst topography common in that area.
The final regression equations developed from this study are planned to be incorporated into the U.S. Geological Survey StreamStats program. StreamStats is a Web-based geographic information system that provides users with access to an assortment of analytical tools useful for water-resources planning and management, and for engineering design applications, such as the design of bridges. The StreamStats program provides streamflow statistics and basin characteristics for U.S. Geological Survey streamgage locations and ungaged sites of interest. StreamStats also can compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in Georgia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175001","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Gotvald, A.J., 2017, Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in North Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5001, 25 p., https://doi.org/10.3133/sir20175001. ","productDescription":"Report: vi, 25 p.; 3 Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077003","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":333138,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5001/sir20175001.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5001"},{"id":333139,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5001/sir20175001_tables1-2-5.xlsx","text":"Tables 1, 2, and 5 - ","size":"74.8 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Table 1. Description of streamgages evaluated for use in the regional regression analysis for north GeorgiaDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Recent reports suggest that host-seeking nymphs in southern populations of Ixodes scapularis remain below the leaf litter surface, while northern nymphs seek hosts on leaves and twigs above the litter surface. This behavioral difference potentially results in decreased tick contact with humans in the south, and fewer cases of Lyme disease. We studied whether north-south differences in tick survival patterns might contribute to this phenomenon. Four month old larvae resulting from a cross between Wisconsin males and South Carolina females died faster under southern than under northern conditions in the lab, as has previously been reported for ticks from both northern and southern populations. However, newly-emerged larvae from Rhode Island parents did not differ consistently in mortality under northern and southern conditions, possibly because of their younger age. Survival is lower, and so the north-south survival difference might be greater in older ticks. Larval survival was positively related to larval size (as measured by scutal area), while survival was positively related to larval fat content in some, but not all, trials. The difference in larval survival under northern vs. southern conditions might simply result from faster metabolism under warmer southern conditions leading to shorter life spans. However, ticks consistently died faster under southern than under northern conditions in the laboratory when relative humidity was low (75%), but not under moderate (85%) or high (95%) RH. Therefore, mortality due to desiccation stress is greater under southern than under northern conditions. We hypothesize that mortality resulting from the greater desiccation stress under southern conditions acts as a selective pressure resulting in the evolution of host-seeking behavior in which immatures remain below the leaf litter surface in southern I. scapularis populations, so as to avoid the desiccating conditions at the surface. If this hypothesis is correct, it has implications for the effect of climate change on the future distribution of Lyme disease.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0168723","usgsCitation":"Ginsberg, H., Albert, M., Acevedo, L., Dyer, M.C., Arsnoe, I.M., Tsao, J.I., Mather, T.N., and LeBrun, R.A., 2017, Environmental factors affecting survival of immature Ixodes scapularis and implications for geographical distribution of lyme disease: The climate/behavior hypothesis: PLoS ONE, v. 12, no. 1, e0168723; 17 p., https://doi.org/10.1371/journal.pone.0168723.","productDescription":"e0168723; 17 p.","ipdsId":"IP-079492","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0168723","text":"Publisher Index Page"},{"id":333208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"5879f5a8e4b0847d353f44b8","contributors":{"authors":[{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":658444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albert, Marisa","contributorId":178307,"corporation":false,"usgs":false,"family":"Albert","given":"Marisa","email":"","affiliations":[],"preferred":false,"id":658445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Acevedo, Lixis","contributorId":178308,"corporation":false,"usgs":false,"family":"Acevedo","given":"Lixis","email":"","affiliations":[],"preferred":false,"id":658446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dyer, Megan C.","contributorId":178309,"corporation":false,"usgs":false,"family":"Dyer","given":"Megan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":658447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arsnoe, Isis M.","contributorId":140902,"corporation":false,"usgs":false,"family":"Arsnoe","given":"Isis","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":658448,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":658449,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mather, Thomas N.","contributorId":178310,"corporation":false,"usgs":false,"family":"Mather","given":"Thomas","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":658450,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LeBrun, Roger A.","contributorId":70907,"corporation":false,"usgs":false,"family":"LeBrun","given":"Roger","email":"","middleInitial":"A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":658451,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70179440,"text":"ds1032 - 2017 - Coastal bathymetry data collected in 2013 from the Chandeleur Islands, Louisiana","interactions":[],"lastModifiedDate":"2017-01-12T08:50:59","indexId":"ds1032","displayToPublicDate":"2017-01-12T09:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1032","title":"Coastal bathymetry data collected in 2013 from the Chandeleur Islands, Louisiana","docAbstract":"As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys around the northern Chandeleur Islands, Louisiana, in July and August of 2013. The objective of the study is to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1‒5 years). Collecting geophysical data will allow us to identify relationships between the geologic history of the island and its present day morphology and sediment distribution. This mapping effort was the third in a series of three planned surveys in this area. High resolution geophysical data collected in each of three consecutive years along this rapidly changing barrier island system will provide a unique time-series dataset that will significantly further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over short time scales (1‒5 years).
This data series includes the geophysical data that were collected during two cruises (USGS Field Activity Numbers (FAN) 13BIM02, 13BIM03, and 13BIM04, in July 2013; and FANs 13BIM07 and 13BIM08 in August 2013) aboard the R/V Sallenger, the R/V Jabba Jaw, and the R/V Shark along the northern portion of the Chandeleur Islands, Breton National Wildlife Refuge, Louisiana. Primary data were acquired with the following equipment: (1) a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz [kHz]), (2) an EdgeTech 424 (4‒24 kHz) chirp sub-bottom profiling system, and (3) two Odom Hydrographic Systems, Incorporated, Echotrach CV100 single beam echosounders.
This data series report serves as an archive of processed interferometric swath and single-beam bathymetry data. Geographic information system data products include an interpolated digital elevation model, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1032","usgsCitation":"DeWitt, N.T., Miselis, J.L., Fredericks, J.J., Bernier, J.C., Reynolds, B.J., Kelso, K.W., Thompson, D.M., Flocks, J.G., and Wiese, D.S., 2017, Coastal bathymetry data collected in 2013 from the Chandeleur Islands, Louisiana: U.S. Geological Survey Data Series Report 1032, https://doi.org/10.3133/ds1032.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078418","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":332772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1032/coverthb.jpg"},{"id":332773,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1032/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1032"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.933333,\n 30.116667\n ],\n [\n -88.933333,\n 29.85\n ],\n [\n -88.733333,\n 29.85\n ],\n [\n -88.733333,\n 30.116667\n ],\n [\n -88.933333,\n 30.116667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Environmental release of veterinary pharmaceuticals has been of regulatory concern for more than a decade. Monensin is a feed additive antibiotic that is prevalent throughout the dairy industry and is excreted in dairy waste. This study investigates the potential of dairy waste management practices to alter the amount of monensin available for release into the environment. Analysis of wastewater and groundwater from two dairy farms in California consistently concluded that monensin is most present in lagoon water and groundwater downgradient of lagoons. Since the lagoons represent a direct source of monensin to groundwater, the effect of waste management, by mechanical screen separation and lagoon aeration, on aqueous monensin concentration was investigated through construction of lagoon microcosms. The results indicate that monensin attenuation is not improved by increased solid-liquid separation prior to storage in lagoons, as monensin is rapidly desorbed after dilution with water. Monensin is also shown to be easily degraded in lagoon microcosms receiving aeration, but is relatively stable and available for leaching under typical anaerobic lagoon conditions.
","language":"English","publisher":"Academic Press","publisherLocation":"New York, NY","doi":"10.1016/j.jenvman.2016.12.024","usgsCitation":"Hafner, S.C., Watanabe, N., Harter, T., Bergamaschi, B.A., and Parikh, S.J., 2017, Effects of solid-liquid separation and storage on monensin attenuation in dairy waste management systems: Journal of Environmental Management, v. 190, p. 28-34, https://doi.org/10.1016/j.jenvman.2016.12.024.","productDescription":"7 p.","startPage":"28","endPage":"34","ipdsId":"IP-082151","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":461791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2016.12.024","text":"Publisher Index Page"},{"id":333078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"190","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5878a489e4b04df303d957fa","contributors":{"authors":[{"text":"Hafner, Sarah C.","contributorId":178243,"corporation":false,"usgs":false,"family":"Hafner","given":"Sarah","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":658289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watanabe, Naoko","contributorId":178244,"corporation":false,"usgs":false,"family":"Watanabe","given":"Naoko","email":"","affiliations":[],"preferred":false,"id":658290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harter, Thomas","contributorId":178245,"corporation":false,"usgs":false,"family":"Harter","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":658291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parikh, Sanjai J.","contributorId":178246,"corporation":false,"usgs":false,"family":"Parikh","given":"Sanjai","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":658292,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179695,"text":"70179695 - 2017 - Geochemical characteristics of igneous rocks associated with epithermal mineral deposits—A review","interactions":[],"lastModifiedDate":"2017-01-12T11:55:34","indexId":"70179695","displayToPublicDate":"2017-01-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical characteristics of igneous rocks associated with epithermal mineral deposits—A review","docAbstract":"Newly synthesized data indicate that the geochemistry of igneous rocks associated with epithermal mineral deposits varies extensively and continuously from subalkaline basaltic to rhyolitic compositions. Trace element and isotopic data for these rocks are consistent with subduction-related magmatism and suggest that the primary source magmas were generated by partial melting of the mantle-wedge above subducting oceanic slabs. Broad geochemical and petrographic diversity of individual igneous rock units associated with epithermal deposits indicate that the associated magmas evolved by open-system processes. Following migration to shallow crustal reservoirs, these magmas evolved by assimilation, recharge, and partial homogenization; these processes contribute to arc magmatism worldwide.
Although epithermal deposits with the largest Au and Ag production are associated with felsic to intermediate composition igneous rocks, demonstrable relationships between magmas having any particular composition and epithermal deposit genesis are completely absent because the composition of igneous rock units associated with epithermal deposits ranges from basalt to rhyolite. Consequently, igneous rock compositions do not constitute effective exploration criteria with respect to identification of terranes prospective for epithermal deposit formation. However, the close spatial and temporal association of igneous rocks and epithermal deposits does suggest a mutual genetic relationship. Igneous systems likely contribute heat and some of the fluids and metals involved in epithermal deposit formation. Accordingly, deposit formation requires optimization of source metal contents, appropriate fluid compositions and characteristics, structural features conducive to hydrothermal fluid flow and confinement, and receptive host rocks, but not magmas with special compositional characteristics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2016.08.023","usgsCitation":"du Bray, E.A., 2017, Geochemical characteristics of igneous rocks associated with epithermal mineral deposits—A review: Ore Geology Reviews, v. 80, p. 767-783, https://doi.org/10.1016/j.oregeorev.2016.08.023.","productDescription":"17 p.","startPage":"767","endPage":"783","ipdsId":"IP-066206","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":333082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5878a489e4b04df303d957f8","contributors":{"authors":[{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":658321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179847,"text":"70179847 - 2017 - Life history plasticity does not confer resilience to environmental change in the mole salamander (Ambystoma talpoideum)","interactions":[],"lastModifiedDate":"2017-03-14T09:22:18","indexId":"70179847","displayToPublicDate":"2017-01-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Life history plasticity does not confer resilience to environmental change in the mole salamander (Ambystoma talpoideum)","docAbstract":"Plasticity in life history strategies can be advantageous for species that occupy spatially or temporally variable environments. We examined how phenotypic plasticity influences responses of the mole salamander, Ambystoma talpoideum, to disturbance events at the St. Marks National Wildlife Refuge (SMNWR), FL, USA from 2009 to 2014. We observed periods of extensive drought early in the study, in contrast to high rainfall and expansive flooding events in later years. Flooding facilitated colonization of predatory fishes to isolated wetlands across the refuge. We employed multistate occupancy models to determine how this natural experiment influenced the occurrence of aquatic larvae and paedomorphic adults and what implications this may have for the population. We found that, in terms of occurrence, responses to environmental variation differed between larvae and paedomorphs, but plasticity (i.e. the ability to metamorphose rather than remain in aquatic environment) was not sufficient to buffer populations from declining as a result of environmental perturbations. Drought and fish presence negatively influenced occurrence dynamics of larval and paedomorphic mole salamanders and, consequently, contributed to observed short-term declines of this species. Overall occurrence of larval salamanders decreased from 0.611 in 2009 to 0.075 in 2014 and paedomorph occurrence decreased from 0.311 in 2009 to 0.121 in 2014. Although variation in selection pressures has likely maintained this polyphenism previously, our results suggest that continued changes in environmental variability and the persistence of fish in isolated wetlands could lead to a loss of paedomorphosis in the SMNWR population and, ultimately, impact regional persistence in the future.","language":"English","publisher":"Springer","doi":"10.1007/s00442-017-3810-y","collaboration":"Courtney L. Davis; David A.W. Miller; Susan C. Walls; William J. Barichivich; Jeffrey Riley; Mary E. Brown","usgsCitation":"Courtney L. Davis, David A.W. Miller, Walls, S.C., Barichivich, W.J., Riley, J.W., and Brown, M.E., 2017, Life history plasticity does not confer resilience to environmental change in the mole salamander (Ambystoma talpoideum): Oecologia, v. 183, p. 739-749, https://doi.org/10.1007/s00442-017-3810-y.","productDescription":"11 p. ","startPage":"739","endPage":"749","ipdsId":"IP-074456","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":333425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-12","publicationStatus":"PW","scienceBaseUri":"5881ded3e4b01192927d9f77","contributors":{"authors":[{"text":"Courtney L. Davis","contributorId":178448,"corporation":false,"usgs":false,"family":"Courtney L. Davis","affiliations":[],"preferred":false,"id":658929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David A.W. Miller","contributorId":178449,"corporation":false,"usgs":false,"family":"David A.W. Miller","affiliations":[],"preferred":false,"id":658930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":658928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barichivich, William J. 0000-0003-1103-6861 wbarichivich@usgs.gov","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":3697,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","email":"wbarichivich@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Mary E. 0000-0002-5580-137X mbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":5688,"corporation":false,"usgs":true,"family":"Brown","given":"Mary","email":"mbrown@usgs.gov","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":658933,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176170,"text":"fs20163066 - 2017 - Water resources of Calcasieu Parish, Louisiana","interactions":[],"lastModifiedDate":"2017-01-13T10:31:37","indexId":"fs20163066","displayToPublicDate":"2017-01-12T00:00:00","publicationYear":"2017","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":"2016-3066","title":"Water resources of Calcasieu Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Calcasieu Parish, Louisiana, is critical for proper water-resource management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://dx.doi.org/10.5066/F7P55KJN) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163066","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2017, Water resources of Calcasieu Parish, Louisiana: U.S. Geological Survey Fact Sheet 2016–3066, 6 p., https://dx.doi.org/10.3133/fs20163066.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-073096","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":333095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3066/fs20163066.pdf","text":"Fact Sheet","size":"1.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"2016–3066"},{"id":333094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3066/coverthb.jpg"}],"country":"United 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
The efficacy of various sampling gears for age-0 Mountain Whitefish Prosopium williamsoni is largely unknown, which makes it difficult to investigate recruitment and early life history dynamics for the species. We compared four gears: seine, backpack electrofisher, minnow trap, and lighted minnow trap. Gears were tested in backwaters, large channels, and small channels in the Madison River, Montana. No age-0 Mountain Whitefish were captured in minnow traps or lighted minnow traps. Mean CPUE of age-0 Mountain Whitefish was higher for seining (0.18 fish/m2; SD, 0.39) than for electrofishing (0.01 fish/m2; SD, 0.03), and the CV was lower for seining. A broader length distribution was sampled by seining (17–41 mm) than with electrofishing (21–36 mm). Age-0 Mountain Whitefish CPUE in seines was highest in backwaters. In channel sites, Mountain Whitefish presence was associated with areas of still or slow water ≥2 m2. Relative to the other sampling gears we evaluated, seining was the most efficient gear for sampling age-0 Mountain Whitefish in a lotic ecosystem.
","language":"English","publisher":"Taylor and Francis Online","doi":"10.1080/02755947.2016.1254128","usgsCitation":"Boyer, J.K., Guy, C.S., Webb, M., Horton, T.B., and McMahon, T., 2017, Gear comparison for sampling age-0 Mountain Whitefish in the Madison River, Montana: North American Journal of Fisheries Management, v. 37, no. 1, p. 189-195, https://doi.org/10.1080/02755947.2016.1254128.","productDescription":"8 p. 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H.","contributorId":193590,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[],"preferred":false,"id":700902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton, Travis B.","contributorId":193589,"corporation":false,"usgs":false,"family":"Horton","given":"Travis","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":700901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Thomas E.","contributorId":189425,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[],"preferred":false,"id":700903,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188376,"text":"70188376 - 2017 - Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass","interactions":[],"lastModifiedDate":"2017-06-07T14:16:23","indexId":"70188376","displayToPublicDate":"2017-01-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass","title":"Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass","docAbstract":"Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N-mixture model. Multinomial N-mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N-mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N-mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2016.1254127","usgsCitation":"Mollenhauer, R., and Brewer, S.K., 2017, Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass: North American Journal of Fisheries Management, v. 37, no. 1, p. 211-224, https://doi.org/10.1080/02755947.2016.1254127.","productDescription":"14 p.","startPage":"211","endPage":"224","ipdsId":"IP-073138","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":342254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.28167724609375,\n 35.380092992092145\n ],\n [\n -94.46868896484375,\n 35.36217605914681\n ],\n [\n -93.64471435546875,\n 35.3509759564216\n ],\n [\n -93.6749267578125,\n 37.13623498442895\n ],\n [\n -95.2789306640625,\n 37.13623498442895\n ],\n [\n -95.28167724609375,\n 35.380092992092145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-12","publicationStatus":"PW","scienceBaseUri":"593910ade4b0764e6c5e885c","contributors":{"authors":[{"text":"Mollenhauer, Robert","contributorId":176540,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[],"preferred":false,"id":697505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":697455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70181013,"text":"70181013 - 2017 - The contribution of rice agriculture to methylmercury in surface waters: A review of data from the Sacramento Valley, California","interactions":[],"lastModifiedDate":"2018-09-26T15:43:11","indexId":"70181013","displayToPublicDate":"2017-01-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"The contribution of rice agriculture to methylmercury in surface waters: A review of data from the Sacramento Valley, California","docAbstract":"Methylmercury (MeHg) is a bioaccumulative pollutant produced in and exported from flooded soils, including those used for rice (Oriza sativa L.) production. Using unfiltered aqueous MeHg data from MeHg monitoring programs in the Sacramento River watershed from 1996 to 2007, we assessed the MeHg contribution from rice systems to the Sacramento River. Using a mixed-effects regression analysis, we compared MeHg concentrations in agricultural drainage water from rice-dominated regions (AgDrain) to MeHg concentrations in the Sacramento and Feather Rivers, both upstream and downstream of AgDrain inputs. We also calculated MeHg loads from AgDrains and the Sacramento and Feather Rivers. Seasonally, MeHg concentrations were higher during November through May than during June through October, but the differences varied by location. Relative to upstream, November through May AgDrain least-squares mean MeHg concentration (0.18 ng L−1, range 0.15–0.23 ng L−1) was 2.3-fold higher, while June through October AgDrain mean concentration (0.097 ng L−1, range 0.6–1.6 ng L−1) was not significantly different from upstream. June through October AgDrain MeHg loads contributed 10.7 to 14.8% of the total Sacramento River MeHg load. Missing flow data prevented calculation of the percent contribution of AgDrains in November through May. At sites where calculation was possible, November through May loads made up 70 to 90% of the total annual load. Elevated flow and MeHg concentration in November through May both contribute to the majority of the AgDrain MeHg load occurring during this period. Methylmercury reduction efforts should target elevated November through May MeHg concentrations in AgDrains. However, our findings suggest that the contribution and environmental impact of rice is an order of magnitude lower than previous studies in the California Yolo Bypass.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.","doi":"10.2134/jeq2016.07.0262","usgsCitation":"Tanner, K.C., Windham-Myers, L., Fleck, J., Tate, K.W., McCord, S.A., and Linquist, B.A., 2017, The contribution of rice agriculture to methylmercury in surface waters: A review of data from the Sacramento Valley, California: Journal of Environmental Quality, v. 46, no. 1, p. 133-142, https://doi.org/10.2134/jeq2016.07.0262.","productDescription":"9 p.","startPage":"133","endPage":"142","ipdsId":"IP-083271","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470140,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2016.07.0262","text":"Publisher Index Page"},{"id":335172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.0745849609375,\n 38.53957267203905\n ],\n [\n -122.0745849609375,\n 39.41497702499074\n ],\n [\n -121.4044189453125,\n 39.41497702499074\n ],\n [\n -121.4044189453125,\n 38.53957267203905\n ],\n [\n -122.0745849609375,\n 38.53957267203905\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589ffedee4b099f50d3e0430","contributors":{"authors":[{"text":"Tanner, K. 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The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information is presented on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163069","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L.B., 2017, Water resources of East Feliciana Parish, Louisiana: U.S. Geological Survey Fact Sheet 2016–3069, 6 p., https://doi.org/10.3133/fs20163069.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-065609","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":333087,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3069/coverthb.jpg"},{"id":333088,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3069/fs20163069.pdf","text":"Fact Sheet","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3069"}],"country":"United States","state":"Louisiana","otherGeospatial":"East Feliciana Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-91.0608,30.9995],[-90.8268,30.9992],[-90.829,30.9947],[-90.8386,30.9916],[-90.8435,30.9839],[-90.843,30.9747],[-90.8458,30.9619],[-90.8474,30.9597],[-90.8506,30.9565],[-90.8565,30.9515],[-90.8619,30.9451],[-90.8588,30.9355],[-90.8572,30.9309],[-90.8541,30.9186],[-90.852,30.9108],[-90.8553,30.9053],[-90.8532,30.9012],[-90.8505,30.8985],[-90.8484,30.8962],[-90.8491,30.8825],[-90.8528,30.8788],[-90.856,30.8761],[-90.8598,30.8743],[-90.8598,30.8679],[-90.8577,30.8629],[-90.8551,30.856],[-90.853,30.8528],[-90.8493,30.8505],[-90.8424,30.8486],[-90.8414,30.8449],[-90.8425,30.8427],[-90.8468,30.8372],[-90.8457,30.8335],[-90.8447,30.8308],[-90.8421,30.8271],[-90.8405,30.8248],[-90.8378,30.8207],[-90.8352,30.8193],[-90.8347,30.8166],[-90.8379,30.8102],[-90.839,30.8066],[-90.8385,30.8024],[-90.8396,30.797],[-90.8434,30.7933],[-90.8423,30.7906],[-90.8419,30.7869],[-90.8419,30.7782],[-90.8404,30.7732],[-90.8436,30.7641],[-90.8447,30.7623],[-90.8479,30.7563],[-90.8512,30.75],[-90.8523,30.744],[-90.8502,30.7417],[-90.846,30.7362],[-90.8418,30.7325],[-90.8407,30.7266],[-90.8413,30.7234],[-90.8434,30.7229],[-90.8461,30.7211],[-90.8477,30.7198],[-91.2492,30.7072],[-91.2577,30.7027],[-91.2636,30.7],[-91.2678,30.6949],[-91.2673,30.6917],[-91.2689,30.6895],[-91.2679,30.6863],[-91.2711,30.6808],[-91.2891,30.6781],[-91.2897,30.668],[-91.2929,30.6621],[-91.2934,30.6552],[-91.2977,30.6493],[-91.2993,30.6516],[-91.3051,30.6529],[-91.3051,30.6735],[-91.3088,30.6804],[-91.3125,30.6822],[-91.3146,30.6927],[-91.3194,30.6959],[-91.321,30.6991],[-91.3194,30.7005],[-91.3135,30.6987],[-91.3119,30.6991],[-91.3109,30.7023],[-91.3114,30.7083],[-91.3039,30.7078],[-91.3007,30.7156],[-91.2928,30.716],[-91.2922,30.7188],[-91.2959,30.7252],[-91.2964,30.727],[-91.2863,30.7347],[-91.2874,30.7439],[-91.2863,30.7475],[-91.282,30.7507],[-91.2799,30.7535],[-91.2761,30.7585],[-91.2602,30.7621],[-91.2591,30.7658],[-91.2628,30.7745],[-91.2617,30.7758],[-91.2575,30.7767],[-91.2532,30.7776],[-91.2473,30.7868],[-91.2372,30.7945],[-91.2383,30.7977],[-91.2425,30.8009],[-91.243,30.8046],[-91.2361,30.8068],[-91.2329,30.81],[-91.2302,30.8164],[-91.2345,30.8219],[-91.2345,30.8246],[-91.2339,30.8256],[-91.2307,30.8333],[-91.227,30.8383],[-91.2269,30.8406],[-91.2253,30.8484],[-91.2296,30.8544],[-91.2232,30.8566],[-91.2194,30.8644],[-91.2258,30.8703],[-91.2247,30.8726],[-91.222,30.8735],[-91.221,30.8772],[-91.2225,30.8813],[-91.2188,30.8868],[-91.2156,30.8922],[-91.2065,30.8927],[-91.2065,30.9004],[-91.2091,30.9055],[-91.2059,30.9109],[-91.208,30.9137],[-91.208,30.9183],[-91.2,30.9191],[-91.1947,30.931],[-91.1931,30.9328],[-91.1898,30.9333],[-91.1872,30.9369],[-91.1914,30.9438],[-91.193,30.9507],[-91.1956,30.9598],[-91.1919,30.9671],[-91.1908,30.9721],[-91.1892,30.973],[-91.186,30.9721],[-91.1822,30.9739],[-91.1801,30.9789],[-91.1811,30.9853],[-91.18,30.9908],[-91.1757,31],[-91.1115,31],[-91.0608,30.9995]]]},\"properties\":{\"name\":\"East Feliciana\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
In 1975, the Federal government responded to the need for establishing national expertise in wildlife health by creating the National Wildlife Health Center (NWHC), a facility within the Department of the Interior; the NWHC is the only national center dedicated to wildlife disease detection, control, and prevention. Its mission is to provide national leadership to safeguard wildlife and ecosystem health through active partnerships and exceptional science. Comparisons are often made between the NWHC, which strives to protect the health of our Nation’s wildlife, and the Centers for Disease Control and Prevention (CDC), which strive to protect public health. The NWHC, a science center of the U.S. Geological Survey (USGS) with specialized laboratories, works to safeguard the Nation’s wildlife from diseases by studying the causes and drivers of these threats, and by developing strategies to prevent and manage them. In addition to the main campus, located in Madison, Wisconsin, the NWHC also operates the Honolulu Field Station that addresses wildlife health issues in Hawaii and the Pacific Region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163102","usgsCitation":"Moede Rogall, Gail, and Sleeman, J.M., 2017, The USGS National Wildlife Health Center: Advancing wildlife and ecosystem health: U.S. Geological Survey Fact Sheet 2016-3102, 6 p., https://doi.org/10.3133/fs20163102. ","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072962","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":333041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3102/fs20163102.pdf","text":"Report","size":"6.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3102"},{"id":333040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3102/coverthb.jpg"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711-6223
https://www.usgs.gov/nwhc
This paper describes the tectonic summaries for all magnitude 7 and larger earthquakes in the period 2000–2015, as produced by the U.S. Geological Survey National Earthquake Information Center during their routine response operations to global earthquakes. The goal of such summaries is to provide important event-specific information to the public rapidly and concisely, such that recent earthquakes can be understood within a global and regional seismotectonic framework. We compile these summaries here to provide a long-term archive for this information, and so that the variability in tectonic setting and earthquake history from region to region, and sometimes within a given region, can be more clearly understood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161192","usgsCitation":"Hayes, G.P., Myers, E.K., Dewey, J.W., Briggs, R.W., Earle, P.S., Benz, H.M., Smoczyk, G.M., Flamme, H.E., Barnhart, W.D., Gold, R.D., and Furlong, K.P., 2017, Tectonic summaries of magnitude 7 and greater earthquakes from 2000 to 2015: U.S. Geological Survey Open-File Report 2016–1192, 148 p., https://doi.org/10.3133/ofr20161192.","productDescription":"Report: v, 148 p.; KMZ file","onlineOnly":"Y","ipdsId":"IP-077362","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":333007,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1192/ofr20161192.kmz","text":"KMZ file","size":"112 kB","description":"OFR 2016-1192 KMZ file"},{"id":333005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1192/coverthb.jpg"},{"id":333006,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1192/ofr20161192.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1192"}],"otherGeospatial":"Earth","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
The Iġnik Sikumi Gas Hydrate Exchange Field Experiment was conducted by ConocoPhillips in partnership with the U.S. Department of Energy, the Japan Oil, Gas and Metals National Corporation, and the U.S. Geological Survey within the Prudhoe Bay Unit on the Alaska North Slope during 2011 and 2012. The primary goals of the program were to (1) determine the feasibility of gas injection into hydrate-bearing sand reservoirs and (2) observe reservoir response upon subsequent flowback in order to assess the potential for CO2 exchange for CH4 in naturally occurring gas hydrate reservoirs. Initial modeling determined that no feasible means of injection of pure CO2 was likely, given the presence of free water in the reservoir. Laboratory and numerical modeling studies indicated that the injection of a mixture of CO2 and N2 offered the best potential for gas injection and exchange. The test featured the following primary operational phases: (1) injection of a gaseous phase mixture of CO2, N2, and chemical tracers; (2) flowback conducted at downhole pressures above the stability threshold for native CH4 hydrate; and (3) an extended (30-days) flowback at pressures near, and then below, the stability threshold of native CH4 hydrate. The test findings indicate that the formation of a range of mixed-gas hydrates resulted in a net exchange of CO2 for CH4 in the reservoir, although the complexity of the subsurface environment renders the nature, extent, and efficiency of the exchange reaction uncertain. The next steps in the evaluation of exchange technology should feature multiple well applications; however, such field test programs will require extensive preparatory experimental and numerical modeling studies and will likely be a secondary priority to further field testing of production through depressurization. Additional insights gained from the field program include the following: (1) gas hydrate destabilization is self-limiting, dispelling any notion of the potential for uncontrolled destabilization; (2) gas hydrate test wells must be carefully designed to enable rapid remediation of wellbore blockages that will occur during any cessation in operations; (3) sand production during hydrate production likely can be managed through standard engineering controls; and (4) reservoir heat exchange during depressurization was more favorable than expected—mitigating concerns for near-wellbore freezing and enabling consideration of more aggressive pressure reduction.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.energyfuels.6b01909","usgsCitation":"Boswell, R., Schoderbek, D., Collett, T.S., Ohtsuki, S., White, M., and Anderson, B.J., 2017, The Iġnik Sikumi Field Experiment, Alaska North Slope: Design, operations, and implications for CO2−CH4 exchange in gas hydrate reservoirs: Energy & Fuels, v. 31, no. 1, p. 140-153, https://doi.org/10.1021/acs.energyfuels.6b01909.","productDescription":"14 p.","startPage":"140","endPage":"153","ipdsId":"IP-074604","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":333052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-14","publicationStatus":"PW","scienceBaseUri":"58772077e4b0315b4c11fe24","contributors":{"authors":[{"text":"Boswell, Ray","contributorId":12307,"corporation":false,"usgs":true,"family":"Boswell","given":"Ray","affiliations":[],"preferred":false,"id":658205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoderbek, David","contributorId":178207,"corporation":false,"usgs":false,"family":"Schoderbek","given":"David","email":"","affiliations":[],"preferred":false,"id":658206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":658204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ohtsuki, Satoshi","contributorId":150141,"corporation":false,"usgs":false,"family":"Ohtsuki","given":"Satoshi","email":"","affiliations":[{"id":17917,"text":"Japan Oil, Gas and Metals National Corporation","active":true,"usgs":false}],"preferred":false,"id":658208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Mark","contributorId":150142,"corporation":false,"usgs":false,"family":"White","given":"Mark","email":"","affiliations":[{"id":6727,"text":"Pacific Northwest National Laboratory, Richland, WA","active":true,"usgs":false}],"preferred":false,"id":658209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Brian J.","contributorId":147120,"corporation":false,"usgs":false,"family":"Anderson","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":658207,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70181010,"text":"70181010 - 2017 - Acetylene fuels TCE reductive dechlorination by defined Dehalococcoides/Pelobacter consortia","interactions":[],"lastModifiedDate":"2017-02-24T10:37:55","indexId":"70181010","displayToPublicDate":"2017-01-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Acetylene fuels TCE reductive dechlorination by defined Dehalococcoides/Pelobacter consortia","docAbstract":"Acetylene (C2H2) can be generated in contaminated groundwater sites as a consequence of chemical degradation of trichloroethene (TCE) by in situ minerals, and C2H2 is known to inhibit bacterial dechlorination. In this study, we show that while high C2H2 (1.3 mM) concentrations reversibly inhibit reductive dechlorination of TCE by Dehalococcoides mccartyi isolates as well as enrichment cultures containing D. mccartyi sp., low C2H2 (0.4 mM) concentrations do not inhibit growth or metabolism of D. mccartyi. Cocultures of Pelobacter SFB93, a C2H2-fermenting bacterium, with D. mccartyi strain 195 or with D. mccartyi strain BAV1 were actively sustained by providing acetylene as the electron donor and carbon source while TCE or cis-DCE served as the electron acceptor. Inhibition by acetylene of reductive dechlorination and methanogenesis in the enrichment culture ANAS was observed, and the inhibition was removed by adding Pelobacter SFB93 into the consortium. Transcriptomic analysis of D. mccartyi strain 195 showed genes encoding for reductive dehalogenases (e.g., tceA) were not affected during the C2H2-inhibition, while genes encoding for ATP synthase, biosynthesis, and Hym hydrogenase were down-regulated during C2H2 inhibition, consistent with the physiological observation of lower cell yields and reduced dechlorination rates in strain 195. These results will help facilitate the optimization of TCE-bioremediation at contaminated sites containing both TCE and C2H2.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.6b05770","usgsCitation":"Mao, X., Oremland, R.S., Liu, T., Landers, A.A., Baesman, S., and Alvarez-Cohen, L., 2017, Acetylene fuels TCE reductive dechlorination by defined Dehalococcoides/Pelobacter consortia: Environmental Science & Technology, v. 51, no. 4, p. 2366-2372, https://doi.org/10.1021/acs.est.6b05770.","productDescription":"7 p.","startPage":"2366","endPage":"2372","ipdsId":"IP-081407","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470141,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6436540","text":"External Repository"},{"id":335176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-03","publicationStatus":"PW","scienceBaseUri":"589ffedee4b099f50d3e0432","chorus":{"doi":"10.1021/acs.est.6b05770","url":"http://dx.doi.org/10.1021/acs.est.6b05770","publisher":"American Chemical Society (ACS)","authors":"Mao Xinwei, Oremland Ronald S., Liu Tong, Gushgari Sara, Landers Abigail A., Baesman Shaun M., Alvarez-Cohen Lisa","journalName":"Environmental Science & Technology","publicationDate":"2/3/2017"},"contributors":{"authors":[{"text":"Mao, Xinwei","contributorId":179298,"corporation":false,"usgs":false,"family":"Mao","given":"Xinwei","email":"","affiliations":[],"preferred":false,"id":663260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":663258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Tong","contributorId":179299,"corporation":false,"usgs":false,"family":"Liu","given":"Tong","email":"","affiliations":[],"preferred":false,"id":663261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landers, Abigail A","contributorId":179300,"corporation":false,"usgs":false,"family":"Landers","given":"Abigail","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":663262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baesman, Shaun 0000-0003-0741-8269 sbaesman@usgs.gov","orcid":"https://orcid.org/0000-0003-0741-8269","contributorId":3478,"corporation":false,"usgs":true,"family":"Baesman","given":"Shaun","email":"sbaesman@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":663264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alvarez-Cohen, Lisa","contributorId":179301,"corporation":false,"usgs":false,"family":"Alvarez-Cohen","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":663265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178590,"text":"ofr20161198 - 2017 - Peak streamflow on selected streams in Arkansas, December 2015","interactions":[],"lastModifiedDate":"2017-01-11T15:13:09","indexId":"ofr20161198","displayToPublicDate":"2017-01-11T00:00:00","publicationYear":"2017","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":"2016-1198","title":"Peak streamflow on selected streams in Arkansas, December 2015","docAbstract":"Heavy rainfall during December 2015 resulted in flooding across parts of Arkansas; rainfall amounts were as high as 12 inches over a period from December 27, 2015, to December 29, 2015. Although precipitation accumulations were highest in northwestern Arkansas, significant flooding occurred in other parts of the State. Flood damage occurred in several counties as water levels rose in streams, and disaster declarations were declared in 32 of the 75 counties in Arkansas.
Given the severity of the December 2015 flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency (FEMA), conducted a study to document the meteorological and hydrological conditions prior to and during the flood; compiled flood-peak gage heights, streamflows, and flood probabilities at USGS streamflow-gaging stations; and estimated streamflows and flood probabilities at selected ungaged locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161198","usgsCitation":"Breaker, B.K., 2017, Peak streamflow on selected streams in Arkansas, December 2015: U.S. Geological Survey Open-File Report 2016–1198, 7 p., https://doi.org/10.3133/ofr20161198.","productDescription":"7 p.","onlineOnly":"Y","ipdsId":"IP-079418","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":332997,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1198/coverthb2.jpg"},{"id":332995,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1198/ofr20161198.pdf","text":"Report","size":"622 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1198"}],"country":"United 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U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-016-0274-1","usgsCitation":"Hefley, T.J., Hooten, M., Hanks, E.M., Russell, R.E., and Walsh, D.P., 2017, The Bayesian group lasso for confounded spatial data: Journal of Agricultural, Biological, and Environmental Statistics, v. 22, no. 1, p. 42-59, https://doi.org/10.1007/s13253-016-0274-1.","productDescription":"18 p.","startPage":"42","endPage":"59","ipdsId":"IP-071980","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":333019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"22","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-05","publicationStatus":"PW","scienceBaseUri":"58760114e4b04eac8e0746d5","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":657904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":657903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Ephraim M.","contributorId":178093,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":657905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":657906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":657907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179652,"text":"70179652 - 2017 - Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach","interactions":[],"lastModifiedDate":"2017-01-10T10:34:49","indexId":"70179652","displayToPublicDate":"2017-01-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach","docAbstract":"The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat requirements and will be useful for management and conservation activities.
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