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The wetlands of the Great Salt Lake ecosystem are recognized regionally, nationally, and hemispherically for their importance as breeding, wintering, and migratory habitat for diverse groups of waterbirds. Bear River Migratory Bird Refuge is the largest freshwater component of the Great Salt Lake ecosystem and provides critical breeding habitat for more than 60 bird species. However, the Great Salt Lake ecosystem also has a history of both mercury and selenium contamination, and this pollution could reduce the health and reproductive success of waterbirds. The overall objective of this study was to evaluate the risk of mercury and selenium contamination to birds breeding within Great Salt Lake, especially at Bear River Migratory Bird Refuge, and to identify the waterbird species and areas at greatest risk to contamination. We sampled eggs from 33 species of birds breeding within wetlands of Great Salt Lake during 2010 ̶ 2012 and focused on American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), Forster’s terns (Sterna forsteri), white-faced ibis (Plegadis chihi), and marsh wrens (Cistothorus palustris) for additional studies of the effects of contaminants on reproduction.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151020","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ackerman, J., Herzog, M., Hartman, C.A., Isanhart, J., Herring, G., Vaughn, S., Cavitt, J.F., Eagles-Smith, C.A., Browers, H., Cline, C., and Vest, J., 2015, Mercury and selenium contamination in waterbird eggs and risk to avian reproduction at Great Salt Lake, Utah: U.S. Geological Survey Open-File Report 2015-1020, Report: x, 164 p.; Data Release, https://doi.org/10.3133/ofr20151020.","productDescription":"Report: x, 164 p.; Data Release","numberOfPages":"178","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061800","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":297692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151020.jpg"},{"id":297691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1020/pdf/ofr2015-1020.pdf","text":"Report","size":"15.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297690,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1020/"},{"id":374389,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4US4N","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Mercury and selenium concentrations in bird eggs at Great Salt Lake, Utah"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 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Center","active":true,"usgs":true}],"preferred":false,"id":539655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":3965,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, Christopher A. chartman@usgs.gov","contributorId":5242,"corporation":false,"usgs":true,"family":"Hartman","given":"Christopher","email":"chartman@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isanhart, John P.","contributorId":20209,"corporation":false,"usgs":true,"family":"Isanhart","given":"John P.","affiliations":[],"preferred":false,"id":539725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":539726,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vaughn, Sharon","contributorId":139009,"corporation":false,"usgs":false,"family":"Vaughn","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":539727,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cavitt, John F.","contributorId":28112,"corporation":false,"usgs":true,"family":"Cavitt","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":539728,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":539729,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Browers, Howard","contributorId":139010,"corporation":false,"usgs":false,"family":"Browers","given":"Howard","email":"","affiliations":[],"preferred":false,"id":539730,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cline, Chris","contributorId":139011,"corporation":false,"usgs":false,"family":"Cline","given":"Chris","email":"","affiliations":[],"preferred":false,"id":539731,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vest, Josh","contributorId":24240,"corporation":false,"usgs":false,"family":"Vest","given":"Josh","affiliations":[],"preferred":false,"id":539732,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70139777,"text":"ofr20151017 - 2015 - A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","interactions":[],"lastModifiedDate":"2017-02-08T13:32:17","indexId":"ofr20151017","displayToPublicDate":"2015-02-02T14:30:00","publicationYear":"2015","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":"2015-1017","title":"A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning","docAbstract":"

The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151017","collaboration":"Prepared in cooperation with the California Landscape Conservation Cooperative, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Matchett, E., Fleskes, J.P., Young, C., and Purkey, D.R., 2015, A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning: U.S. Geological Survey Open-File Report 2015-1017, vi, 40 p., https://doi.org/10.3133/ofr20151017.","productDescription":"vi, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053267","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":334995,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H13050","text":"Data for projected impacts of climate, urbanization, water management, and wetland restoration on waterbird habitat in California’s Central Valley"},{"id":297683,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1017/"},{"id":297684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151017.PNG"},{"id":297685,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1017/pdf/ofr2015-1017.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.16748046874999,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 40.68063802521456\n ],\n [\n -119.68505859375,\n 34.59704151614417\n ],\n [\n -124.16748046874999,\n 34.59704151614417\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4ae4b08de9379b2fc4","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Charles A.","contributorId":139008,"corporation":false,"usgs":false,"family":"Young","given":"Charles A.","affiliations":[],"preferred":false,"id":539698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purkey, David R.","contributorId":139005,"corporation":false,"usgs":false,"family":"Purkey","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":539696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70123191,"text":"ds877 - 2015 - Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","interactions":[],"lastModifiedDate":"2015-02-02T12:50:59","indexId":"ds877","displayToPublicDate":"2015-02-02T12:45:00","publicationYear":"2015","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":"877","title":"Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset","docAbstract":"

Wetland sediment data were collected in 2009 and 2010 throughout the southwest Louisiana Chenier Plain as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits from tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh, intermediate, and brackish marsh and are located coincident with Coastwide Reference Monitoring System (CRMS) sites. The nine sediment cores were collected at the Rockefeller Wildlife Refuge (RWR) located in Grand Chenier, La.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds877","usgsCitation":"Smith, K.E., Flocks, J.G., Steyer, G.D., and Piazza, S.C., 2015, Wetland paleoecological study of southwest coastal Louisiana: sediment cores and diatom calibration dataset: U.S. Geological Survey Data Series 877, HTML Document, https://doi.org/10.3133/ds877.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052587","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds877.PNG"},{"id":297678,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0877/"},{"id":297679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0877/html/ds877_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"Louisiana","city":"Grand Chenier","otherGeospatial":"Chenier Plain, Rockefeller Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85894775390625,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 30.071470887901302\n ],\n [\n -91.96929931640624,\n 29.508939763268394\n ],\n [\n -93.85894775390625,\n 29.508939763268394\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ad0e4b08de9379b321c","contributors":{"authors":[{"text":"Smith, Kathryn E. L. kelsmith@usgs.gov","contributorId":3242,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E. L.","affiliations":[],"preferred":false,"id":519342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":539676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piazza, Sarai C. 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":466,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":539677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133604,"text":"ds901 - 2015 - Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","interactions":[],"lastModifiedDate":"2016-02-08T14:09:10","indexId":"ds901","displayToPublicDate":"2015-02-02T12:30:00","publicationYear":"2015","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":"901","title":"Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions","docAbstract":"

This report describes a series of geoelectrical soundings carried out on and near Mount St. Helens volcano, Washington, in 2010–2011. These soundings used a controlled-source audio-frequency magnetotelluric (CSAMT) approach (Zonge and Hughes, 1991; Simpson and Bahr, 2005). We chose CSAMT for logistical reasons: It can be deployed by helicopter, has an effective depth of penetration of as much as 1 kilometer, and requires less wire than a Schlumberger sounding.

\n

This Data Series provides the edited data for these CSAMT soundings as well as several different types of 1-D inversions (where the signal data are converted to conductivity-versus-depth models). In addition, we include a map showing station locations on and around the volcano and the Pumice Plain to the north.

\n

The apparent conductivity (or its inverse, apparent resistivity) measured by a geoelectrical system is caused by several factors. The most important of these are water-filled rock porosity and the presence of water-filled fractures; however, rock type and minerals (for instance, sulfides and clay content) also contribute to apparent conductivity. In situations with little recharge (for instance, in arid regions), variations in ionic content of water occupying pore space and fractures sampled by the measurement system must also be factored in (Wynn, 2006). Variations in ionic content may also be present in hydrothermal fluids surrounding volcanoes in wet regions. In unusual cases, temperature may also affect apparent conductivity (Keller, 1989; Palacky, 1989). There is relatively little hydrothermal alteration (and thus fewer clay minerals that might add to the apparent conductivity) in the eruptive products of Mount St. Helens (Reid and others, 2010), so conductors observed in the Fischer, Occam, and Marquardt inversion results later in this report are thus believed to map zones with significant water content. Geoelectrical surveys thus have the potential to reveal subsurface regions with significant groundwater content, including perched and regional aquifers. Reid and others (2001) and Reid (2004) have suggested that groundwater involvement may figure in both the scale and the character of some if not all volcanic edifice collapse events. Ongoing research by the U.S. Geological Survey (USGS) and others aims to better understand the contribution of groundwater to both edifice pore pressure and rock alteration as well as its direct influence on eruption processes by violent interaction with magma (Schmincke, 1998).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds901","usgsCitation":"Wynn, J., and Pierce, H., 2015, Mount St. Helens: Controlled-source audio-frequency magnetotelluric (CSAMT) data and inversions: U.S. Geological Survey Data Series 901, HTML Document, https://doi.org/10.3133/ds901.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044700","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297677,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds901.gif"},{"id":316600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/ds901.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297676,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0901/cover.html","text":"Report","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator projection, Zone 10N","datum":"World Geodetic System 1984","country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28675842285158,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.27388525189855\n ],\n [\n -122.09415435791016,\n 46.150107913663334\n ],\n [\n -122.28675842285158,\n 46.150107913663334\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a9ce4b08de9379b3137","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Herbert A.","contributorId":83093,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert A.","affiliations":[],"preferred":false,"id":539673,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148078,"text":"70148078 - 2015 - Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","interactions":[],"lastModifiedDate":"2017-07-26T17:13:27","indexId":"70148078","displayToPublicDate":"2015-02-02T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping migratory flyways in Asia using dynamic Brownian bridge movement models","docAbstract":"

Background

\n

Identifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways.

\n

Results

\n

Our approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct.

\n

Conclusions

\n

The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.

","language":"English","publisher":"Minerva Center for Movement Ecology","publisherLocation":"London","doi":"10.1186/s40462-015-0029-6","usgsCitation":"Palm, E., Newman, S.H., Prosser, D.J., Xiao, X., Luo, Z., Batbayar, N., Balachandran, S., and Takekawa, J.Y., 2015, Mapping migratory flyways in Asia using dynamic Brownian bridge movement models: Movement Ecology, v. 3, no. 1, p. 1-10, https://doi.org/10.1186/s40462-015-0029-6.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062254","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-015-0029-6","text":"Publisher Index Page"},{"id":300545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-02","publicationStatus":"PW","scienceBaseUri":"555c5eb6e4b0a92fa7eacc02","contributors":{"authors":[{"text":"Palm, E.C.","contributorId":40708,"corporation":false,"usgs":true,"family":"Palm","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":547228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, S. H.","contributorId":21888,"corporation":false,"usgs":false,"family":"Newman","given":"S.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":547229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiao, Xiangming","contributorId":67212,"corporation":false,"usgs":true,"family":"Xiao","given":"Xiangming","affiliations":[],"preferred":false,"id":547231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":547232,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":547233,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Balachandran, Sivananinthaperumal","contributorId":20593,"corporation":false,"usgs":true,"family":"Balachandran","given":"Sivananinthaperumal","affiliations":[],"preferred":false,"id":547234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":547235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70135892,"text":"sir20145232 - 2015 - Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","interactions":[],"lastModifiedDate":"2015-04-20T14:25:03","indexId":"sir20145232","displayToPublicDate":"2015-02-02T09:00:00","publicationYear":"2015","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":"2014-5232","title":"Potentiometric surfaces and water-level trends in the Cockfield (upper Claiborne) aquifer in southern Arkansas and the Wilcox (lower Wilcox) aquifer of northeastern and southern Arkansas, 2012","docAbstract":"

The Cockfield aquifer, located in southern Arkansas, is composed of Eocene-age sand beds found near the base of the Cockfield Formation of Claiborne Group. The Wilcox aquifer, located in northeastern and southern Arkansas, is composed of Paleocene-age sand beds found in the middle to lower part of the Wilcox Group. The Cockfield and Wilcox aquifers are primary sources of groundwater. In 2010, withdrawals from the Cockfield aquifer in Arkansas totaled 19.2 million gallons per day (Mgal/d), and withdrawals from the Wilcox aquifer totaled 36.5 Mgal/d.

\n

A study was conducted by the U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey to measure water levels associated with the Cockfield aquifer and the Wilcox aquifer in northeastern and southern Arkansas. Water levels were measured at 43 wells completed in the Cockfield aquifer and 47 wells completed in the Wilcox aquifer in February and March 2012. Measurements from 2012 are presented as potentiometric-surface maps and in combination with measurements from 2006 as water-level difference maps. Trends in water-level change over time within the Cockfield and Wilcox aquifers were determined using the water-level difference maps and selected well hydrographs.

\n

The Cockfield aquifer study area in southern Arkansas is bounded on the east by the Mississippi River and on the west by the area that contains outcrops and subcrops of the Cockfield Formation. The northern boundary of the Cockfield aquifer study area is defined by the area that contains observation wells completed in the Cockfield aquifer and the southern boundary is the Louisiana State line.

\n

The Wilcox aquifer study area in northeastern Arkansas is bounded on the east by the Mississippi River and on the north by the Missouri State line. The southern and western boundaries are defined by areas containing observation wells completed in the Wilcox aquifer or by outcrop areas on or near Crowleys Ridge. The Wilcox aquifer study area in southern Arkansas is defined by observation wells completed in the Wilcox aquifer or by areas that contain outcrops of the Wilcox Group, or both.

\n

The potentiometric-surface map of the Cockfield aquifer shows the regional direction of groundwater flow was generally toward the east-southeast, except in areas of intense groundwater withdrawals such as southwestern Ashley County, where groundwater flows toward the town of Crossett. The highest water-level altitude measured was 350 feet (ft) above National Geodetic Vertical Datum of 1929 (NGVD 29) in central Columbia County. The lowest water-level altitude measured was 40 ft above NGVD 29 in southeastern Lincoln County.

\n

The water-level difference map for the Cockfield aquifer in Arkansas was constructed using 42 water-level measurements made during 2006 and 2012. The difference in water levels for the Cockfield aquifer ranged from 27.4 ft to -10.4 ft. The largest water-level rise was in Calhoun County, and the largest water-level decline was 10.4 ft in Union County. Of the 42 wells, 13 wells had a rise in water level, and the remaining 29 wells had a decline in water level.

\n

Hydrographs for 32 wells in the Cockfield aquifer with historical water-level data were evaluated using linear regression to calculate the annual rise or decline for each well. These data were aggregated by county and statistically evaluated for the range, mean, and median of water-level change in each county. Hydrographs for Bradley, Calhoun, Chicot, Columbia, and Union Counties indicated both rising and declining water levels. The mean annual water-level rise or decline for Calhoun County was 0.00 foot per year (ft/yr) or unchanged. The mean annual water-level for Ashley, Bradley, Chicot, Cleveland, Columbia, Lincoln, and Union Counties show declines ranging from -0.02 to -1.10 ft/yr.

\n

Two potentiometric-surface maps, one for the southern area and one for the northeastern area, were constructed to show the altitude of the water surface in the Wilcox aquifer. The direction of groundwater flow in the northeastern area was generally towards the south-southwest except for some areas immediately adjacent to the Mississippi River where the flow was more eastward towards the river. The highest water-level altitude was 219 ft in northern Mississippi County, and the lowest water-level altitude was 123 ft near West Memphis in Crittenden County. The direction of groundwater flow in the northern part of the southern area was generally towards the southwest. The direction of groundwater flow in the southern part was in all directions because of two cones of depression and two water-level mounds. The highest water-level altitude measured was 394 ft at the center of a water-level mound in eastern Hot Spring County and a water-level mound in southwestern Hempstead County. The lowest water-level altitude measured was 145 ft at the center of the cone of depression in Clark County.

\n

Water-level difference maps for the Wilcox aquifer in Arkansas were constructed using 47 water-level measurements made during 2006 and 2012. The difference in water levels for the Wilcox aquifer in the northeastern area ranged from 22.0 ft to -17.9 ft. The largest rise in water level occurred in Crittenden County, and the largest decline occurred in Lee County. Twenty-one wells had rising water levels, and 10 wells had declining water levels. The difference in water levels for the Wilcox aquifer in the southern area ranged from 18.1 ft to -4.2 ft. The largest rise and the largest decline in water level occurred in Nevada County. Twelve wells had rising water levels, and 4 wells had declining water levels.

\n

Linear regression analysis of long-term hydrographs was used to determine the mean annual water-level rise and decline in the Wilcox aquifer in the northeastern and southern areas of Arkansas. In the northeastern area, the mean annual water level declined in all seven counties. The mean annual declines ranged from -0.55 ft/yr in Craighead County to -1.46 ft/yr in St. Francis County. In the southern area, the annual rise and decline calculations for wells with over 20 years of records indicate rising and declining water levels in Clark, Hot Spring, and Nevada Counties. The mean annual water level declined in all counties except Hot Spring County.

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Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536978,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137956,"text":"ofr20151007 - 2015 - Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-04-12T17:29:26","indexId":"ofr20151007","displayToPublicDate":"2015-02-02T08:30:00","publicationYear":"2015","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":"2015-1007","title":"Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin","docAbstract":"

In 2009, the U.S. Geological Survey (USGS) developed a Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model for the Upper Colorado River Basin (UCRB) relating dissolved-solids sources and transport in the 1991 water year to upstream catchment characteristics. The SPARROW model focused on geologic and agricultural sources of dissolved solids in the UCRB and was calibrated using water-year 1991 dissolved-solids loads from 218 monitoring sites. A new UCRB SPARROW model is planned that will update the investigation of dissolved-solids sources and transport in the basin to circa 2010 conditions and will improve upon the 2009 model by incorporating more detailed information about agricultural-irrigation and rangeland-management practices, among other improvements. Geospatial datasets relating to circa 2010 rangeland conditions are required for the new UCRB SPARROW modeling effort. This study compiled geospatial datasets for the UCRB that relate to the biotic alterations and rangeland conditions of grazing, fire and other land disturbance, and vegetation type and cover. Datasets representing abiotic alterations of access control (off-highway vehicles) and sediment generation and transport in general, were also compiled. These geospatial datasets may be tested in the upcoming SPARROW model to better understand the potential contribution of rangelands to dissolved-solids loading in UCRB streams.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151007","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Tillman, F., Flynn, M., and Anning, D.W., 2015, Geospatial datasets for assessing the effects of rangeland conditions on dissolved-solids yields in the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1007, Report: v, 21 p.; 6 Geospatial Datasets, https://doi.org/10.3133/ofr20151007.","productDescription":"Report: v, 21 p.; 6 Geospatial Datasets","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060100","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":297671,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151007.gif"},{"id":297670,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/UCRB_R-factor.zip","text":"Rainfall-Runoff Erosivity","size":"962 kB","description":"Geospatial dataset","linkHelpText":"This tabular dataset presents the 1971–2000 average annual rainfall-runoff erosivity factor (R-factor) for the UCRB. The R-factor is a measure of the cumulative erosive force of individual precipitation events (Daly and Taylor, 2002). All other factors being constant, sediment generation from precipitation is directly proportional to the product of the total kinetic energy of a storm and the storm’s maximum 30-minute intensity. The mean annual R-factor is a sum of this product for all storms in a year, averaged over all years of record (Daly and Taylor, 2002)."},{"id":297663,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1007/"},{"id":297668,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_VegTypeCover.zip","text":"Existing Vegetation Type and Cover","size":"540 MB","description":"Geospatial dataset","linkHelpText":"These layers include information on the vegetation type and vegetation cover in 2010 in the UCRB. The 2010 existing vegetation cover (EVC) layer represents the vertically projected percent cover of the live canopy layer. The 2010 existing vegetation type (EVT) layer represents the species composition. Spatially, both grids cover the entire UCRB and have a 30-meter pixel resolution."},{"id":297664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/OFR2015-1007.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297666,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2015/1007/downloads/datasets/2010_UCRB_USFS_Grazing_projected.zip","text":"U.S. Forest Service Grazing","size":"3.8 MB","description":"Geospatial dataset","linkHelpText":"The shapefile contains 444 polygons of USFS grazing allotments within or bordering the UCRB (fig. 4). 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Center","active":true,"usgs":true}],"preferred":true,"id":539658,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168684,"text":"70168684 - 2015 - River mainstem thermal regimes influence population structuring within an Appalachian brook trout population","interactions":[],"lastModifiedDate":"2019-12-14T06:14:04","indexId":"70168684","displayToPublicDate":"2015-02-01T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"River mainstem thermal regimes influence population structuring within an Appalachian brook trout population","docAbstract":"

Brook trout (Salvelinus fontinalis) often exist as highly differentiated populations, even at small spatial scales, due either to natural or anthropogenic sources of isolation and low rates of dispersal. In this study, we used molecular approaches to describe the unique population structure of brook trout inhabiting the Shavers Fork watershed, located in eastern West Virginia, and contrast it to nearby populations in tributaries of the upper Greenbrier River and North Fork South Branch Potomac Rivers. Bayesian and maximum likelihood clustering methods identified minimal population structuring among 14 collections of brook trout from throughout the mainstem and tributaries of Shavers Fork, highlighting the role of the cold-water mainstem for connectivity and high rates of effective migration among tributaries. In contrast, the Potomac and Greenbrier River collections displayed distinct levels of population differentiation among tributaries, presumably resulting from tributary isolation by warm-water mainstems. Our results highlight the importance of protecting and restoring cold-water mainstem habitats as part of region-wide brook trout conservation efforts. In addition, our results from Shavers Fork provide a contrast to previous genetic studies that characterize Appalachian brook trout as fragmented isolates rather than well-mixed populations. Additional study is needed to determine whether the existence of brook trout as genetically similar populations among tributaries is truly unique and whether connectivity among brook trout populations can potentially be restored within other central Appalachian watersheds.

","language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0636-6","usgsCitation":"Aunins, A.W., Petty, J.T., King, T.L., Schilz, M., and Mazik, P.M., 2015, River mainstem thermal regimes influence population structuring within an Appalachian brook trout population: Conservation Genetics, v. 16, no. 1, p. 15-29, https://doi.org/10.1007/s10592-014-0636-6.","productDescription":"15 p.","startPage":"15","endPage":"29","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052856","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":318369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.079345703125,\n 38.09998264736481\n ],\n [\n -79.420166015625,\n 38.03078569382294\n ],\n [\n -78.299560546875,\n 39.308800296002914\n ],\n [\n -78.760986328125,\n 39.470125122358176\n ],\n [\n -79.1015625,\n 39.35978526869001\n ],\n [\n -80.079345703125,\n 38.09998264736481\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-27","publicationStatus":"PW","scienceBaseUri":"56cee27be4b015c306ec5f01","contributors":{"authors":[{"text":"Aunins, Aaron W. 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","middleInitial":"W.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":621315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schilz, Mariya","contributorId":167176,"corporation":false,"usgs":false,"family":"Schilz","given":"Mariya","email":"","affiliations":[],"preferred":false,"id":621317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":621262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155258,"text":"70155258 - 2015 - A Bayesian kriging approach for blending satellite and ground precipitation observations","interactions":[],"lastModifiedDate":"2022-11-15T15:07:01.784075","indexId":"70155258","displayToPublicDate":"2015-02-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian kriging approach for blending satellite and ground precipitation observations","docAbstract":"

Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the “true” observed precipitation value at each grid cell.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2014WR015963","usgsCitation":"Verdin, A.P., Rajagopalan, B., Kleiber, W., and Funk, C.C., 2015, A Bayesian kriging approach for blending satellite and ground precipitation observations: Water Resources Research, v. 51, no. 2, p. 908-921, https://doi.org/10.1002/2014WR015963.","productDescription":"14 p.","startPage":"908","endPage":"921","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059780","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015963","text":"Publisher Index Page"},{"id":306505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.81632212611561,\n 10.015029125925736\n ],\n [\n -71.2808031725719,\n 12.09555191269581\n ],\n [\n -74.73402713091187,\n 10.852006430112795\n ],\n [\n -77.21850797862407,\n 8.713663685154202\n ],\n [\n -79.41987151315135,\n 9.786489276111354\n ],\n [\n -81.04404574688206,\n 8.743926005251254\n ],\n [\n -82.41623838685905,\n 9.473469414609596\n ],\n [\n -83.73635743659167,\n 11.525091246808799\n ],\n [\n -83.23445386370992,\n 14.652633865094415\n ],\n [\n -84.32577316042915,\n 15.88928095391691\n ],\n [\n -88.79734742847882,\n 16.004790444581047\n ],\n [\n -88.21513890838666,\n 18.344083184580015\n ],\n [\n -90.40042887702003,\n 17.759482734359935\n ],\n [\n -91.04910311365558,\n 17.14123874170798\n ],\n [\n -90.35911384507358,\n 16.391142531706166\n ],\n [\n -92.22557510093608,\n 14.38136938077568\n ],\n [\n -90.87228561271752,\n 13.623920899226192\n ],\n [\n -87.61119935386394,\n 13.26864716978318\n ],\n [\n -82.09248872782524,\n 7.933279880637983\n ],\n [\n -80.86633169250197,\n 7.172026204942057\n ],\n [\n -80.09014204558488,\n 7.47701439779469\n ],\n [\n -80.46443299353692,\n 8.17781343122843\n ],\n [\n -79.01162994394076,\n 8.782940526946703\n ],\n [\n -77.32715639625906,\n 6.170679076154258\n ],\n [\n -78.63977018899459,\n 1.7560879959772535\n ],\n [\n -76.29608093885051,\n 0.4803896875874756\n ],\n [\n -64.81632212611561,\n 10.015029125925736\n ],\n [\n -64.81632212611561,\n 10.015029125925736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"55c9cb2ee4b08400b1fdb6df","contributors":{"authors":[{"text":"Verdin, Andrew P.","contributorId":35235,"corporation":false,"usgs":true,"family":"Verdin","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":565397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rajagopalan, Balaji","contributorId":145813,"corporation":false,"usgs":false,"family":"Rajagopalan","given":"Balaji","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":565398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleiber, William","contributorId":145814,"corporation":false,"usgs":false,"family":"Kleiber","given":"William","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":565399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155259,"text":"70155259 - 2015 - Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","interactions":[],"lastModifiedDate":"2017-01-18T10:06:09","indexId":"70155259","displayToPublicDate":"2015-02-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture","docAbstract":"

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JHM-D-14-0049.1","collaboration":"Amy McNally; Gregory J. Husak; Molly Brown; Mark Carroll; Chris Funk; Joel Michaelsen; Soni Yatheendradas; Kristi Arsenault, Christa Peters-Lidard; James P. Verdin","usgsCitation":"McNally, A., Gregory J. Husak, Brown, M., Carroll, M.L., Funk, C.C., Soni Yatheendradas, Arsenault, K., Christa Peters-Lidard, and Verdin, J., 2015, Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture: Journal of Hydrometeorology, v. 16, no. 1, p. 295-305, https://doi.org/10.1175/JHM-D-14-0049.1.","productDescription":"11 p.","startPage":"295","endPage":"305","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0049.1","text":"Publisher Index Page"},{"id":306506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-04","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a4","contributors":{"authors":[{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gregory J. Husak","contributorId":145824,"corporation":false,"usgs":false,"family":"Gregory J. Husak","affiliations":[{"id":16245,"text":"Department of Geography and Climate Hazards Group, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":565401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Molly","contributorId":145825,"corporation":false,"usgs":false,"family":"Brown","given":"Molly","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, Mark L.","contributorId":145826,"corporation":false,"usgs":false,"family":"Carroll","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":7239,"text":"Science Systems and Applications, Inc.","active":true,"usgs":false},{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":16247,"text":"Sigma Space Corp, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soni Yatheendradas","contributorId":145828,"corporation":false,"usgs":false,"family":"Soni Yatheendradas","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arsenault, Kristi","contributorId":145829,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","email":"","affiliations":[{"id":16248,"text":"Hydrologic Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":565407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Christa Peters-Lidard","contributorId":116524,"corporation":false,"usgs":true,"family":"Christa Peters-Lidard","affiliations":[],"preferred":false,"id":565408,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Verdin, James 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":145830,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":565409,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70157523,"text":"70157523 - 2015 - An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","interactions":[],"lastModifiedDate":"2017-07-21T14:50:38","indexId":"70157523","displayToPublicDate":"2015-02-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5004,"text":"Fundamental and Applied Limnology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems","docAbstract":"

In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.

","language":"English","publisher":"International Association of Theoretical and Applied Limnology","publisherLocation":"Stuttgart, Germany","doi":"10.1127/fal/2015/0611","usgsCitation":"Maloney, K.O., Talbert, C., Cole, J.C., Galbraith, H.S., Blakeslee, C.J., Hanson, L., and Holmquist-Johnson, C.L., 2015, An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems: Fundamental and Applied Limnology, v. 186, no. 1-2, p. 171-192, https://doi.org/10.1127/fal/2015/0611.","productDescription":"22 p.","startPage":"171","endPage":"192","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054083","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":309723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, 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Center","active":true,"usgs":true}],"preferred":true,"id":573435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Leanne hansonl@usgs.gov","contributorId":3231,"corporation":false,"usgs":true,"family":"Hanson","given":"Leanne","email":"hansonl@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":573437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holmquist-Johnson, Christopher L. h-johnsonc@usgs.gov","contributorId":922,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":573438,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155262,"text":"70155262 - 2015 - The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","interactions":[],"lastModifiedDate":"2017-01-18T10:06:49","indexId":"70155262","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter","docAbstract":"

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-14-00344.1","usgsCitation":"Hoell, A., Funk, C.C., and Barlow, M., 2015, The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter: Journal of Climate, v. 28, no. 4, p. 1511-1526, https://doi.org/10.1175/JCLI-D-14-00344.1.","productDescription":"16 p.","startPage":"1511","endPage":"1526","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472296,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-14-00344.1","text":"Publisher Index Page"},{"id":306490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-11","publicationStatus":"PW","scienceBaseUri":"57f7ef86e4b0bc0bec09f1a6","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145832,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","email":"","affiliations":[{"id":16249,"text":"UMASS Lowel","active":true,"usgs":false}],"preferred":false,"id":565419,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148103,"text":"70148103 - 2015 - An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus","interactions":[],"lastModifiedDate":"2015-05-21T11:01:58","indexId":"70148103","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus","docAbstract":"

The effectiveness of several non-lethal techniques as indicators of total lipid content in smallmouth bass Micropterus dolomieu, walleye Sander vitreus and channel catfish Ictalurus punctatus was investigated. The techniques included (1) the Fulton and relative condition factors, (2) relative mass, (3) plasma indicators of nutritional status (alkaline phosphatase, calcium, cholesterol, protein, triglycerides and glucose) and (4) readings from a hand-held, microwave energy meter. Although simple linear regression analysis showed that lipid content was significantly correlated with several predictor variables in each species, the r2 values for the relations ranged from 0·17 to 0·50 and no single approach was consistent for all species. Only one model, between energy-meter readings and lipid content in I. punctatus, had an r2 value (0·83) high enough to justify using it as a predictive tool. Results indicate that no single variable was an accurate and reliable indicator of whole body lipid content in these fishes, except the energy meter for I. punctatus.

","language":"English","publisher":"Fisheries Society of the British Isles","publisherLocation":"London","doi":"10.1111/jfb.12600","usgsCitation":"Mesa, M.G., and Rose, B.P., 2015, An assessment of morphometric indices, blood chemistry variables and an energy meter as indicators of the whole body lipid content in Micropterus dolomieu, Sander vitreus and Ictalurus punctatus: Journal of Fish Biology, v. 86, no. 2, p. 755-764, https://doi.org/10.1111/jfb.12600.","productDescription":"10 p.","startPage":"755","endPage":"764","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":300634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-26","publicationStatus":"PW","scienceBaseUri":"555f01b2e4b0a92fa7eb968f","contributors":{"authors":[{"text":"Mesa, Matthew G. mmesa@usgs.gov","contributorId":3423,"corporation":false,"usgs":true,"family":"Mesa","given":"Matthew","email":"mmesa@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Brien P. brose@usgs.gov","contributorId":3493,"corporation":false,"usgs":true,"family":"Rose","given":"Brien","email":"brose@usgs.gov","middleInitial":"P.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547401,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148672,"text":"70148672 - 2015 - Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","interactions":[],"lastModifiedDate":"2015-06-19T10:52:23","indexId":"70148672","displayToPublicDate":"2015-02-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach","docAbstract":"

The presence of endocrine-disrupting compounds (EDCs), particularly estrogenic compounds, in the environment has drawn public attention across the globe, yet a clear understanding of the extent and distribution of estrogenic EDCs in surface waters and their relationship to potential sources is lacking. The objective of the present study was to identify and examine the potential input of estrogenic EDC sources in North Carolina water bodies using a geographic information system (GIS) mapping and analysis approach. Existing data from state and federal agencies were used to create point and nonpoint source maps depicting the cumulative contribution of potential sources of estrogenic EDCs to North Carolina surface waters. Water was collected from 33 sites (12 associated with potential point sources, 12 associated with potential nonpoint sources, and 9 reference), to validate the predictive results of the GIS analysis. Estrogenicity (measured as 17β-estradiol equivalence) ranged from 0.06 ng/L to 56.9 ng/L. However, the majority of sites (88%) had water 17β-estradiol concentrations below 1 ng/L. Sites associated with point and nonpoint sources had significantly higher 17β-estradiol levels than reference sites. The results suggested that water 17β-estradiol was reflective of GIS predictions, confirming the relevance of landscape-level influences on water quality and validating the GIS approach to characterize such relationships.

","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1002/etc.2797","collaboration":"North Carolina Wildlife Resources Commission (NCWRC); North Carolina State University; US Geological Survey; US Fish and Wildlife Service; Wildlife Management Institute","usgsCitation":"Sackett, D.K., Pow, C.L., Rubino, M.J., Aday, D., Cope, W., Kullman, S.W., Rice, J., Kwak, T.J., and Law, L.M., 2015, Sources of endocrine-disrupting compounds in North Carolina waterways: a geographic information systems approach: Environmental Toxicology and Chemistry, v. 34, no. 2, p. 437-445, https://doi.org/10.1002/etc.2797.","productDescription":"9 p.","startPage":"437","endPage":"445","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055607","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"55853d5be4b023124e8f5b47","contributors":{"authors":[{"text":"Sackett, Dana K.","contributorId":141232,"corporation":false,"usgs":false,"family":"Sackett","given":"Dana","email":"","middleInitial":"K.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pow, Crystal Lee","contributorId":141233,"corporation":false,"usgs":false,"family":"Pow","given":"Crystal","email":"","middleInitial":"Lee","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":549009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubino, Matthew J. 0000-0003-0651-3053","orcid":"https://orcid.org/0000-0003-0651-3053","contributorId":141234,"corporation":false,"usgs":false,"family":"Rubino","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39327,"text":"North Carolina Cooperative Fish and Wildlife Research Unit, Department of Applied Ecology, North Carolina State Univ.","active":true,"usgs":false}],"preferred":false,"id":549010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aday, D.D.","contributorId":75356,"corporation":false,"usgs":true,"family":"Aday","given":"D.D.","email":"","affiliations":[],"preferred":false,"id":549011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":549012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kullman, Seth W.","contributorId":62516,"corporation":false,"usgs":true,"family":"Kullman","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":549013,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rice, J. A.","contributorId":101217,"corporation":false,"usgs":true,"family":"Rice","given":"J.","middleInitial":"A.","affiliations":[],"preferred":false,"id":549014,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":549015,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Law, LeRoy M.","contributorId":104603,"corporation":false,"usgs":true,"family":"Law","given":"LeRoy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":549016,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70164451,"text":"70164451 - 2015 - Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","interactions":[],"lastModifiedDate":"2017-07-21T14:54:16","indexId":"70164451","displayToPublicDate":"2015-02-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams","docAbstract":"

Fatty acids are integral components of periphyton and differ among algal taxa. We examined seasonal patterns in periphyton fatty acids in six minimally disturbed headwater streams in Pennsylvania’s Appalachian Mountains, USA. Environmental data and periphyton were collected across four seasons for fatty acid and algal taxa content. Non-metric multidimensional scaling ordination suggested significant seasonal differences in fatty acids; an ordination on algal composition revealed similar seasonal patterns, but with slightly weaker separation of summer and fall. Summer and fall fatty acid profiles were driven by temperature, overstory cover, and conductivity and winter profiles by measures of stream size. Ordination on algal composition suggested that summer and fall communities were driven by overstory and temperature, whereas winter communities were driven by velocity. The physiologically important fatty acid 18:3ω6 was highest in summer and fall. Winter samples had the highest 20:3ω3. Six saturated fatty acids differed among the seasons. Periphyton fatty acids profiles appeared to reflect benthic algal species composition. This suggests that periphyton fatty acid composition can be useful in characterizing basal food resources and stream water quality.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrobiologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Kluwer","publisherLocation":"Dordrecht","doi":"10.1007/s10750-014-2054-7","usgsCitation":"Honeyfield, D.C., and Maloney, K.O., 2015, Seasonal patterns in stream periphyton fatty acids and community benthic algal composition in six high quality headwater streams: Hydrobiologia, v. 744, no. 1, p. 35-47, https://doi.org/10.1007/s10750-014-2054-7.","productDescription":"13 p.","startPage":"35","endPage":"47","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051650","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":316597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Tioga","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.36469268798828,\n 41.77592047575288\n ],\n [\n -77.36452102661133,\n 41.784369074958214\n ],\n [\n -77.35937118530273,\n 41.79460830893809\n ],\n [\n -77.34460830688477,\n 41.803182408964865\n ],\n [\n -77.34752655029297,\n 41.81546568714986\n ],\n [\n -77.35696792602539,\n 41.82467660012918\n ],\n [\n -77.37258911132812,\n 41.83183972757714\n ],\n [\n -77.38443374633789,\n 41.83439779313833\n ],\n [\n -77.3990249633789,\n 41.837595231322986\n ],\n [\n -77.40966796875,\n 41.840792509764945\n ],\n [\n -77.43026733398438,\n 41.838362592717665\n ],\n [\n -77.43713378906249,\n 41.83887416186901\n ],\n [\n -77.44674682617188,\n 41.82825826404019\n ],\n [\n -77.44571685791016,\n 41.821478516604024\n ],\n [\n -77.45550155639648,\n 41.8262116234836\n ],\n [\n -77.4620246887207,\n 41.828897825796226\n ],\n [\n -77.47421264648438,\n 41.82403699620285\n ],\n [\n -77.48331069946289,\n 41.81687299570986\n ],\n [\n -77.49412536621094,\n 41.81930372856746\n ],\n [\n -77.5056266784668,\n 41.825060359418075\n ],\n [\n -77.52279281616211,\n 41.82608370627639\n ],\n [\n -77.54030227661133,\n 41.82275776918215\n ],\n [\n -77.54837036132812,\n 41.81828027334614\n ],\n [\n -77.5418472290039,\n 41.804462026999374\n ],\n [\n -77.52399444580078,\n 41.786929036776925\n ],\n [\n -77.51455307006836,\n 41.7806569487635\n ],\n [\n -77.48777389526366,\n 41.77796872322689\n ],\n [\n -77.47438430786133,\n 41.77118365292609\n ],\n [\n -77.46562957763672,\n 41.76606236987991\n ],\n [\n -77.44485855102539,\n 41.764653945369396\n ],\n [\n -77.4290657043457,\n 41.76555021908967\n ],\n [\n -77.41052627563477,\n 41.76503806421117\n ],\n [\n -77.39850997924805,\n 41.77169575874489\n ],\n [\n -77.38975524902344,\n 41.77336007442078\n ],\n [\n -77.37258911132812,\n 41.77028745790557\n ],\n [\n -77.36452102661133,\n 41.775408403663285\n ],\n [\n -77.36469268798828,\n 41.77592047575288\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"744","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-04","publicationStatus":"PW","scienceBaseUri":"56b5d659e4b0cc7999817399","contributors":{"authors":[{"text":"Honeyfield, Dale C. 0000-0003-3034-2047 honeyfie@usgs.gov","orcid":"https://orcid.org/0000-0003-3034-2047","contributorId":2774,"corporation":false,"usgs":true,"family":"Honeyfield","given":"Dale","email":"honeyfie@usgs.gov","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":597439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":597440,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156795,"text":"70156795 - 2015 - An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities","interactions":[],"lastModifiedDate":"2018-02-08T12:49:20","indexId":"70156795","displayToPublicDate":"2015-02-01T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities","docAbstract":"

An early to middle Pleistocene ostracode fauna was discovered in sediment core P1-93-AR-23 (P23, 76.95°N, 155.07°W) from 951 meter water depth from the Northwind Ridge, western Arctic Ocean. Piston core P23 yielded more than 30,000 specimens and a total of about 30 species. Several early to mid-Pleistocene species in the genera Krithe,Echinocythereis, Pterygocythereis, and Arcacythere are now extinct in the Arctic and show taxonomic affinities to North Atlantic Ocean species. Our results suggest that there was a major ostracode faunal turnover during the global climate transitions known as the Mid-Pleistocene Transition (MPT, ~ 1.2 to 0.7 Ma) and the Mid-Brunhes Event (MBE, ~ 400 ka) reflecting the development of perennial sea ice during interglacial periods and large ice shelves during glacial periods over the last 400,000 years.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.palaeo.2014.07.026","usgsCitation":"DeNinno, L.H., Cronin, T.M., Rodriquez-Lazaro, J., and Brenner, A.R., 2015, An early to mid-Pleistocene deep Arctic Ocean ostracode fauna with North Atlantic affinities: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 419, p. 90-99, https://doi.org/10.1016/j.palaeo.2014.07.026.","productDescription":"10 p.","startPage":"90","endPage":"99","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057946","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":307825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"419","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e81daae4b0dacf699e6650","chorus":{"doi":"10.1016/j.palaeo.2014.07.026","url":"http://dx.doi.org/10.1016/j.palaeo.2014.07.026","publisher":"Elsevier BV","authors":"DeNinno L.H., Cronin T.M., Rodriguez-Lazaro J., Brenner A.","journalName":"Palaeogeography, Palaeoclimatology, Palaeoecology","publicationDate":"2/2015","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"DeNinno, Lauren H. ldeninno@usgs.gov","contributorId":5312,"corporation":false,"usgs":true,"family":"DeNinno","given":"Lauren","email":"ldeninno@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriquez-Lazaro, J.","contributorId":147163,"corporation":false,"usgs":false,"family":"Rodriquez-Lazaro","given":"J.","email":"","affiliations":[{"id":16801,"text":"Universidad Pais Vasco","active":true,"usgs":false}],"preferred":false,"id":570574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenner, Alec R. abrenner@usgs.gov","contributorId":5315,"corporation":false,"usgs":true,"family":"Brenner","given":"Alec","email":"abrenner@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":570575,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141757,"text":"70141757 - 2015 - Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","interactions":[],"lastModifiedDate":"2018-09-04T16:26:28","indexId":"70141757","displayToPublicDate":"2015-02-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2809,"text":"Nanotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles","docAbstract":"

The release of Ag nanoparticles (AgNPs) into the aquatic environment is likely, but the influence of water chemistry on their impacts and fate remains unclear. Here, we characterize the bioavailability of Ag from AgNO3 and from AgNPs capped with polyvinylpyrrolidone (PVP AgNP) and thiolated polyethylene glycol (PEG AgNP) in the freshwater snail, Lymnaea stagnalis, after short waterborne exposures. Results showed that water hardness, AgNP capping agents, and metal speciation affected the uptake rate of Ag from AgNPs. Comparison of the results from organisms of similar weight showed that water hardness affected the uptake of Ag from AgNPs, but not that from AgNO3. Transformation (dissolution and aggregation) of the AgNPs was also influenced by water hardness and the capping agent. Bioavailability of Ag from AgNPs was, in turn, correlated to these physical changes. Water hardness increased the aggregation of AgNPs, especially for PEG AgNPs, reducing the bioavailability of Ag from PEG AgNPs to a greater degree than from PVP AgNPs. Higher dissolved Ag concentrations were measured for the PVP AgNPs (15%) compared to PEG AgNPs (3%) in moderately hard water, enhancing Ag bioavailability of the former. Multiple drivers of bioavailability yielded differences in Ag influx between very hard and deionized water where the uptake rate constants (kuw, l g-1 d-1 ± SE) varied from 3.1 ± 0.7 to 0.2 ± 0.01 for PEG AgNPs and from 2.3 ± 0.02 to 1.3 ± 0.01 for PVP AgNPs. Modeling bioavailability of Ag from NPs revealed that Ag influx into L. stagnalis comprised uptake from the NPs themselves and from newly dissolved Ag.

","language":"English","publisher":"Informa Healthcare","publisherLocation":"London","doi":"10.3109/17435390.2014.991772","usgsCitation":"Stoiber, T., Croteau, M.N., Romer, I., Tejamaya, M., Lead, J.R., and Luoma, S.N., 2015, Influence of hardness on the bioavailability of silver to a freshwater snail after waterborne exposure to silver nitrate and silver nanoparticles: Nanotoxicology, v. 9, no. 7, p. 918-927, https://doi.org/10.3109/17435390.2014.991772.","productDescription":"10 p.","startPage":"918","endPage":"927","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055265","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472297,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":298123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-10","publicationStatus":"PW","scienceBaseUri":"54edaebee4b02d776a6849ad","contributors":{"authors":[{"text":"Stoiber, Tasha L.","contributorId":91402,"corporation":false,"usgs":false,"family":"Stoiber","given":"Tasha L.","affiliations":[],"preferred":false,"id":541043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":541042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romer, Isabella","contributorId":139390,"corporation":false,"usgs":false,"family":"Romer","given":"Isabella","email":"","affiliations":[{"id":7157,"text":"University of Birmingham","active":true,"usgs":false}],"preferred":false,"id":541044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tejamaya, Mila","contributorId":93375,"corporation":false,"usgs":false,"family":"Tejamaya","given":"Mila","email":"","affiliations":[],"preferred":false,"id":541045,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lead, Jamie R.","contributorId":41331,"corporation":false,"usgs":false,"family":"Lead","given":"Jamie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":541046,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":541047,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70147363,"text":"70147363 - 2015 - Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton","interactions":[],"lastModifiedDate":"2015-05-05T10:06:26","indexId":"70147363","displayToPublicDate":"2015-02-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton","docAbstract":"

Smith and Heaton (2011) propose a model in which stress in the crust is fractal‐like and highly variable on a range of length scales, including short length‐scales of ~1 km. Smith and Heaton (2011) motivate the need for stress heterogeneity on short length‐scales by citing observations such as short length‐scale changes in stress directions inferred from borehole breakouts, short length‐scale changes in earthquake slip, and the success of numerical models that include short‐wavelength stress heterogeneity. The heterogeneous part of the stress field in their model is more than twice as large as the homogeneous part. The stress field in this model frequently reverses itself over short distances, as can be seen in figure14 a of Smith and Heaton (2011). The modeled stress field contains at least 10 areas of reversed shear stress direction over the length of a 100 km long profile, with the length of the reversed areas ranging from <1 to ~5 km.

\n

This model makes specific predictions about the orientations and heterogeneity of earthquake focal mechanisms. Smith and Heaton (2011) attempt to validate this heterogeneous stress model using observations of earthquake focal‐mechanism variability from Hardebeck (2006). They then demonstrate that the model predicts a bias in the orientations of earthquake focal mechanisms, which are biased away from the background stress and toward the stressing rate. They suggest the focal‐mechanism bias in this model invalidates the large body of work over the last several decades, that has inferred stress orientations from the inversion of earthquake focal mechanisms. The question of whether or not the Smith and Heaton (2011) model is applicable to the real Earth is therefore important not only for understanding spatial stress variability but also for evaluating the numerous studies that have inferred crustal stress orientations from earthquake focal mechanisms (e.g., as compiled by Heidbach et al., 2008).

","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120130127","usgsCitation":"Hardebeck, J.L., 2015, Comment on “Models of stochastic, spatially varying stress in the crust compatible with focal‐mechanism data, and how stress inversions can be biased toward the stress rate” by Deborah Elaine Smith and Thomas H. Heaton: Bulletin of the Seismological Society of America, v. 105, no. 1, p. 447-451, https://doi.org/10.1785/0120130127.","productDescription":"5 p.","startPage":"447","endPage":"451","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045509","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-13","publicationStatus":"PW","scienceBaseUri":"5549e9b4e4b064e4207ca432","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":545856,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147979,"text":"70147979 - 2015 - H7N9 influenza A virus in turkeys in Minnesota","interactions":[],"lastModifiedDate":"2015-05-11T09:35:58","indexId":"70147979","displayToPublicDate":"2015-02-01T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2301,"text":"Journal of General Virology","active":true,"publicationSubtype":{"id":10}},"title":"H7N9 influenza A virus in turkeys in Minnesota","docAbstract":"

Introductions of H7 Influenza A virus (IAV) from wild birds into poultry have been documented worldwide, resulting in varying degrees of morbidity and mortality. H7 IAV infection in domestic poultry has served as a source of human infection and disease. We report the detection of H7N9 subtype IAV in Minnesota turkey farms during 2009 and 2011. The full-genome was sequenced from eight isolates as well as the hemagglutinin (HA) and neuraminidase (NA) gene segments of H7 and N9 virus subtypes for 108 isolates from North American wild birds between 1986 and 2012. Through maximum likelihood and coalescent phylogenetic analyses, we identified the recent H7 and N9 IAV ancestors of the turkey-origin H7N9 IAV, estimated the time and geographic origin of the ancestral viruses, and determined the relatedness between the 2009 and the 2011 turkey-origin H7N9 IAV. Analyses supported that the 2009 and the 2011 viruses were distantly related genetically, suggesting that the two outbreaks arose from independent introduction events from wild birds. Our findings further support that the 2011 MN turkey-origin H7N9 virus was closely related to H7N9 IAV isolated in poultry in Nebraska during the same year. Although the precise origin of the wild-bird donor of the turkey-origin H7N9 IAV could not be determined, our findings suggest that, for both the NA and HA gene segments, the MN turkey-origin H7N9 viruses were related to viruses circulating in wild birds between 2006 and 2011 in the Mississippi flyway.

","language":"English","publisher":"Society for General Microbiology","publisherLocation":"London, England","doi":"10.1099/vir.0.067504-0","usgsCitation":"Lebarbenchon, C., Pedersen, J., Sreevatsan, S., Ramey, A.M., Dugan, V.G., Halpin, R., Ferro, P.A., Lupiani, B., Enomoto, S., Poulson, R.L., Smeltzer, M., Cardona, C.J., Tompkins, S., Wentworth, D., Stallknecht, D., and Brown, J., 2015, H7N9 influenza A virus in turkeys in Minnesota: Journal of General Virology, v. 96, no. 2, p. 269-276, https://doi.org/10.1099/vir.0.067504-0.","productDescription":"8 p.","startPage":"269","endPage":"276","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055807","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":472298,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4298677","text":"Publisher Index 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M.","contributorId":140672,"corporation":false,"usgs":false,"family":"Smeltzer","given":"M.","email":"","affiliations":[],"preferred":false,"id":546551,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cardona, Carol J.","contributorId":10536,"corporation":false,"usgs":true,"family":"Cardona","given":"Carol","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":546552,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tompkins, S.","contributorId":51123,"corporation":false,"usgs":true,"family":"Tompkins","given":"S.","email":"","affiliations":[],"preferred":false,"id":546553,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wentworth, D.E.","contributorId":23768,"corporation":false,"usgs":true,"family":"Wentworth","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":546554,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stallknecht, D.E.","contributorId":6660,"corporation":false,"usgs":true,"family":"Stallknecht","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":546555,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Brown, J.","contributorId":25486,"corporation":false,"usgs":true,"family":"Brown","given":"J.","affiliations":[],"preferred":false,"id":546556,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70146666,"text":"70146666 - 2015 - Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands","interactions":[],"lastModifiedDate":"2015-06-02T11:30:27","indexId":"70146666","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal 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We determined the best predictors of an index of amphibian biotic integrity calculated from 54 shrub and forested wetlands in Ohio, USA using a two-step sequential holdout validation procedure. We considered 13 variables as predictors: four metrics of wetland condition from the Ohio Rapid Assessment Method (ORAM), a wetland vegetation index of biotic integrity, and eight metrics from a landscape disturbance index. For all iterations, the best model included the single ORAM metric that assesses habitat alteration, substrate disturbance, and habitat development within a wetland. Our results align with results of similar studies that have associated high scores for wetland vegetation indices of biotic integrity with low habitat alteration and substrate disturbance within wetlands. Thus, implementing similar management practices (e.g., not removing downed woody debris, retaining natural morphological features, decreasing nutrient input from surrounding agricultural lands) could concurrently increase ecological integrity of both plant and amphibian communities in a wetland. Further, our results have the unexpected effect of making progress toward a more unifying theory of ecological indices.

","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-015-0638-2","usgsCitation":"Micacchion, M., Stapanian, M.A., and Adams, J.V., 2015, Site-scale disturbance and habitat development best predict an index of amphibian biotic integrity in Ohio shrub and forested wetlands: Wetlands, v. 35, no. 3, p. 509-519, https://doi.org/10.1007/s13157-015-0638-2.","productDescription":"11 p.","startPage":"509","endPage":"519","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053300","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":299809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.825439453125,\n 41.705728515237524\n ],\n [\n -84.83642578125,\n 39.07037913108751\n ],\n [\n -84.385986328125,\n 39.00211029922512\n ],\n [\n -84.19921875,\n 38.736946065676\n ],\n [\n -83.726806640625,\n 38.57393751557591\n ],\n [\n -83.232421875,\n 38.548165423046584\n ],\n [\n -82.891845703125,\n 38.685509760012\n ],\n [\n -82.584228515625,\n 38.36750215395045\n ],\n [\n -82.12280273437499,\n 38.522384090200845\n ],\n [\n -82.02392578125,\n 38.90813299596705\n ],\n [\n -81.9140625,\n 38.796908303484294\n ],\n [\n -81.474609375,\n 39.32579941789298\n ],\n [\n -81.38671875,\n 39.27478966170308\n ],\n [\n -80.804443359375,\n 39.605688178320804\n ],\n [\n -80.518798828125,\n 40.47202439692057\n ],\n [\n -80.518798828125,\n 42.00032514831621\n ],\n [\n -83.4521484375,\n 41.73852846935917\n ],\n [\n -84.825439453125,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-14","publicationStatus":"PW","scienceBaseUri":"553774b1e4b0b22a15808516","contributors":{"authors":[{"text":"Micacchion, Mick","contributorId":21511,"corporation":false,"usgs":true,"family":"Micacchion","given":"Mick","affiliations":[],"preferred":false,"id":545236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545235,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147980,"text":"70147980 - 2015 - Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","interactions":[],"lastModifiedDate":"2018-08-21T13:10:04","indexId":"70147980","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","title":"Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds","docAbstract":"

Migratory birds occupy geographically and ecologically disparate areas during their annual cycle with conditions on breeding and non-breeding grounds playing separate and important roles in population dynamics. We used data from nuclear microsatellite and mitochondrial DNA control region loci to assess the breeding and non-breeding spatial genetic structure of a transoceanic migrant shorebird, the bristle-thighed curlew. We found spatial variance in the distribution of allelic and haplotypic frequencies between the curlew's two breeding areas in Alaska but did not observe this spatial structure throughout its non-breeding range on low-lying tropical and subtropical islands in the Central Pacific (Oceania). This suggests that the two breeding populations do not spatially segregate during the non-breeding season. Lack of migratory connectivity is likely attributable to the species' behavior, as bristle-thighed curlews exhibit differential timing of migration and some individuals move among islands during non-breeding months. Given the detrimental impact of many past and current human activities on island ecosystems, admixture of breeding populations in Oceania may render the bristle-thighed curlew less vulnerable to perturbations there, as neither breeding population will be disproportionally affected by local habitat losses or by stochastic events. Furthermore, lack of migratory connectivity may enable bristle-thighed curlews to respond to changing island ecosystems by altering their non-breeding distribution. However, availability of suitable non-breeding habitat for curlews in Oceania is increasingly limited on both low-lying and high islands by habitat loss, sea level rise, and invasive mammalian predators that pose a threat to flightless and flight-compromised curlews during the molting period.

","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-014-0654-4","usgsCitation":"Sonsthagen, S.A., Tibbitts, T.L., Gill, R., Williams, I.S., and Talbot, S.L., 2015, Spatial genetic structure of bristle-thighed curlews (Numenius tahitiensis): Breeding area differentiation not reflected on the non-breeding grounds: Conservation Genetics, v. 16, no. 1, p. 223-233, https://doi.org/10.1007/s10592-014-0654-4.","productDescription":"11 p.","startPage":"223","endPage":"233","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055300","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438726,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WS8RB7","text":"USGS data release","linkHelpText":"Data from Bristle-Thighed Curlews at James Campbell National Wildlife Refuge, O'ahu, Hawaii, 2012-2014"},{"id":300264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-16","publicationStatus":"PW","scienceBaseUri":"5551d2bbe4b0a92fa7e93c0e","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":140455,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":546537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Ian S.","contributorId":77439,"corporation":false,"usgs":true,"family":"Williams","given":"Ian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":546539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":546540,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145827,"text":"70145827 - 2015 - Integrated survival analysis using an event-time approach in a Bayesian framework","interactions":[],"lastModifiedDate":"2015-04-13T09:31:55","indexId":"70145827","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrated survival analysis using an event-time approach in a Bayesian framework","docAbstract":"

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford, England","doi":"10.1002/ece3.1399","usgsCitation":"Walsh, D.P., Dreitz, V., and Heisey, D.M., 2015, Integrated survival analysis using an event-time approach in a Bayesian framework: Ecology and Evolution, v. 5, no. 3, p. 769-780, https://doi.org/10.1002/ece3.1399.","productDescription":"12 p.","startPage":"769","endPage":"780","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061696","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1399","text":"Publisher Index Page"},{"id":299601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-17","publicationStatus":"PW","scienceBaseUri":"552ce8b8e4b0b22a157f50b5","chorus":{"doi":"10.1002/ece3.1399","url":"http://dx.doi.org/10.1002/ece3.1399","publisher":"Wiley-Blackwell","authors":"Walsh Daniel P., Dreitz Victoria J., Heisey Dennis M.","journalName":"Ecology and Evolution","publicationDate":"1/17/2015","auditedOn":"3/17/2016"},"contributors":{"authors":[{"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":544448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dreitz, VJ","contributorId":140149,"corporation":false,"usgs":false,"family":"Dreitz","given":"VJ","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":544449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heisey, Dennis M. dheisey@usgs.gov","contributorId":2455,"corporation":false,"usgs":true,"family":"Heisey","given":"Dennis","email":"dheisey@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":544450,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70141763,"text":"70141763 - 2015 - Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","interactions":[],"lastModifiedDate":"2015-02-23T09:32:27","indexId":"70141763","displayToPublicDate":"2015-02-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California","docAbstract":"

Much remains to be understood about the evolutionary history and contemporary landscape genetics of unarmored threespine stickleback in southern California, where populations collectively referred to as Gasterosteus aculeatus williamsoni have severely declined over the past 70+ years and are now endangered. We used mitochondrial sequence and microsatellite data to assess the population genetics and phylogeography of unarmored populations sampled immediately downstream from the type locality of G. a. williamsoni in the upper Santa Clara River, and assessed their distinctiveness with respect to low-armor populations in the downstream sections of the river and the adjacent Ventura River. We also characterized the geographic limits of different plate morphs and evaluated the congruence of those boundaries with barriers to dispersal in both river systems and to neutral genetic variation. We show substantial population structuring within the upper reach of the Santa Clara River, but little partitioning between the lower Santa Clara and Ventura Rivers—we attribute these patterns to different ancestry between spatially subdivided populations within the same drainage, a predominance of downstream gene flow, and ability for coastal dispersal between the Santa Clara and Ventura Rivers. We also show that alleles from introduced low-plate stock have infiltrated a native population in at least one upper Santa Clara River tributary, causing this formerly unarmored population to become gradually low-plated over a 30 + year time period. Measures of genetic diversity, census surveys, and severe habitat disturbance all indicate that unarmored stickleback near the type locality are currently at high risk of extinction.

","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-014-0643-7","usgsCitation":"Richmond, J.Q., Jacobs, D.K., Backlin, A.R., Swift, C.C., Dellith, C., and Fisher, R.N., 2015, Ephemeral stream reaches preserve the evolutionary and distributional history of threespine stickleback in the Santa Clara and Ventura River watersheds of southern California: Conservation Genetics, v. 16, no. 1, p. 85-101, https://doi.org/10.1007/s10592-014-0643-7.","productDescription":"17 p.","startPage":"85","endPage":"101","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058303","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":298096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Clara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.02308654785156,\n 37.21392518793643\n ],\n [\n -122.02308654785156,\n 37.41107339721063\n ],\n [\n -121.85142517089844,\n 37.41107339721063\n ],\n [\n -121.85142517089844,\n 37.21392518793643\n ],\n [\n -122.02308654785156,\n 37.21392518793643\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-08","publicationStatus":"PW","scienceBaseUri":"54ec5d41e4b02d776a67daa7","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobs, David K.","contributorId":139394,"corporation":false,"usgs":false,"family":"Jacobs","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":541026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swift, Camm C.","contributorId":139395,"corporation":false,"usgs":false,"family":"Swift","given":"Camm","email":"","middleInitial":"C.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":541028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dellith, Chris","contributorId":139396,"corporation":false,"usgs":false,"family":"Dellith","given":"Chris","email":"","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":541029,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148079,"text":"70148079 - 2015 - An open-population hierarchical distance sampling model","interactions":[],"lastModifiedDate":"2015-05-19T09:05:34","indexId":"70148079","displayToPublicDate":"2015-02-01T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An open-population hierarchical distance sampling model","docAbstract":"

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

","language":"English","publisher":"Ecological Society of America","publisherLocation":"Brooklyn, NY","doi":"10.1890/14-1625.1","usgsCitation":"Sollmann, R., Gardner, B., Chandler, R.B., Royle, J.A., and Sillett, T.S., 2015, An open-population hierarchical distance sampling model: Ecology, v. 96, no. 2, p. 325-331, https://doi.org/10.1890/14-1625.1.","productDescription":"7 p.","startPage":"325","endPage":"331","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060570","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/14-1625.1","text":"Publisher Index Page"},{"id":300528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"555c5eb0e4b0a92fa7eacbf2","contributors":{"authors":[{"text":"Sollmann, Rachel","contributorId":11909,"corporation":false,"usgs":true,"family":"Sollmann","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":547190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":140853,"corporation":false,"usgs":true,"family":"Gardner","given":"Beth","email":"","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Richard B rchandler@usgs.gov","contributorId":140854,"corporation":false,"usgs":false,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B","affiliations":[{"id":13596,"text":"Univ. Georgia","active":true,"usgs":false}],"preferred":false,"id":547192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":547189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sillett, T Scott","contributorId":140855,"corporation":false,"usgs":false,"family":"Sillett","given":"T","email":"","middleInitial":"Scott","affiliations":[{"id":13597,"text":"Smithsonian Institude","active":true,"usgs":false}],"preferred":false,"id":547193,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147339,"text":"70147339 - 2015 - Advancing the science of microbial symbiosis to support invasive species management: a case study on Phragmites in the Great Lakes","interactions":[],"lastModifiedDate":"2022-01-03T17:36:27.313367","indexId":"70147339","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Advancing the science of microbial symbiosis to support invasive species management: a case study on Phragmites in the Great Lakes","title":"Advancing the science of microbial symbiosis to support invasive species management: a case study on Phragmites in the Great Lakes","docAbstract":"

A growing body of literature supports microbial symbiosis as a foundational principle for the competitive success of invasive plant species. Further exploration of the relationships between invasive species and their associated microbiomes, as well as the interactions with the microbiomes of native species, can lead to key new insights into invasive success and potentially new and effective control approaches. In this manuscript, we review microbial relationships with plants, outline steps necessary to develop invasive species control strategies that are based on those relationships, and use the invasive plant species Phragmites australis (common reed) as an example of how development of microbial-based control strategies can be enhanced using a collective impact approach. The proposed science agenda, developed by the Collaborative for Microbial Symbiosis andPhragmites Management, contains a foundation of sequential steps and mutually-reinforcing tasks to guide the development of microbial-based control strategies for Phragmites and other invasive species. Just as the science of plant-microbial symbiosis can be transferred for use in other invasive species, so too can the model of collective impact be applied to other avenues of research and management.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmicb.2015.00095","usgsCitation":"Kowalski, K., Bacon, C.W., Bickford, W.A., Braun, H.A., Clay, K., Leduc-Lapierre, M., Lillard, E., McCormick, M.K., Nelson, E., Torres, M., White, J.W., and Wilcox, D., 2015, Advancing the science of microbial symbiosis to support invasive species management: a case study on Phragmites in the Great Lakes: Frontiers in Microbiology, v. 6, 95, 14 p., https://doi.org/10.3389/fmicb.2015.00095.","productDescription":"95, 14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057771","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2015.00095","text":"Publisher Index Page"},{"id":299985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-19","publicationStatus":"PW","scienceBaseUri":"55435229e4b0a658d794149d","contributors":{"authors":[{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bacon, Charles W.","contributorId":62545,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":545809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":545810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braun, Heather A.","contributorId":61325,"corporation":false,"usgs":true,"family":"Braun","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":545811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clay, Keith","contributorId":140472,"corporation":false,"usgs":false,"family":"Clay","given":"Keith","email":"","affiliations":[{"id":12645,"text":"Indiana University - Northwest","active":true,"usgs":false}],"preferred":false,"id":545812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leduc-Lapierre, Michele","contributorId":140473,"corporation":false,"usgs":false,"family":"Leduc-Lapierre","given":"Michele","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":545813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lillard, Elizabeth","contributorId":140474,"corporation":false,"usgs":false,"family":"Lillard","given":"Elizabeth","email":"","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":545814,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCormick, Melissa K.","contributorId":140475,"corporation":false,"usgs":false,"family":"McCormick","given":"Melissa","email":"","middleInitial":"K.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":545815,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nelson, Eric","contributorId":140476,"corporation":false,"usgs":false,"family":"Nelson","given":"Eric","affiliations":[{"id":13511,"text":"Cornell Univesity","active":true,"usgs":false}],"preferred":false,"id":545816,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Torres, Monica","contributorId":140477,"corporation":false,"usgs":false,"family":"Torres","given":"Monica","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":545817,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"White, James W. C.","contributorId":8367,"corporation":false,"usgs":false,"family":"White","given":"James","email":"","middleInitial":"W. C.","affiliations":[],"preferred":false,"id":545818,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wilcox, Douglas A.","contributorId":9590,"corporation":false,"usgs":true,"family":"Wilcox","given":"Douglas A.","affiliations":[],"preferred":false,"id":545819,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ]}