The 1872 Owens Valley earthquake is the third largest known historical earthquake in California. Relatively sparse field data and a complex rupture trace, however, inhibited attempts to fully resolve the slip distribution and reconcile the total moment release. We present a new, comprehensive record of surface slip based on lidar and field investigation, documenting 162 new measurements of laterally and vertically displaced landforms for 1872 and prehistoric Owens Valley earthquakes. Our lidar analysis uses a newly developed analytical tool to measure fault slip based on cross-correlation of sublinear topographic features and to produce a uniquely shaped probability density function (PDF) for each measurement. Stacking PDFs along strike to form cumulative offset probability distribution plots (COPDs) highlights common values corresponding to single and multiple-event displacements. Lateral offsets for 1872 vary systematically from ∼1.0 to 6.0 m and average 3.3 ± 1.1 m (2σ). Vertical offsets are predominantly east-down between ∼0.1 and 2.4 m, with a mean of 0.8 ± 0.5 m. The average lateral-to-vertical ratio compiled at specific sites is ∼6:1. Summing displacements across subparallel, overlapping rupture traces implies a maximum of 7–11 m and net average of 4.4 ± 1.5 m, corresponding to a geologic Mw ∼7.5 for the 1872 event. We attribute progressively higher-offset lateral COPD peaks at 7.1 ± 2.0 m, 12.8 ± 1.5 m, and 16.6 ± 1.4 m to three earlier large surface ruptures. Evaluating cumulative displacements in context with previously dated landforms in Owens Valley suggests relatively modest rates of fault slip, averaging between ∼0.6 and 1.6 mm/yr (1σ) over the late Quaternary.
","language":"English","publisher":"Geological Society of America","doi":"10.1002/2015GC006033","usgsCitation":"Haddon, E., Amos, C., Zielke, O., Jayko, A.S., and Burgmann, R., 2016, Surface slip during large Owens Valley earthquakes: Geochemistry, Geophysics, Geosystems, v. 17, no. 6, p. 2239-2269, https://doi.org/10.1002/2015GC006033.","productDescription":"31 p.","startPage":"2239","endPage":"2269","ipdsId":"IP-069700","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":470889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gc006033","text":"Publisher Index Page"},{"id":342937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Owens Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.8,\n 35.7\n ],\n [\n -117.4,\n 35.7\n ],\n [\n -117.4,\n 37.7\n ],\n [\n -118.8,\n 37.7\n ],\n [\n -118.8,\n 35.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-22","publicationStatus":"PW","scienceBaseUri":"59536ea9e4b062508e3c7a81","contributors":{"authors":[{"text":"Haddon, E.K.","contributorId":193553,"corporation":false,"usgs":false,"family":"Haddon","given":"E.K.","email":"","affiliations":[],"preferred":false,"id":700808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amos, C.B.","contributorId":193554,"corporation":false,"usgs":false,"family":"Amos","given":"C.B.","email":"","affiliations":[],"preferred":false,"id":700809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zielke, O.","contributorId":166853,"corporation":false,"usgs":false,"family":"Zielke","given":"O.","affiliations":[{"id":24561,"text":"KAUST","active":true,"usgs":false}],"preferred":false,"id":700810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jayko, Angela S. 0000-0002-7378-0330 ajayko@usgs.gov","orcid":"https://orcid.org/0000-0002-7378-0330","contributorId":2531,"corporation":false,"usgs":true,"family":"Jayko","given":"Angela","email":"ajayko@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burgmann, R.","contributorId":193555,"corporation":false,"usgs":false,"family":"Burgmann","given":"R.","affiliations":[],"preferred":false,"id":700811,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173847,"text":"70173847 - 2016 - Endocrine disrupting activities of surface water associated with a West Virginia oil and gas industry wastewater disposal site","interactions":[],"lastModifiedDate":"2018-08-07T11:56:27","indexId":"70173847","displayToPublicDate":"2016-06-14T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Endocrine disrupting activities of surface water associated with a West Virginia oil and gas industry wastewater disposal site","docAbstract":"Currently, >95% of end disposal of hydraulic fracturing wastewater from unconventional oil and gas operations in the US occurs via injection wells. Key data gaps exist in understanding the potential impact of underground injection on surface water quality and environmental health. The goal of this study was to assess endocrine disrupting activity in surface water at a West Virginia injection well disposal site. Water samples were collected from a background site in the area and upstream, on, and downstream of the disposal facility. Samples were solid-phase extracted, and extracts assessed for agonist and antagonist hormonal activities for five hormone receptors in mammalian and yeast reporter gene assays. Compared to reference water extracts upstream and distal to the disposal well, samples collected adjacent and downstream exhibited considerably higher antagonist activity for the estrogen, androgen, progesterone, glucocorticoid and thyroid hormone receptors. In contrast, low levels of agonist activity were measured in upstream/distal sites, and were inhibited or absent at downstream sites with significant antagonism. Concurrent analyses by partner laboratories (published separately) describe the analytical and geochemical profiling of the water; elevated conductivity as well as high sodium, chloride, strontium, and barium concentrations indicate impacts due to handling of unconventional oil and gas wastewater. Notably, antagonist activities in downstream samples were at equivalent authentic standard concentrations known to disrupt reproduction and/or development in aquatic animals. Given the widespread use of injection wells for end-disposal of hydraulic fracturing wastewater, these data raise concerns for human and animal health nearby.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.113","usgsCitation":"Kassotis, C., Iwanowicz, L., Akob, D.M., Cozzarelli, I.M., Mumford, A.C., Orem, W.H., and Nagel, S., 2016, Endocrine disrupting activities of surface water associated with a West Virginia oil and gas industry wastewater disposal site: Science of the Total Environment, v. 557-558, p. 901-910, https://doi.org/10.1016/j.scitotenv.2016.03.113.","productDescription":"10 p.","startPage":"901","endPage":"910","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074246","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":323575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"557-558","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57611c9ce4b04f417c2c32f2","contributors":{"authors":[{"text":"Kassotis, Christopher D.","contributorId":26967,"corporation":false,"usgs":true,"family":"Kassotis","given":"Christopher D.","affiliations":[],"preferred":false,"id":638665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":638666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akob, Denise M. 0000-0003-1534-3025 dakob@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":4980,"corporation":false,"usgs":true,"family":"Akob","given":"Denise","email":"dakob@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":638664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":638667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":171791,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":638668,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":638669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagel, Susan C.","contributorId":56147,"corporation":false,"usgs":true,"family":"Nagel","given":"Susan C.","affiliations":[],"preferred":false,"id":638670,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171091,"text":"tm15C3 - 2016 - Recording and submitting specimen history data","interactions":[{"subject":{"id":70171091,"text":"tm15C3 - 2016 - Recording and submitting specimen history data","indexId":"tm15C3","publicationYear":"2016","noYear":false,"title":"Recording and submitting specimen history data"},"predicate":"IS_PART_OF","object":{"id":70118922,"text":"tm15 - 2015 - Field Manual of Wildlife Diseases","indexId":"tm15","publicationYear":"2015","noYear":false,"title":"Field Manual of Wildlife Diseases"},"id":1}],"isPartOf":{"id":70118922,"text":"tm15 - 2015 - Field Manual of Wildlife Diseases","indexId":"tm15","publicationYear":"2015","noYear":false,"title":"Field Manual of Wildlife Diseases"},"lastModifiedDate":"2018-07-05T11:02:44","indexId":"tm15C3","displayToPublicDate":"2016-06-14T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"15-C3","title":"Recording and submitting specimen history data","docAbstract":"In wildlife disease investigations, determining the history or background of a problem is the first significant step toward establishing a diagnosis and aiding agencies with management considerations. The diagnostic process and overall investigation is often greatly expedited by a chronological record accompanying specimens submitted for laboratory evaluation. Knowing where and when the outbreak is taking place, what the environmental conditions and species involved are, and clinical signs in sick animals, along with necropsy findings and diagnostic test results are important for understanding the natural history or epizootiology of disease outbreaks. It becomes increasingly difficult to retrospectively obtain all of the pertinent history as time passes. The most helpful information is that which is obtained at the time of the die-off event by perceptive field biologists and other observers. Significant events preceding morbidity and/or mortality also provide valuable information on which to base corrective actions. In this chapter, readers will find information regarding what type of information should be recorded, how it should be recorded and why it is relevant to a disease investigation. A thoughtful approach in providing as much information as possible surrounding the situation including about host species and the biotic and abiotic environment, greatly aids in determining the most likely causative agent(s).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Techniques in disease surveillance and investigation in Book 15: Field Manual of Wildlife Diseases","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm15C3","usgsCitation":"Bodenstein, B.L., 2016, Recording and submitting specimen history data, in Franson, J.C., Friend, M., Gibbs, S.E.J., and Wild, M.A., eds., Field manual of wildlife diseases: U.S. Geological Survey Techniques and Methods, book 15, chap. C3, 7 p., https://dx.doi.org/10.3133/tm15c3.","productDescription":"iii, 7 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074475","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":323305,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/publication/tm15","text":"Techniques and Methods 15 - Field Manual of Wildlife Diseases","description":"TM 15-C3"},{"id":323302,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/15/c03/coverthb.jpg"},{"id":323303,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/15/c03/tm15c3.pdf","text":"Report","size":"533 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 15-C3"}],"publicComments":"This report in Chapter 3 of Section C: Techniques in disease surveillance and investigation in Book 15: Field Manual of Wildlife Diseases","contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Rd.
Madison, WI 53711–6223
http://www.nwhc.usgs.gov/
Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Manual of Environmental Microbiology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"ASM Press","publisherLocation":"Washington, D.C.","doi":"10.1128/9781555818821.ch3.4.6","usgsCitation":"Nevers, M., Byappanahalli, M., Phanikumar, M.S., and Whitman, R.L., 2016, Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6, chap. 3.4.6 of Manual of Environmental Microbiology, p. 3.4.6-1-3.4.6-16, https://doi.org/10.1128/9781555818821.ch3.4.6.","productDescription":"16 p.","startPage":"3.4.6-1","endPage":"3.4.6-16","ipdsId":"IP-049156","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":340175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-01","publicationStatus":"PW","scienceBaseUri":"58ff0e9de4b006455f2d61bc","contributors":{"authors":[{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":573242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":573243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phanikumar, Mantha S.","contributorId":147924,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":692598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":573245,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171197,"text":"ofr20161089 - 2016 - Herpetological monitoring and assessment on the Trinity River, Trinity County, California—Final report","interactions":[],"lastModifiedDate":"2017-11-22T16:04:49","indexId":"ofr20161089","displayToPublicDate":"2016-06-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1089","title":"Herpetological monitoring and assessment on the Trinity River, Trinity County, California—Final report","docAbstract":"The primary goal of the Trinity River Restoration Program is to rehabilitate the fisheries on the dam-controlled Trinity River. However, maintaining and enhancing other wildlife populations through the restoration initiative is also a key objective. Foothill yellow-legged frogs (Rana boylii) and western pond turtles (Actinemys marmorata) have been identified as important herpetological species on which to focus monitoring efforts due to their status as California state-listed species of concern and potential listing on the U.S. Endangered Species List. We developed and implemented a monitoring strategy for these species specific to the Trinity River with the objectives of establishing baseline values for probabilities of site occupancy, colonization, and local extinction; identifying site characteristics that correlate with the probability of extinction; and estimating overall trends in abundance. Our 3-year study suggests that foothill yellow-legged frogs declined in the probability of site occupancy. Conversely, our results suggest that western pond turtles increased in both abundance and the probability of site occupancy. The short length of our study period makes it difficult to draw firm conclusions, but these results provide much-needed baseline data. Further monitoring and directed studies are required to assess how habitat changes and management decisions relate to the status and trend of these species over the long term.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161089","collaboration":"Prepared in cooperation with the Trinity River Restoration Program","usgsCitation":"Snover, M.L., and Adams, M.J., 2016, Herpetological monitoring and assessment on the Trinity River, Trinity County, California—Final report: U.S. Geological Survey Open-File Report 2016-1089, 93 p., https://dx.doi.org/10.3133/ofr20161089.","productDescription":"vi, 93 p.","numberOfPages":"103","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070527","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":323596,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1089/ofr20161089.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Forest and Rangeland Ecosystem Science Center
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777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The U.S. Geological Survey, in cooperation with the Tennessee Duck River Development Agency, monitored water quality at several locations in the upper Duck River watershed between October 2007 and September 2010. Discrete water samples collected at 24 sites in the watershed were analyzed for water quality, and Escherichia coli (E. coli) and enterococci concentrations. Additional analyses, including the determination of anthropogenic-organic compounds, bacterial concentration of resuspended sediment, and bacterial-source tracking, were performed at a subset of sites. Continuous monitoring of streamflow, turbidity, and specific conductance was conducted at seven sites; a subset of sites also was monitored for water temperature and dissolved oxygen concentration. Multiple-regression models were developed to predict instantaneous E. coli concentrations and loads at sites with continuous monitoring. This data collection effort, along with the E. coli models and predictions, support analyses of the relations among land use, bacteria source and transport, and basin hydrology in the upper Duck River watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1003","collaboration":"Prepared in cooperation with the Tennessee Duck River Development Agency","usgsCitation":"Murphy, Jennifer, Farmer, James, and Layton, Alice, 2016, Water-quality data and Escherichia coli predictions for selected karst catchments of the upper Duck River watershed in central Tennessee, 2007–10:\nU.S. Geological Survey Data Series 1003, 17 p., https://dx.doi.org/10.3133/ds1003.","productDescription":"Report: v, 17 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2007-10-01","ipdsId":"IP-059652","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":438613,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7445JKC","text":"USGS data release","linkHelpText":"Water-quality datasets and E. coli predictions for selected streams in the Upper Duck River Watershed, central Tennessee, 2007-2010"},{"id":323294,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1003/coverthb.jpg"},{"id":323295,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1003/ds1003.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":" Data Series 1003"},{"id":323304,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7445JKC","text":"USGS data release - Water-quality datasets and E. coli predictions for selected streams in the Upper Duck River Watershed, central Tennessee, 2007–10","description":"USGS Data Release"}],"country":"United States","state":"Tennessee","otherGeospatial":"Duck River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.66908264160156,\n 35.45395828344931\n ],\n [\n -86.39579772949219,\n 35.45395828344931\n ],\n [\n -86.39579772949219,\n 35.66566448946006\n ],\n [\n -86.66908264160156,\n 35.66566448946006\n ],\n [\n -86.66908264160156,\n 35.45395828344931\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Ste 100
Nashville, TN 37211
The chemical composition of formation water and associated gases from the lower Cretaceous Paluxy Formation was determined using four different sampling methods at a characterization well in the Citronelle Oil Field, Alabama, as part of the Southeast Regional Carbon Sequestration Partnership (SECARB) Phase III Anthropogenic Test, which is an integrated carbon capture and storage project. In this study, formation water and gas samples were obtained from well D-9-8 #2 at Citronelle using gas lift, electric submersible pump, U-tube, and a downhole vacuum sampler (VS) and subjected to both field and laboratory analyses. Field chemical analyses included electrical conductivity, dissolved sulfide concentration, alkalinity, and pH; laboratory analyses included major, minor and trace elements, dissolved carbon, volatile fatty acids, free and dissolved gas species. The formation water obtained from this well is a Na–Ca–Cl-type brine with a salinity of about 200,000 mg/L total dissolved solids. Differences were evident between sampling methodologies, particularly in pH, Fe and alkalinity. There was little gas in samples, and gas composition results were strongly influenced by sampling methods. The results of the comparison demonstrate the difficulty and importance of preserving volatile analytes in samples, with the VS and U-tube system performing most favorably in this aspect.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.06.001","usgsCitation":"Conaway, C.H., Thordsen, J., Manning, M.A., Cook, P.J., Trautz, R.C., Thomas, B., and Kharaka, Y.K., 2016, Comparison of geochemical data obtained using four brine sampling methods at the SECARB Phase III Anthropogenic Test CO2 injection site, Citronelle Oil Field, Alabama: International Journal of Coal Geology, v. 162, p. 85-95, https://doi.org/10.1016/j.coal.2016.06.001.","productDescription":"11 p.","startPage":"85","endPage":"95","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075978","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470899,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1327451","text":"Publisher Index Page"},{"id":323486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"162","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575fcb1de4b04f417c2b2669","contributors":{"authors":[{"text":"Conaway, Christopher H. 0000-0002-0991-033X cconwaya@usgs.gov","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":127598,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher","email":"cconwaya@usgs.gov","middleInitial":"H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thordsen, James J. jthordsn@usgs.gov","contributorId":3329,"corporation":false,"usgs":true,"family":"Thordsen","given":"James J.","email":"jthordsn@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manning, Michael A. mmanning@usgs.gov","contributorId":1994,"corporation":false,"usgs":true,"family":"Manning","given":"Michael","email":"mmanning@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Paul J.","contributorId":171753,"corporation":false,"usgs":false,"family":"Cook","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":26940,"text":"Lawrence Berkeley National Laboratories Earth Science Division, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":638531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trautz, Robert C.","contributorId":171754,"corporation":false,"usgs":false,"family":"Trautz","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":26941,"text":"Electric Power Research Institute, Palo Alto, CA","active":true,"usgs":false}],"preferred":false,"id":638532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Burt","contributorId":95454,"corporation":false,"usgs":true,"family":"Thomas","given":"Burt","affiliations":[],"preferred":false,"id":638533,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kharaka, Yousif K. 0000-0001-9861-8260 ykharaka@usgs.gov","orcid":"https://orcid.org/0000-0001-9861-8260","contributorId":1928,"corporation":false,"usgs":true,"family":"Kharaka","given":"Yousif","email":"ykharaka@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638534,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173820,"text":"70173820 - 2016 - Greenhouse gas fluxes of a shallow lake in south-central North Dakota, USA","interactions":[],"lastModifiedDate":"2019-12-14T06:56:24","indexId":"70173820","displayToPublicDate":"2016-06-13T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Greenhouse gas fluxes of a shallow lake in south-central North Dakota, USA","docAbstract":"Greenhouse gas (GHG) fluxes of aquatic ecosystems in the northern Great Plains of the U.S. represent a significant data gap. Consequently, a 3-year study was conducted in south-central North Dakota, USA, to provide an initial estimate of GHG fluxes from a large, shallow lake. Mean GHG fluxes were 0.02 g carbon dioxide (CO2) m−2 h−1, 0.0009 g methane (CH4) m−2 h−1, and 0.0005 mg nitrous oxide (N2O) m−2 h−1. Fluxes of CO2 and CH4 displayed temporal and spatial variability which is characteristic of aquatic ecosystems, while fluxes of N2O were consistently low throughout the study. Comparisons between results of this study and published values suggest that mean daily fluxes of CO2, CH4, and N2O fromLong Lakewere low, particularly when compared to the well-studied prairie pothole wetlands of the region. Similarly, cumulative seasonal CH4 fluxes, which ranged from 2.68–7.58 g CH4 m−2, were relatively low compared to other wetland systems of North America. The observed variability among aquatic ecosystems underscores the need for further research.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0782-3","usgsCitation":"Tangen, B., Finocchiaro, R., Gleason, R.A., and Dahl, C.F., 2016, Greenhouse gas fluxes of a shallow lake in south-central North Dakota, USA: Wetlands, v. 36, no. 4, p. 779-787, https://doi.org/10.1007/s13157-016-0782-3.","productDescription":"9 p.","startPage":"779","endPage":"787","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070255","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":323489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.711669921875,\n 46.475699386607516\n ],\n [\n -99.393310546875,\n 46.475699386607516\n ],\n [\n -99.393310546875,\n 47.03269459852135\n ],\n [\n -100.711669921875,\n 47.03269459852135\n ],\n [\n -100.711669921875,\n 46.475699386607516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-09","publicationStatus":"PW","scienceBaseUri":"575fcb1ee4b04f417c2b2671","chorus":{"doi":"10.1007/s13157-016-0782-3","url":"http://dx.doi.org/10.1007/s13157-016-0782-3","publisher":"Springer Nature","authors":"Tangen Brian A., Finocchiaro Raymond G., Gleason Robert A., Dahl Charles F.","journalName":"Wetlands","publicationDate":"6/9/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"6/9/2016"},"contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":638507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finocchiaro, Raymond 0000-0002-5514-8729 rfinocchiaro@usgs.gov","orcid":"https://orcid.org/0000-0002-5514-8729","contributorId":167278,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":638508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":638510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahl, Charles F. cdahl@usgs.gov","contributorId":4052,"corporation":false,"usgs":true,"family":"Dahl","given":"Charles","email":"cdahl@usgs.gov","middleInitial":"F.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":638509,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173834,"text":"70173834 - 2016 - Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis, in the Mojave Desert, USA","interactions":[],"lastModifiedDate":"2016-07-18T21:30:55","indexId":"70173834","displayToPublicDate":"2016-06-13T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis, in the Mojave Desert, USA","docAbstract":"Predicting changes in species distributions under a changing climate is becoming widespread with the use of species distribution models (SDMs). The resulting predictions of future potential habitat can be cast in light of planned land use changes, such as urban expansion and energy development to identify areas with potential conflict. However, SDMs rarely incorporate an understanding of dispersal capacity, and therefore assume unlimited dispersal in potential range shifts under uncertain climate futures. We use SDMs to predict future distributions of the Mojave ground squirrel, Xerospermophilus mohavensis Merriam, and incorporate partial dispersal models informed by field data on juvenile dispersal to assess projected impact of climate change and energy development on future distributions of X. mohavensis. Our models predict loss of extant habitat, but also concurrent gains of new habitat under two scenarios of future climate change. Under the B1 emissions scenario- a storyline describing a convergent world with emphasis on curbing greenhouse gas emissions- our models predicted losses of up to 64% of extant habitat by 2080, while under the increased greenhouse gas emissions of the A2 scenario, we suggest losses of 56%. New potential habitat may become available to X. mohavensis, thereby offsetting as much as 6330 km2 (50%) of the current habitat lost. Habitat lost due to planned energy development was marginal compared to habitat lost from changing climates, but disproportionately affected current habitat. Future areas of overlap in potential habitat between the two climate change scenarios are identified and discussed in context of proposed energy development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2016.05.033","usgsCitation":"Inman, R.D., Esque, T., Nussear, K.E., Leitner, P., Matocq, M.D., Weisberg, P.J., and Dilts, T.E., 2016, Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis, in the Mojave Desert, USA: Biological Conservation, v. 200, p. 112-121, https://doi.org/10.1016/j.biocon.2016.05.033.","productDescription":"10 p.","startPage":"112","endPage":"121","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071079","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":323498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119,\n 34\n ],\n [\n -119,\n 38\n ],\n [\n -116,\n 38\n ],\n [\n -116,\n 34\n ],\n [\n -119,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"200","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575fcb1ee4b04f417c2b2673","contributors":{"authors":[{"text":"Inman, Richard D. rdinman@usgs.gov","contributorId":3316,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":638567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":168763,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":638566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":638568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leitner, Philip","contributorId":31319,"corporation":false,"usgs":true,"family":"Leitner","given":"Philip","email":"","affiliations":[],"preferred":false,"id":638569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matocq, Marjorie D.","contributorId":25482,"corporation":false,"usgs":true,"family":"Matocq","given":"Marjorie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":638570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weisberg, Peter J.","contributorId":33631,"corporation":false,"usgs":true,"family":"Weisberg","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638571,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dilts, Thomas E.","contributorId":36833,"corporation":false,"usgs":true,"family":"Dilts","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":638572,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173559,"text":"70173559 - 2016 - Anthropogenic disturbance and environmental associations with fish assemblage structure in two nonwadeable rivers","interactions":[],"lastModifiedDate":"2019-12-14T06:55:00","indexId":"70173559","displayToPublicDate":"2016-06-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Anthropogenic disturbance and environmental associations with fish assemblage structure in two nonwadeable rivers","docAbstract":"Nonwadeable rivers are unique ecosystems that support high levels of aquatic biodiversity, yet they have been greatly altered by human activities. Although riverine fish assemblages have been studied in the past, we still have an incomplete understanding of how fish assemblages respond to both natural and anthropogenic influences in large rivers. The purpose of this study was to evaluate associations between fish assemblage structure and reach-scale habitat, dam, and watershed land use characteristics. In the summers of 2011 and 2012, comprehensive fish and environmental data were collected from 33 reaches in the Iowa and Cedar rivers of eastern-central Iowa. Canonical correspondence analysis (CCA) was used to evaluate environmental relationships with species relative abundance, functional trait abundance (e.g. catch rate of tolerant species), and functional trait composition (e.g. percentage of tolerant species). On the basis of partial CCAs, reach-scale habitat, dam characteristics, and watershed land use features explained 25.0–81.1%, 6.2–25.1%, and 5.8–47.2% of fish assemblage variation, respectively. Although reach-scale, dam, and land use factors contributed to overall assemblage structure, the majority of fish assemblage variation was constrained by reach-scale habitat factors. Specifically, mean annual discharge was consistently selected in nine of the 11 CCA models and accounted for the majority of explained fish assemblage variance by reach-scale habitat. This study provides important insight on the influence of anthropogenic disturbances across multiple spatial scales on fish assemblages in large river systems.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/rra.2844","usgsCitation":"Parks, T.P., Quist, M.C., and Pierce, C., 2016, Anthropogenic disturbance and environmental associations with fish assemblage structure in two nonwadeable rivers: River Research and Applications, v. 32, no. 1, p. 66-84, https://doi.org/10.1002/rra.2844.","productDescription":"19 p.","startPage":"66","endPage":"84","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043810","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470901,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/97","text":"External Repository"},{"id":323527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Cedar River, Iowa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.758056640625,\n 41.566141964768384\n ],\n [\n -93.251953125,\n 43.866218006556394\n ],\n [\n -93.779296875,\n 43.691707903073805\n ],\n [\n -92.74658203125,\n 42.47209690919285\n ],\n [\n -91.395263671875,\n 41.376808565702355\n ],\n [\n -91.07666015625,\n 41.31082388091818\n ],\n [\n -90.758056640625,\n 41.566141964768384\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"575fcb1be4b04f417c2b2665","contributors":{"authors":[{"text":"Parks, T. P.","contributorId":171776,"corporation":false,"usgs":false,"family":"Parks","given":"T.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":638611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, C.L. 0000-0001-5088-5431","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":93606,"corporation":false,"usgs":true,"family":"Pierce","given":"C.L.","affiliations":[],"preferred":false,"id":638612,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70164457,"text":"fs20153083 - 2016 - Water resources of Washington Parish, Louisiana","interactions":[],"lastModifiedDate":"2016-06-13T16:14:02","indexId":"fs20153083","displayToPublicDate":"2016-06-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3083","title":"Water resources of Washington Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Washington Parish, Louisiana, is critical for proper water-resource management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
\nIn 2010, about 34.55 million gallons per day (Mgal/d) of water were withdrawn in Washington Parish, including about 28.10 Mgal/d from groundwater sources and 6.44 Mgal/d from surface-water sources1 (table 1). Withdrawals for industrial use accounted for about 52 percent (17.80 Mgal/d) of the total water withdrawn (table 2). Other categories of use included public supply, rural domestic, irrigation, and livestock. Water-use data collected at 5-year intervals from 1960 to 2010 (fig. 2) indicated that water withdrawals peaked in 1975 at about 51.9 Mgal/d.
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In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath bathymetry data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Monterey Canyon and Vicinity map area lies within Monterey Bay in central California. Monterey Bay is one of the largest embayments along the west coast of the United States, spanning 36 km from its northern to southern tips (in Santa Cruz and Monterey, respectively) and 20 km along its central axis. Not only does it contain one of the broadest sections of continental shelf along California’s coast, it also contains Monterey Canyon, one of the largest and deepest submarine canyons in the world. Note that the California’s State Waters limit extends farther offshore between Santa Cruz and Monterey so that it encompasses all of Monterey Bay.
The coastal area within the map area is lightly populated. The community of Moss Landing (population, 204) hosts the largest commercial fishing fleet in Monterey Bay in its harbor. The map area also includes parts of the cities of Marina (population, about 20,000) and Castroville (population, about 6,500). Fertile lowlands of the Salinas River and Pajaro River valleys largely occupy the inland part of the map area, and land use is primarily agricultural.
The offshore part of the map area lies completely within the Monterey Bay National Marine Sanctuary. The map area also includes Portuguese Ledge and Soquel Canyon State Marine Conservation Areas. Designated conservation and (or) recreation areas in the onshore part of the map area include Salinas River National Wildlife Refuge, Elkhorn Slough State Marine Conservation Area, Elkhorn Slough State Marine Reserve, Moss Landing Wildlife Area, Zmudowski and Salinas River State Beaches, and Marina Dunes Preserve.
Monterey Bay, a geologically complex area within a tectonically active continental margin, lies between two major, converging strike-slip faults. The northwest-striking San Andreas Fault lies about 34 km east of Monterey Bay; this section of the fault ruptured in both the 1989 M6.9 Loma Prieta earthquake and the 1906 M7.8 great California earthquake. The northwest-striking San Gregorio Fault crosses Monterey Canyon west of Monterey Bay. Between these two regional faults, strain is accommodated by the northwest-striking Monterey Bay Fault Zone. Deformation associated with these major regional faults and related structures has resulted in uplift of the Santa Cruz Mountains, as well as the granitic highlands of the Monterey peninsula.
Monterey Canyon begins in the nearshore area directly offshore of Moss Landing and Elkhorn Slough, and it can be traced for more than 400 km seaward, out to water depths of more than 4,000 m. Within the map area, the canyon can be traced for about 42 km to a water depth of about 1,520 m. The head of the canyon consists of three branches that begin about 150 m offshore of Moss Landing Harbor. At 500 m offshore, the canyon is already 70 m deep and 750 m wide. Large sand waves, which have heights from 1 to 3 m and wavelengths of about 50 m, are present along the channel axis in the upper 4 km of the canyon.
Soquel Canyon is the most prominent tributary of Monterey Canyon within the map area. The head of Soquel Canyon is isolated from coastal watersheds and, thus, is considered inactive as a conduit for coarse sediment transport.
North and south of Monterey and Soquel Canyons, the relatively flat continental shelf contains only a few rocky outcrop exposures. Bedrock is covered largely by sediment derived from the Salinas and Pajaro Rivers. North of Monterey Canyon, the broad and flat continental shelf dips gently seaward, to water depths of about 95 m. To the south, the shelf also dips slightly, to water depths of as much as 150 m along the canyon edge.
In the map area, Monterey Canyon splits the Santa Cruz littoral cell (north of the canyon) and the southern Monterey littoral cell (south of the canyon). It is estimated that about 400,000 m3/yr of sand on average enters Monterey Canyon from both of these littoral cells.
In the Santa Cruz littoral cell, sand generally travels east and south. Sand is supplied through sea cliff erosion, as well as from the San Lorenzo River, the Pajaro River, and several other smaller coastal watersheds. About 152,911 m3/yr of sand is dredged from the entrance channel of the Santa Cruz Small Craft Harbor north of the map area and then placed on beaches to the east (downdrift) of it. This sand feeds the beaches in the southeastern reach of the Santa Cruz littoral cell and (or) is eventually trapped and lost by Monterey Canyon.
The southern Monterey Bay littoral cell in the map area consists of two subcells. From the head of Monterey Canyon to the Salinas River, littoral drift is dominantly to the north; sand entering the ocean from the Salinas River either is deposited offshore or travels north in the littoral zone, nourishing the beaches until it is transported down Monterey Canyon. From south of the Salinas River to the southern extent of the map area, coastal sediment is moved mainly to the south; dune erosion is the only significant source of sand in this subcell.
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Cochran, eds.), 2016, California State Waters Map Series — Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161072.","productDescription":"Pamphlet: iv, 48 p.; 10 Sheets: 72.75 x 36.00 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059488","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438614,"rank":22,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XD0ZQ4","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Monterey Canyon and Vicinity, California"},{"id":321805,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161025","text":"Open-File Report 2016–1025","linkHelpText":"California State Waters Map Series—Offshore of Aptos, California, by Guy R. 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Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-06-10","noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"575bd6a0e4b04f417c275edb","contributors":{"editors":[{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630600,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science 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Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dieter, Bryan E.","contributorId":21859,"corporation":false,"usgs":true,"family":"Dieter","given":"Bryan E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Golden, Nadine E. 0000-0001-6007-6486 ngolden@usgs.gov","orcid":"https://orcid.org/0000-0001-6007-6486","contributorId":138974,"corporation":false,"usgs":true,"family":"Golden","given":"Nadine","email":"ngolden@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hartwell, Stephen R. 0000-0002-3522-7526 shartwell@usgs.gov","orcid":"https://orcid.org/0000-0002-3522-7526","contributorId":4995,"corporation":false,"usgs":true,"family":"Hartwell","given":"Stephen","email":"shartwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630577,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cochrane, Guy R. 0000-0002-8094-4583 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dfinlayson@usgs.gov","contributorId":1381,"corporation":false,"usgs":true,"family":"Finlayson","given":"David","email":"dfinlayson@usgs.gov","middleInitial":"P.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630580,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kvitek, Rikk G.","contributorId":44099,"corporation":false,"usgs":true,"family":"Kvitek","given":"Rikk","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":630581,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":630582,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Greene, H. Gary","contributorId":38958,"corporation":false,"usgs":true,"family":"Greene","given":"H. Gary","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630583,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Davenport, Clifton W.","contributorId":140374,"corporation":false,"usgs":false,"family":"Davenport","given":"Clifton W.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":630584,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Endris, Charles A.","contributorId":87875,"corporation":false,"usgs":true,"family":"Endris","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":630585,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Krigsman, Lisa M.","contributorId":43642,"corporation":false,"usgs":true,"family":"Krigsman","given":"Lisa M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":630586,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70173766,"text":"ofr20161095 - 2016 - Jaguar surveying and monitoring in the United States","interactions":[],"lastModifiedDate":"2016-11-08T16:41:35","indexId":"ofr20161095","displayToPublicDate":"2016-06-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1095","title":"Jaguar surveying and monitoring in the United States","docAbstract":"
Because of the jaguar’s (Panthera onca) endangered status under the Endangered Species Act (ESA) of 1973 throughout its range (from Arizona in the north to Argentina in the south), jaguar individuals and populations are monitored to varying degrees throughout their range. Knowledge gained from monitoring jaguars is helpful for wildlife managers who are responsible for conserving this species. The University of Arizona (UA) has conducted a multiyear surveying and monitoring effort for jaguars and ocelots in southern Arizona and New Mexico. The purpose of this work was to establish an effective surveying and monitoring system for jaguars along the United States-Mexico border. Surveying and monitoring in this study focused on the United States side of the border, but the methods could also be used in Mexico. The intent was to develop and implement a surveying and monitoring system that would provide the greatest probability of recording jaguar presence in, and passage through, the border area.
\nThis project established and implemented a noninvasive system for detecting and monitoring jaguars. The study area incorporates most of the mountainous areas north of the United States-Mexico international border and south of Interstate 10, from the Baboquivari Mountains in Arizona to the Animas Mountains in New Mexico. We used two primary methods to detect exact jaguar locations: paired motion-sensor trail cameras, and genetic testing of large carnivore scat collected in the field. We emphasize that this project used entirely noninvasive methods and no jaguars were captured, radiocollared, baited, or harassed in any way. Scat sample collection occurred during the entire field part of the study, but was intensified with the use of a trained scat detection dog following the first jaguar photo detection event (photo detection event was October 2012, scat detection dog began working January 2013). We also collected weather, vegetation, and geographic information system (GIS) data to analyze in conjunction with photo and video data. The results of this study are intended to aid and inform future management and conservation practices for jaguars and ocelots in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161095","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Culver, Melanie, 2016, Jaguar surveying and monitoring in the United States (ver. 1.1, November 2016): U.S. Geological Survey Open-File Report 2016–1095, 228 p., https://dx.doi.org/10.3133/ofr20161095.","productDescription":"228 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075400","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1095/ofr20161095.pdf","text":"Report","size":"18.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1095"},{"id":323457,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1095/coverthb.jpg"},{"id":330879,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1095/versionHist.txt","size":"708 bytes","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1095 Version History"}],"country":"United States","state":"Arizona, California, New Mexico, Texas","otherGeospatial":"United States - Mexico Border","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3779296875,\n 33.50475906922606\n ],\n [\n -104.9853515625,\n 32.32427558887655\n ],\n [\n -97.3388671875,\n 27.644606381943326\n ],\n [\n -97.3828125,\n 24.806681353851964\n ],\n [\n -102.26074218749999,\n 27.955591004642553\n ],\n [\n -106.74316406249999,\n 30.29701788337205\n ],\n [\n -117.158203125,\n 31.203404950917395\n ],\n [\n -117.3779296875,\n 33.50475906922606\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/
The U.S. Geological Survey conducted a bathymetric survey in Little Holland Tract, a flooded agricultural tract, in the northern Sacramento-San Joaquin Delta (the “Delta”) during the summer of 2015. The new bathymetric data were combined with existing data to generate a digital elevation model (DEM) at 1-meter resolution. Little Holland Tract (LHT) was historically diked off for agricultural uses and has been tidally inundated since an accidental levee breach in 1983. Shallow tidal regions such as LHT have the potential to improve habitat quality in the Delta. The DEM of LHT was developed to support ongoing studies of habitat quality in the area and to provide a baseline for evaluating future geomorphic change. The new data comprise 138,407 linear meters of real-time-kinematic (RTK) Global Positioning System (GPS) elevation data, including both bathymetric data collected from personal watercraft and topographic elevations collected on foot at low tide. A benchmark (LHT15_b1) was established for geodetic control of the survey. Data quality was evaluated both by comparing results among surveying platforms, which showed systematic offsets of 1.6 centimeters (cm) or less, and by error propagation, which yielded a mean vertical uncertainty of 6.7 cm. Based on the DEM and time-series measurements of water depth, the mean tidal prism of LHT was determined to be 2,826,000 cubic meters. The bathymetric data and DEM are available at http://dx.doi.org/10.5066/F7RX9954.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161093","usgsCitation":"Snyder, A.G., Lacy, J.R., Stevens, A.W., and Carlson, E.M., 2016, Bathymetric survey and digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California: U.S. Geological Survey Open-File Report 2016‒1093, 14 p., https://dx.doi.org/10.3133/ofr20161093. ","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071752","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":323417,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1093/ofr20161093.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1093"},{"id":323416,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1093/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.69349670410158,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.34556060133404\n ],\n [\n -121.64148330688475,\n 38.27632714009116\n ],\n [\n -121.69349670410158,\n 38.27632714009116\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
Many anuran monitoring programs now include autonomous recording units (ARUs). These devices collect audio data for extended periods of time with little maintenance and at sites where traditional call surveys might be difficult. Additionally, computer software programs have grown increasingly accurate at automatically identifying the calls of species. However, increased automation may cause increased error. We collected 435 min of audio data with 2 types of ARUs at 10 wetland sites in Vermont and New York, USA, from 1 May to 1 July 2010. For each minute, we determined presence or absence of 4 anuran species (Hyla versicolor, Pseudacris crucifer, Anaxyrus americanus, and Lithobates clamitans) using 1) traditional human identification versus 2) computer-mediated identification with software package, Song Scope® (Wildlife Acoustics, Concord, MA). Detections were compared with a data set consisting of verified calls in order to quantify false positive, false negative, true positive, and true negative rates. Multinomial logistic regression analysis revealed a strong (P < 0.001) 3-way interaction between the ARU recorder type, identification method, and focal species, as well as a trend in the main effect of rain (P = 0.059). Overall, human surveyors had the lowest total error rate (<2%) compared with 18–31% total errors with automated methods. Total error rates varied by species, ranging from 4% for A. americanus to 26% for L. clamitans. The presence of rain may reduce false negative rates. For survey minutes where anurans were known to be calling, the odds of a false negative were increased when fewer individuals of the same species were calling.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.619","usgsCitation":"Brauer, C., Donovan, T., Mickey, R.M., Katz, J., and Mitchell, B.R., 2016, A comparison of acoustic montoring methods for common anurans of the northeastern United States: Wildlife Society Bulletin, v. 40, no. 1, p. 140-149, https://doi.org/10.1002/wsb.619.","productDescription":"10 p.","startPage":"140","endPage":"149","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052906","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500057,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/00b50ba27b334e528321781e925d1f6d","text":"External Repository"},{"id":323389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-06","publicationStatus":"PW","scienceBaseUri":"575a8521e4b04f417c271089","contributors":{"authors":[{"text":"Brauer, Corinne","contributorId":66587,"corporation":false,"usgs":true,"family":"Brauer","given":"Corinne","email":"","affiliations":[],"preferred":false,"id":638243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese tdonovan@usgs.gov","contributorId":171599,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mickey, Ruth M.","contributorId":171666,"corporation":false,"usgs":false,"family":"Mickey","given":"Ruth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katz, Jonathan","contributorId":8370,"corporation":false,"usgs":true,"family":"Katz","given":"Jonathan","affiliations":[],"preferred":false,"id":638245,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mitchell, Brian R.","contributorId":14683,"corporation":false,"usgs":true,"family":"Mitchell","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":638246,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160537,"text":"sir20155157 - 2016 - Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010","interactions":[],"lastModifiedDate":"2016-06-09T12:48:12","indexId":"sir20155157","displayToPublicDate":"2016-06-09T10:45:00","publicationYear":"2016","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":"2015-5157","title":"Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010","docAbstract":"The ability to characterize baseline streamflow conditions, compare them with current conditions, and assess effects of human activities on streamflow is fundamental to water-management programs addressing water allocation, human-health issues, recreation needs, and establishment of ecological flow criteria. The U.S. Geological Survey, through the National Water Census, has developed the Delaware River Basin Streamflow Estimator Tool (DRB-SET) to estimate baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) and altered streamflow at a daily time step for ungaged stream locations in the Delaware River Basin for water years 1960–2010. Daily mean baseline streamflow is estimated by using the QPPQ method to equate streamflow expressed as a percentile from the flow-duration curve (FDC) for a particular day at an ungaged stream location with the percentile from a FDC for the same day at a hydrologically similar gaged location where streamflow is measured. Parameter-based regression equations were developed for 22 exceedance probabilities from the FDC for ungaged stream locations in the Delaware River Basin. Water use data from 2010 is used to adjust the baseline daily mean streamflow generated from the QPPQ method at ungaged stream locations in the Delaware River Basin to reflect current, or altered, conditions. To evaluate the effectiveness of the overall QPPQ method contained within DRB-SET, a comparison of observed and estimated daily mean streamflows was performed for 109 reference streamgages in and near the Delaware River Basin. The Nash-Sutcliffe efficiency (NSE) values were computed as a measure of goodness of fit. The NSE values (using log10 streamflow values) ranged from 0.22 to 0.98 (median of 0.90) for 45 streamgages in the Upper Delaware River Basin and from -0.37 to 0.98 (median of 0.79) for 41 streamgages in the Lower Delaware River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155157","collaboration":"National Water Census","usgsCitation":"Stuckey, M.H., 2016, Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010: U.S. Geological Survey Scientific Investigations Report 2015–5157, 42 p., https://dx.doi.org/10.3133/sir20155157.","productDescription":"v, 42 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066276","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":322017,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151192","text":"User’s Guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET)","description":"SIR 2015-5157"},{"id":321421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5157/coverthb.jpg"},{"id":321422,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5157/sir20155157.pdf","text":"Report","size":"6.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5157"}],"country":"United States","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.4815673828125,\n 39.70296052957233\n ],\n [\n -74.498291015625,\n 39.8465036024177\n ],\n [\n -74.4927978515625,\n 40.26695230509781\n ],\n [\n -74.970703125,\n 40.75974059207392\n ],\n [\n -74.6685791015625,\n 40.979898069620155\n ],\n [\n -74.5806884765625,\n 41.335575973123895\n ],\n [\n -74.11376953125,\n 42.13082130188811\n ],\n [\n -74.9432373046875,\n 42.44372793752476\n ],\n [\n -75.574951171875,\n 42.00848901572399\n ],\n [\n -75.8880615234375,\n 41.244772343082104\n ],\n [\n -76.343994140625,\n 40.329795743702064\n ],\n [\n -76.04736328125,\n 39.73253798438173\n ],\n [\n -75.4815673828125,\n 39.70296052957233\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coordinator—National Water Census
U.S. Geological Survey
1770 Corporate Drive
Suite 500
Norcross, GA 30093
Or visit the National Water Census Web site at:
http://water.usgs.gov/watercensus
Freshwater inflow characteristics define estuarine functioning by delivering nutrients, sediments, and freshwater, which affect biological resources and ultimately system production. Using 20 years of water quality, weather, and oyster growth and mortality data from Breton Sound Estuary (BSE), Louisiana, we examined the relationship of riverine, weather, and tidal influence on estuarine salinity, and the relationship of salinity to oyster growth and mortality. Mississippi River discharge was found to be the most important factor determining salinity patterns over oyster grounds within lower portions of BSE, with increased river flow associated with lowered salinities, while easterly winds associated with increased salinity were less influential. These patterns were consistent throughout the year. Salinity and temperature (season) were found to critically control oyster growth and mortality, suggesting that seasonal changes to river discharge affecting water quality over the oyster grounds have profound impacts on oyster populations. The management of oyster reefs in estuaries (such as BSE) requires an understanding of how estuarine hydrodynamics and salinity are influenced by forcing factors such as winds, river flow, and by the volume, timing, and location of controlled releases of riverine water.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-15-00146.1","usgsCitation":"LaPeyre, M.K., Geaghan, J., Decossas, G.A., and La Peyre, J.F., 2016, Analysis of environmental factors influencing salinity patterns, oyster growth, and mortality in lower Breton Sound Estuary, Louisiana using 20 years of data: Journal of Coastal Research, v. 32, no. 3, p. 519-530, https://doi.org/10.2112/JCOASTRES-D-15-00146.1.","productDescription":"12 p.","startPage":"519","endPage":"530","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061906","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":323276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Breton Sound Estuary","volume":"32","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575933aee4b04f417c253d0a","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":637425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geaghan, James","contributorId":171569,"corporation":false,"usgs":false,"family":"Geaghan","given":"James","email":"","affiliations":[],"preferred":false,"id":637952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decossas, Gary A.","contributorId":21472,"corporation":false,"usgs":true,"family":"Decossas","given":"Gary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":637954,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173764,"text":"70173764 - 2016 - A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations","interactions":[],"lastModifiedDate":"2016-06-09T11:15:02","indexId":"70173764","displayToPublicDate":"2016-06-08T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations","docAbstract":"Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.
","language":"English","publisher":"Elsevier","usgsCitation":"Nicol, S., Wiederholt, R., Diffendorfer, J., Mattsson, B., Thogmartin, W.E., Semmens, D.J., Laura Lopez-Hoffman, and Norris, R., 2016, A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations: Ecological Indicators, v. 69, p. 792-802.","productDescription":"10 p.","startPage":"792","endPage":"802","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071948","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":323371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":323299,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S1470160X1630262X"}],"volume":"69","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575a932ee4b04f417c275118","contributors":{"authors":[{"text":"Nicol, Sam","contributorId":171610,"corporation":false,"usgs":false,"family":"Nicol","given":"Sam","email":"","affiliations":[{"id":26927,"text":"CSIRO, Australia","active":true,"usgs":false}],"preferred":false,"id":638088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiederholt, Ruscena","contributorId":171611,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","email":"","affiliations":[{"id":12738,"text":"U of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":638089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":638087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mattsson, Brady J.","contributorId":171612,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady J.","affiliations":[{"id":26928,"text":"Univ. of Vienna","active":true,"usgs":false}],"preferred":false,"id":638090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":638091,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":638092,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Laura Lopez-Hoffman","contributorId":171613,"corporation":false,"usgs":false,"family":"Laura Lopez-Hoffman","affiliations":[{"id":12738,"text":"U of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":638093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Norris, Ryan","contributorId":171614,"corporation":false,"usgs":false,"family":"Norris","given":"Ryan","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":638094,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70173646,"text":"70173646 - 2016 - Native prey distribution and migration mediates wolf (Canis lupus) predation on domestic livestock in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2016-06-08T11:51:19","indexId":"70173646","displayToPublicDate":"2016-06-08T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Native prey distribution and migration mediates wolf (Canis lupus) predation on domestic livestock in the Greater Yellowstone Ecosystem","docAbstract":"Little research has evaluated how the migration and distribution of native prey influence patterns of livestock depredation by large carnivores. Previous research suggests that the presence of native prey can increase depredation rates by attracting predators (prey tracking hypothesis). Alternatively, the absence of native prey may facilitate predation on livestock (prey scarcity hypothesis). In this study, we evaluated support for these competing hypotheses through analysis of 4 years of cattle (Bos taurus L., 1758) depredation data (n = 39 kills), 2 years of summer and fall wolf (Canis lupus L., 1758) predation and tracking data (n = 4 wolves), and 3 years of elk (Cervus elaphus L., 1758) movement data (n = 70 elk). We used logistic regression to compare the relative influence of landscape features and elk distribution on the risk of livestock depredation in areas with migratory and resident elk. Cattle depredations occurred in habitats with increased encounter rates between wolves and livestock. In resident elk areas, depredation sites were associated with elk distribution and open roads. In migratory elk areas, depredation sites were associated with wolf dens, streams, and open habitat. Patterns of carnivore–livestock conflicts are complex, and using ungulate distribution data can predict and minimize such instances.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2015-0094","usgsCitation":"Nelson, A.A., Kauffman, M., Middleton, A., Jimenez, M., McWhirter, D.E., and Gerow, K., 2016, Native prey distribution and migration mediates wolf (Canis lupus) predation on domestic livestock in the Greater Yellowstone Ecosystem: Canadian Journal of Zoology, v. 94, no. 4, p. 291-299, https://doi.org/10.1139/cjz-2015-0094.","productDescription":"9 p.","startPage":"291","endPage":"299","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058337","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488463,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjz-2015-0094","text":"External Repository"},{"id":323270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575933b1e4b04f417c253d16","contributors":{"authors":[{"text":"Nelson, Abigail A.","contributorId":69042,"corporation":false,"usgs":true,"family":"Nelson","given":"Abigail","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":637909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew mkauffman@usgs.gov","contributorId":171443,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, A.D.","contributorId":93730,"corporation":false,"usgs":true,"family":"Middleton","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":637910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jimenez, M.D.","contributorId":10242,"corporation":false,"usgs":true,"family":"Jimenez","given":"M.D.","email":"","affiliations":[],"preferred":false,"id":637911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McWhirter, D. E.","contributorId":171549,"corporation":false,"usgs":false,"family":"McWhirter","given":"D.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":637912,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerow, K.","contributorId":171550,"corporation":false,"usgs":false,"family":"Gerow","given":"K.","email":"","affiliations":[],"preferred":false,"id":637913,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170905,"text":"fs20163030 - 2016 - Assessment of continuous (unconventional) oil and gas resources in the Late Cretaceous Mancos Shale of the Piceance Basin, Uinta-Piceance Province, Colorado and Utah, 2016","interactions":[],"lastModifiedDate":"2018-02-15T14:58:01","indexId":"fs20163030","displayToPublicDate":"2016-06-08T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3030","title":"Assessment of continuous (unconventional) oil and gas resources in the Late Cretaceous Mancos Shale of the Piceance Basin, Uinta-Piceance Province, Colorado and Utah, 2016","docAbstract":"The U.S. Geological Survey (USGS) completed a geology-based assessment of the continuous (unconventional) oil and gas resources in the Late Cretaceous Mancos Shale within the Piceance Basin of the Uinta-Piceance Province (fig. 1). The previous USGS assessment of the Mancos Shale in the Piceance Basin was completed in 2003 as part of a comprehensive assessment of the greater UintaPiceance Province (U.S. Geological Survey Uinta-Piceance Assessment Team, 2003). Since the last assessment, more than 2,000 wells have been drilled and completed in one or more intervals within the Mancos Shale of the Piceance Basin (IHS Energy Group, 2015). In addition, the USGS Energy Resources Program drilled a research core in the southern Piceance Basin that provided significant new geologic and geochemical data that were used to refine the 2003 assessment of undiscovered, technically recoverable oil and gas in the Mancos Shale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163030","usgsCitation":"Hawkins, S.J., Charpentier, R.R., Schenk, C.J., Leathers-Miller, H.M., Klett, T.R., Brownfield, M.E., Finn, T.M., Gaswirth, S.B., Marra, K.R., Le, P.A., Mercier, T.J., Pitman, J.K., and Tennyson, M.E., 2016, Assessment of continuous (unconventional) oil and gas resources in the Late Cretaceous Mancos Shale of the Piceance Basin, Uinta-Piceance Province, Colorado and Utah, 2016: U.S. Geological Survey Fact Sheet 2016-3030, 4 p., https://dx.doi.org/10.3133/fs20163030.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073153","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":323942,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2016/3030/fs20163030_version_history.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2016-3030 Version History"},{"id":321469,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3030/coverthb.jpg"},{"id":321470,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3030/fs20163030.pdf","text":"Report","size":"1.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3030"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 38\n ],\n [\n -110,\n 40.5\n ],\n [\n -106,\n 40.5\n ],\n [\n -106,\n 38\n ],\n [\n -110,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov
While multi-species occupancy models (MSOMs) are emerging as a popular method for analyzing biodiversity data, formal checking and validation approaches for this class of models have lagged behind. Concurrent with the rise in application of MSOMs among ecologists, a quiet regime shift is occurring in Bayesian statistics where predictive model comparison approaches are experiencing a resurgence. Unlike single-species occupancy models that use integrated likelihoods, MSOMs are usually couched in a Bayesian framework and contain multiple levels. Standard model checking and selection methods are often unreliable in this setting and there is only limited guidance in the ecological literature for this class of models. We examined several different contemporary Bayesian hierarchical approaches for checking and validating MSOMs and applied these methods to a freshwater aquatic study system in Colorado, USA, to better understand the diversity and distributions of plains fishes. Our findings indicated distinct differences among model selection approaches, with cross-validation techniques performing the best in terms of prediction.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1471.1","usgsCitation":"Broms, K.M., Hooten, M., and Fitzpatrick, R.M., 2016, Model selection and assessment for multi-species occupancy models: Ecology, v. 97, no. 7, p. 1759-1770, https://doi.org/10.1890/15-1471.1.","productDescription":"12 p.","startPage":"1759","endPage":"1770","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068638","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"575933b1e4b04f417c253d14","contributors":{"authors":[{"text":"Broms, Kristin M.","contributorId":171524,"corporation":false,"usgs":false,"family":"Broms","given":"Kristin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":637464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Ryan M.","contributorId":55746,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Ryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173660,"text":"70173660 - 2016 - Combining statistical inference and decisions in ecology","interactions":[],"lastModifiedDate":"2016-09-06T14:01:45","indexId":"70173660","displayToPublicDate":"2016-06-08T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Combining statistical inference and decisions in ecology","docAbstract":"Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1593.1","usgsCitation":"Williams, P.J., and Hooten, M., 2016, Combining statistical inference and decisions in ecology: Ecological Applications, v. 26, no. 6, p. 1930-1942, https://doi.org/10.1890/15-1593.1.","productDescription":"13 p.","startPage":"1930","endPage":"1942","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066134","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-02","publicationStatus":"PW","scienceBaseUri":"575933b0e4b04f417c253d0e","chorus":{"doi":"10.1890/15-1593.1","url":"http://dx.doi.org/10.1890/15-1593.1","publisher":"Wiley-Blackwell","authors":"Williams Perry J., Hooten Mevin B.","journalName":"Ecological Applications","publicationDate":"9/2016"},"contributors":{"authors":[{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":637845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":637468,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170922,"text":"ds999 - 2016 - Sedimentologic characteristics of recent washover deposits from Assateague Island, Maryland","interactions":[],"lastModifiedDate":"2025-05-13T16:49:55.913774","indexId":"ds999","displayToPublicDate":"2016-06-08T10:00:00","publicationYear":"2016","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":"999","title":"Sedimentologic characteristics of recent washover deposits from Assateague Island, Maryland","docAbstract":"The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. Although physical changes caused by tropical and extratropical storms to the sandy beaches and dunes fronting barrier islands are generally well documented, the interaction between sandy shoreline erosion and overwash with the back-barrier wetland and estuarine environments is poorly constrained. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, causing erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments.
\nThis report describes sediment data collected using sand augers in active overwash zones on Assateague Island in Maryland. Samples were collected by the U.S. Geological Survey (USGS) during two surveys in March/April and October 2014 (USGS Field Activity Numbers [FAN] 2014-301-FA and 2014-322-FA, respectively). The physical characteristics (for example, sediment texture or bedding structure) of and spatial differences among these deposits will provide information about overwash processes and sediment transport from the sandy barrier-island reaches to the back-barrier environments. Metrics derived from these data, such as mean grain size or deposit thicknesses, can be used to ground-truth remote sensing and geophysical data and can also be incorporated into sediment transport models. Data products, including sample location tables, descriptive core logs, core photographs and x-radiographs, the results of sediment grain-size analyses, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FGDC) metadata can be downloaded from the Data Downloads page.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds999","usgsCitation":"Bernier, J.C., Zaremba, N.J., Wheaton, C.J., Ellis, A.M., Marot, M.E., and Smith, C.G., 2016, Sedimentologic characteristics of recent washover deposits from Assateague Island, Maryland: U.S. Geological Survey Data Series 999, https://dx.doi.org/10.3133/ds999.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070719","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321606,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0999"},{"id":323239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":399133,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104286.htm"}],"country":"United States","state":"Maryland","otherGeospatial":"Assateague Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.09841918945311,\n 38.32765244536364\n ],\n [\n -75.08880615234375,\n 38.32388174326885\n ],\n [\n -75.09361267089844,\n 38.313645991657935\n ],\n [\n -75.157470703125,\n 38.16749461578964\n ],\n [\n -75.21377563476562,\n 38.05295746694274\n ],\n [\n -75.28999328613281,\n 37.947446401992934\n ],\n [\n -75.32981872558594,\n 37.88081521949766\n ],\n [\n -75.34629821777344,\n 37.86292829402713\n ],\n [\n -75.36552429199219,\n 37.849916893514944\n ],\n [\n -75.39779663085938,\n 37.84612146910074\n ],\n [\n -75.40054321289062,\n 37.85804928797244\n ],\n [\n -75.4046630859375,\n 37.87647939392142\n ],\n [\n -75.39299011230469,\n 37.88623464254098\n ],\n [\n -75.37994384765625,\n 37.90032327590217\n ],\n [\n -75.38063049316406,\n 37.91278405007035\n ],\n [\n -75.36346435546874,\n 37.917117737741826\n ],\n [\n -75.35041809082031,\n 37.92090950501414\n ],\n [\n -75.33531188964844,\n 37.929575667562325\n ],\n [\n -75.3277587890625,\n 37.93986540897977\n ],\n [\n -75.32295227050781,\n 37.94690492842903\n ],\n [\n -75.32295227050781,\n 37.962064679782394\n ],\n [\n -75.31539916992188,\n 37.977762552327654\n ],\n [\n -75.30715942382812,\n 37.996162679728116\n ],\n [\n -75.29205322265625,\n 38.01455819225335\n ],\n [\n -75.27626037597656,\n 38.034030762875844\n ],\n [\n -75.27008056640625,\n 38.059986139487975\n ],\n [\n -75.25016784667969,\n 38.08052761936274\n ],\n [\n -75.24055480957031,\n 38.10322464859825\n ],\n [\n -75.23368835449219,\n 38.11349003681576\n ],\n [\n -75.2178955078125,\n 38.14103736644331\n ],\n [\n -75.201416015625,\n 38.17559185481662\n ],\n [\n -75.18150329589844,\n 38.20797181420939\n ],\n [\n -75.17189025878906,\n 38.22091976683121\n ],\n [\n -75.15678405761719,\n 38.238180119798635\n ],\n [\n -75.14442443847656,\n 38.250583468289555\n ],\n [\n -75.13687133789061,\n 38.26891497618184\n ],\n [\n -75.12931823730467,\n 38.28346905497185\n ],\n [\n -75.12176513671874,\n 38.29586467286608\n ],\n [\n -75.11283874511719,\n 38.31041334882078\n ],\n [\n -75.09841918945311,\n 38.32765244536364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center acquired sediment cores, sediment surface grab samples, ground-penetrating radar (GPR) and Differential Global Positioning System (DGPS) data from Assateague Island, Maryland, in October 2014. The objectives were to identify washover deposits in the stratigraphic record to aid in understanding barrier island evolution.
\nThis report serves as an archive of GPR and DGPS data collected from Assateague Island in October 2014. Data products, including raw GPR and processed DGPS data, elevation corrected GPR profiles, and accompanying Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.
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600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
The main goal of this study was to gain knowledge on post-release survival and movement of Western Grebes (Aechmophorus occidentalis) using a modified technique for implanting satellite transmitters. This technique had improved post-surgical survival in an earlier study. Nine Western Grebes, implanted with intracoelomic (within the body cavity) satellite transmitters with percutaneous antennae, were released close to their capture site in San Francisco Bay, California, USA. Eight survived at least 25 days (average number of transmittal days was 140.8), while two had transmitters that provided data for greater than 1 year (436 and 454 days). The average cumulative distance recorded for all Western Grebes (n = 9) was 829 km with two round-trip movements documented. One individual Western Grebe traveled a cumulative round-trip distance of 2,144 km in July and November 2011, while another individual traveled a round-trip distance of 1,514 km between 8 and 14 December 2011. This study provides a step forward in testing implantable satellite transmitters in Western Grebes and highlights the need to further improve tracking methods, potentially improving our understanding of their population threats.
","language":"English","publisher":"Waterbird Society","doi":"10.1675/063.039.0208","usgsCitation":"Mills, K.L., Gaydos, J.K., Fiorello, C.V., Whitmer, E., De La Cruz, S., Mulcahy, D.M., Vilchis, L.I., and Ziccardi, M.H., 2016, Post-release survival and movement of Western Grebes (Aechmophorus occidentalis) implanted with intracoelomic satellite transmitters: Waterbirds, v. 39, no. 2, p. 175-186, https://doi.org/10.1675/063.039.0208.","productDescription":"12 p.","startPage":"175","endPage":"186","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051534","costCenters":[{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Clear Lake, Drews Reservoir, San Francisco Bay, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07958984375001,\n 32.602361666817515\n ],\n [\n -124.07958984375001,\n 43.24520272203359\n ],\n [\n -116.3232421875,\n 43.24520272203359\n ],\n [\n -116.3232421875,\n 32.602361666817515\n ],\n [\n -124.07958984375001,\n 32.602361666817515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577e2bb1e4b0ef4d2f445a36","contributors":{"authors":[{"text":"Mills, Kyra L.","contributorId":172677,"corporation":false,"usgs":false,"family":"Mills","given":"Kyra","email":"","middleInitial":"L.","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":641545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaydos, Joseph K.","contributorId":28456,"corporation":false,"usgs":true,"family":"Gaydos","given":"Joseph","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":641546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiorello, Christine V.","contributorId":172678,"corporation":false,"usgs":false,"family":"Fiorello","given":"Christine","email":"","middleInitial":"V.","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":641547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitmer, Emily","contributorId":172679,"corporation":false,"usgs":false,"family":"Whitmer","given":"Emily","email":"","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":641548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De La Cruz, Susan sdelacruz@usgs.gov","contributorId":131159,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mulcahy, Daniel M. dmulcahy@usgs.gov","contributorId":3102,"corporation":false,"usgs":true,"family":"Mulcahy","given":"Daniel","email":"dmulcahy@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":641550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vilchis, L. Ignacio","contributorId":172680,"corporation":false,"usgs":false,"family":"Vilchis","given":"L.","email":"","middleInitial":"Ignacio","affiliations":[{"id":24831,"text":"San Diego Zoo Institute for Conservation Research","active":true,"usgs":false}],"preferred":false,"id":641551,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ziccardi, Michael H.","contributorId":16677,"corporation":false,"usgs":true,"family":"Ziccardi","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":641552,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}