Flow-duration curves (FDCs) of daily streamflow are useful for many applications in water resources planning and management but must be estimated at ungaged sites. One common technique for estimating FDCs at ungaged sites in a given region is to use equations obtained by linear regression of FDC quantiles against multiple basin characteristics that can be computed by means of a geographic information system (GIS) computer program. In this study, such regional regression equations for estimating FDC quantiles were computed at the 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 98, 99, 99.5, 99.8, and 99.9-percent exceedance probabilities for rural, unregulated streams in Indiana and Illinois with temporally stationary records, using data through September 30, 2007. The approach used accounts for censored values below 0.01 cubic feet per second, which are observed at exceedance probabilities as low as 70 percent (that is, occurring at least 30 percent of the time). The basin characteristics used are suitable for computation by the USGS Web-based application, StreamStats, and are available for all U.S. Environmental Protection Agency (EPA) Region V states and the larger Great Lakes area, with some specific local exceptions. Indiana and Illinois were each divided into three regions, and a different set of equations for estimating FDC quantiles was computed for each region.
The error of estimation of the FDC quantiles, measured as the mean square residual in log space converted to a percentage of the quantile, varies somewhat among regions and varies strongly with exceedance probability, with a minimum error of 10 to 20 percent at an exceedance probability of 5 or 10 percent, but rises to 17 to 38 percent at the high-flow end of the FDCs (the 0.1-percent quantile) and 100 to 745 percent at the low-flow end. For comparison, errors of estimation also were computed for FDC quantiles estimated by linear regression on drainage area alone and by using the drainage-area ratio (DAR) method. Three criteria, the nearest basin centroid and two others termed “strict” and “broad”, were used to select index stations for the DAR method. The “strict” and “broad” criteria put conditions on the basin centroid distance and the range of their drainage-area ratios, and the errors were averaged for all index station pairs satisfying each criterion. The use of the simpler DAR method usually resulted in higher errors of estimation compared to the linear regression equations with multiple basin characteristics, except occasionally in the case of the DAR method with the strict index station selection criterion, a criterion that is rarely possible to satisfy in practice.
An example application of the estimated equations to one gaged and a few ungaged locations in a watershed in the study area is included to illustrate the steps required. These steps are the computation of the basin characteristics and, using those characteristics together with the estimated equations, the computation of the FDC quantiles and their uncertainties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145177","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Region V, and the Indiana Department of Environmental Management","usgsCitation":"Over, T.M., Riley, J.D., Marti, M.K., Sharpe, J.B., and Arvin, D., 2014, Estimation of regional flow-duration curves for Indiana and Illinois (ver. 2.0, April 2022): U.S. Geological Survey Scientific Investigations Report 2014–5177, 24 p. and additional downloads, tables 2–5, 8–13, and 18, https://doi.org/10.3133/sir20145177.","productDescription":"Report: v, 24 p.; Tables: 2-5, 8-13, and 18; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053042","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":438739,"rank":26,"type":{"id":30,"text":"Data 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U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
• Premise of the study: A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona.
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• Methods: We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data.
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• Key results: Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates.
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• Conclusions: Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events.
","language":"English","publisher":"Botanical Society of America","doi":"10.3732/ajb.1400035","usgsCitation":"Shryock, D.F., Esque, T., and Huges, L., 2014, Population viability of Pediocactus brady (Cactaceae) in a changing climate: American Journal of Botany, v. 101, no. 11, p. 1944-1953, https://doi.org/10.3732/ajb.1400035.","productDescription":"10 p.","startPage":"1944","endPage":"1953","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053992","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472668,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3732/ajb.1400035","text":"Publisher Index Page"},{"id":297604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.873046875,\n 31.653381399664\n ],\n [\n -114.873046875,\n 36.949891786813296\n ],\n [\n -109.072265625,\n 36.949891786813296\n ],\n [\n -109.072265625,\n 31.653381399664\n ],\n [\n -114.873046875,\n 31.653381399664\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","issue":"11","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c28e4b08de9379b3673","contributors":{"authors":[{"text":"Shryock, Daniel F. dshryock@usgs.gov","contributorId":5139,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel","email":"dshryock@usgs.gov","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":3221,"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":539456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huges, Lee","contributorId":138963,"corporation":false,"usgs":false,"family":"Huges","given":"Lee","email":"","affiliations":[{"id":12596,"text":"Retired, BLM, AZ Strip Field Office, St George, UT","active":true,"usgs":false}],"preferred":false,"id":539458,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191813,"text":"70191813 - 2014 - Effects of prey abundance, distribution, visual contrast and morphology on selection by a pelagic piscivore","interactions":[],"lastModifiedDate":"2017-10-18T11:08:22","indexId":"70191813","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of prey abundance, distribution, visual contrast and morphology on selection by a pelagic piscivore","docAbstract":"Groundwater quality in the 1,850-square-mile North San Francisco Bay Shallow Aquifer (NSF-SA) study unit was investigated by the U.S. Geological Survey (USGS) from April to August 2012, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The NSF-SA study unit was the first study unit to be sampled as part of the second phase of the GAMA-PBP, which focuses on the shallow aquifer system.
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The GAMA NSF-SA study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the shallow aquifer systems and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The shallow aquifer system in the NSF-SA study unit was defined as the part of the aquifer system that is used by many private domestic wells and is shallower than the primary aquifer system used by many public-supply wells.
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In the NSF-SA study unit located in Marin, Mendocino, Napa, Solano, and Sonoma Counties, groundwater samples were collected from 71 wells. Seventy of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and one well was selected to aid in evaluation of water-quality issues (understanding well).
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The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides, and pesticide degradates); constituents of special interest (perchlorate and 1,2,3-trichloropropane [1,2,3-TCP]); naturally occurring inorganic constituents (trace elements, nutrients, major and minor ions, silica, and total dissolved solids [TDS]); and radioactive constituents (radon-222 and gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen, oxygen, boron, strontium, and inorganic carbon in water, tritium activities, and carbon-14 abundances) were measured to help identify the sources and ages of the sampled groundwater. In total, 207 constituents and water-quality indicators were measured.
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Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 13 percent of the wells in the NSF-SA study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample-collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 91 percent of the compounds.
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Most of the wells sampled for this study were private domestic wells. Private domestic wells are not regulated in California, and groundwater from these wells is rarely analyzed for water-quality constituents. Although regulatory benchmarks for drinking-water quality do not apply to private domestic wells, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and California Department of Public Health (CDPH), to non-regulatory health-based benchmarks established by the USGS in cooperation with the USEPA, and to non-regulatory benchmarks established for aesthetic concerns by the CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most of the organic and inorganic constituents that were detected in groundwater samples from the 70 grid wells in the NSF-SA study unit were detected at concentrations less than drinking-water benchmarks.
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Of the 149 organic and special-interest constituents analyzed for in groundwater samples, 31 were detected; concentrations of most detected constituents were less than regulatory and non-regulatory health-based benchmarks. One VOC, benzene, and one insecticide, dieldrin, were detected at concentrations above their respective health-based benchmarks. In total, VOCs were detected in 40 percent of the grid wells sampled, pesticides and pesticide degradates were detected in 13 percent, and perchlorate was detected in 27 percent of the 70 grid wells sampled.
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Groundwater samples from 70 grid wells were analyzed for trace elements, major and minor ions, nutrients, and radioactive constituents; most detected concentrations were less than health-based benchmarks. Exceptions are 12 detections of manganese greater than the USGS Health-Based Screening Level (HBSL), 7 detections of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (μg/L), 2 detections of boron greater than the HBSL of 6,000 μg/L, 2 detections of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter (mg/L), 2 detections of nitrate greater than the MCL-US of 10 mg/L, and two detections of radon-222 greater than the proposed MCL-US of 4,000 picocuries per liter.
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Results for constituents with non-regulatory benchmarks set for aesthetic concerns from the grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in 13 grid wells. Chloride was detected at a concentration greater than the SMCL-CA recommended benchmark of 250 mg/L in two grid wells. Sulfate concentrations greater than the SMCL-CA recommended benchmark of 250 mg/L were measured in two grid wells, and the concentration in one of these wells was also greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 15 grid wells, and concentrations in 4 of these wells were also greater than the SMCL-CA upper benchmark of 1,000 mg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds865","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. Prepared in cooperation with the California State Water Resources Control Board.","usgsCitation":"Bennett, G.L., and Fram, M.S., 2014, Groundwater-quality data in the North San Francisco Bay Shallow Aquifer study unit, 2012: results from the California GAMA Program: U.S. Geological Survey Data Series 865, x, 94 p., https://doi.org/10.3133/ds865.","productDescription":"x, 94 p.","numberOfPages":"108","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-050639","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":295916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds865.jpg"},{"id":295765,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0865/pdf/ds865.pdf","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295758,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0865/"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Shallow Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 38.18638677411551\n ],\n [\n -122.464599609375,\n 37.97018468810549\n ],\n [\n -121.95922851562501,\n 38.03078569382294\n ],\n [\n -122.03613281249999,\n 38.35888785866677\n ],\n [\n -122.51953124999999,\n 38.79690830348427\n ],\n [\n -122.947998046875,\n 38.93377552819722\n ],\n [\n -123.23364257812499,\n 38.762650338334154\n ],\n [\n -123.277587890625,\n 38.39333888832238\n ],\n [\n -123.04687499999999,\n 38.18638677411551\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c9bb5e4b0ba8303f709ce","contributors":{"authors":[{"text":"Bennett, George L. V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519005,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70074697,"text":"70074697 - 2014 - An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data","interactions":[],"lastModifiedDate":"2020-12-28T12:43:57.68989","indexId":"70074697","displayToPublicDate":"2014-10-21T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data","docAbstract":"Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large‐scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short‐term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage‐grouse (Centrocercus minimus). The long‐term population index data available for Gunnison sage‐grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage‐grouse to be variable and slightly declining over the past 16 years.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1290","usgsCitation":"Davis, A.J., Hooten, M., Phillips, M.L., and Doherty, P.F., 2014, An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data: Ecology and Evolution, v. 4, no. 22, p. 4247-2457, https://doi.org/10.1002/ece3.1290.","productDescription":"11 p.","startPage":"4247","endPage":"2457","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045802","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1290","text":"Publisher Index Page"},{"id":311317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -111.68701171875,\n 37.00255267215955\n ],\n [\n -111.68701171875,\n 39.487084981687495\n ],\n [\n -106.9189453125,\n 39.487084981687495\n ],\n [\n -106.9189453125,\n 37.00255267215955\n ],\n [\n -111.68701171875,\n 37.00255267215955\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"22","noUsgsAuthors":false,"publicationDate":"2014-10-22","publicationStatus":"PW","scienceBaseUri":"564717bde4b0e2669b3130ff","contributors":{"authors":[{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":579809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":119998,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin B.","affiliations":[],"preferred":false,"id":518511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Michael L.","contributorId":149855,"corporation":false,"usgs":false,"family":"Phillips","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":579810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doherty, Paul F. Jr.","contributorId":37636,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","suffix":"Jr.","email":"","middleInitial":"F.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":579811,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70124101,"text":"ofr20141198 - 2014 - Late Holocene sedimentary environments of south San Francisco Bay, California, illustrated in gravity cores","interactions":[],"lastModifiedDate":"2020-07-09T13:32:28.455946","indexId":"ofr20141198","displayToPublicDate":"2014-10-10T13:55:00","publicationYear":"2014","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":"2014-1198","title":"Late Holocene sedimentary environments of south San Francisco Bay, California, illustrated in gravity cores","docAbstract":"Data are reported here from 51 gravity cores collected from the southern part of San Francisco Bay by the U.S. Geological Survey in 1990. The sedimentary record in the cores demonstrates a stable geographic distribution of facies and spans a few thousand years. Carbon-14 dating of the sediments suggests that sedimentation rates average about 1 mm/yr. The geometry of the bay floor and the character of the sediment deposited have remained about the same in the time spanned by the cores. However, the sedimentary record over periods of centuries or decades is likely to be much more variable. Sediments containing a few bivalve shells and bivalve or oyster coquinas are most often found west of the main channel and near the San Mateo Bridge. Elsewhere in the south bay, shells are rare except in the southernmost reaches where scattered gastropod shells are found.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141198","usgsCitation":"Woodrow, D., Fregoso, T., Wong, F.L., and Jaffe, B.E., 2014, Late Holocene sedimentary environments of south San Francisco Bay, California, illustrated in gravity cores: U.S. Geological Survey Open-File Report 2014-1198, Report: iv, 91 p.; Spatial Data; Metadata, https://doi.org/10.3133/ofr20141198.","productDescription":"Report: iv, 91 p.; Spatial Data; Metadata","numberOfPages":"97","onlineOnly":"Y","ipdsId":"IP-054320","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295217,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1198/pdf/ofr2014-1198.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":295218,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2014/1198/downloads/ofr2014-1198_shape.zip","linkFileType":{"id":6,"text":"zip"}},{"id":295216,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1198/","linkFileType":{"id":5,"text":"html"}},{"id":295219,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2014/1198/downloads/metadata","linkFileType":{"id":5,"text":"html"}},{"id":376153,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1198/images/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.26660156249999,\n 37.23032838760387\n ],\n [\n -121.4208984375,\n 37.23032838760387\n ],\n [\n -121.4208984375,\n 38.41055825094609\n ],\n [\n -123.26660156249999,\n 38.41055825094609\n ],\n [\n -123.26660156249999,\n 37.23032838760387\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5438e706e4b0c47db4290587","contributors":{"authors":[{"text":"Woodrow, Donald L.","contributorId":88668,"corporation":false,"usgs":true,"family":"Woodrow","given":"Donald L.","affiliations":[],"preferred":false,"id":500588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fregoso, Theresa A.","contributorId":81824,"corporation":false,"usgs":true,"family":"Fregoso","given":"Theresa A.","affiliations":[],"preferred":false,"id":500587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":500585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":500586,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173512,"text":"70173512 - 2014 - Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon","interactions":[],"lastModifiedDate":"2016-06-22T13:11:13","indexId":"70173512","displayToPublicDate":"2014-10-07T05:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon","docAbstract":"Ceratomyxa shasta (Myxozoa) is a common gastrointestinal pathogen of salmonid fishes in the Pacific Northwest of the United States. We have been investigating this parasite in adult Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River, Oregon. In prior work, we observed differences in the pattern of development of C. shasta in adult salmon compared to juvenile salmon. Adult salmon consistently had large numbers of prespore stages in many of the fish that survived to spawn in the fall. However, myxospores were rarely observed, even though they were exposed and presumably infected for months before spawning. We evaluated the ability of C. shasta to sporulate following fish death because it is reported that myxosores are common in carcasses of Chinook salmon. We collected the intestine from 30 adult salmon immediately after artificial spawning and death (T0). A total of 23 fish were infected with C. shasta based on histology, but only a few myxospores were observed in 1 fish by histology. Intestines of these fish were examined at T0 and T7 (latter held at 17 C for 7 days) using quantified wet mount preparations. An increase in myxospore concentrations was seen in 39% of these fish, ranging between a 1.5- to a 14.5-fold increase. The most heavily infected fish exhibited a 4.6-fold increase from 27,841 to 129,352 myxospores/cm. This indicates, supported by various statistical analyses, that under certain conditions presporogonic forms are viable and continue to sporulate after death in adult salmon. Considering the life cycle of C. shasta and anadromous salmon, the parasite may have evolved 2, non-mutually exclusive developmental strategies. In young fish (parr and smolts), the parasite sporulates shortly after infection and is released into freshwater from either live or dead fish before their migration to seawater, where the alternate host is absent. The second strategy occurs in adult salmon, particularly spring Chinook salmon, which become infected upon their return to freshwater in the spring or early summer. For several months throughout the summer, only prespore stages are observed in most fish, even at the time of spawning. But once the fish dies, environmental conditions experienced by C. shasta change and viable presporogonic stages are induced to sporulate. As the post-spawned fish occur in the upper reaches of rivers, the myxospores would be released in a freshwater environment that would provide a reasonable opportunity for them to encounter their freshwater polychaete hosts, which reside downstream.
","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/13-490.1","usgsCitation":"Kent, M., Soderlund, K., Thomann, E., Schreck, C.B., and Sharpton, T., 2014, Post-mortem sporulation of Ceratomyxa shasta (Myxozoa) after death in adult Chinook salmon: Journal of Parasitology, v. 100, no. 5, p. 679-683, https://doi.org/10.1645/13-490.1.","productDescription":"5 p.","startPage":"679","endPage":"683","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056298","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b9e4b07657d1a22930","contributors":{"authors":[{"text":"Kent, Michael L.","contributorId":108420,"corporation":false,"usgs":true,"family":"Kent","given":"Michael L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":640340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soderlund, K.","contributorId":80883,"corporation":false,"usgs":true,"family":"Soderlund","given":"K.","email":"","affiliations":[],"preferred":false,"id":640341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomann, E.","contributorId":32801,"corporation":false,"usgs":true,"family":"Thomann","given":"E.","email":"","affiliations":[],"preferred":false,"id":640342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharpton, T.J.","contributorId":172324,"corporation":false,"usgs":false,"family":"Sharpton","given":"T.J.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":640343,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70128127,"text":"70128127 - 2014 - A cross-validation package driving Netica with python","interactions":[],"lastModifiedDate":"2014-10-03T16:17:23","indexId":"70128127","displayToPublicDate":"2014-10-03T16:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A cross-validation package driving Netica with python","docAbstract":"Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2014.09.007","usgsCitation":"Fienen, M., and Plant, N.G., 2014, A cross-validation package driving Netica with python: Environmental Modelling and Software, v. 63, p. 14-23, https://doi.org/10.1016/j.envsoft.2014.09.007.","productDescription":"10 p.","startPage":"14","endPage":"23","numberOfPages":"10","ipdsId":"IP-058198","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":294937,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2014.09.007"},{"id":294950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fac86e4b092f17df61cc2","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":502769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":502770,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70128076,"text":"70128076 - 2014 - Fatal paralytic shellfish poisoning in Kittlitz's Murrelet (Brachyramphus brevirostris) nestlings, Alaska, USA","interactions":[],"lastModifiedDate":"2017-07-12T15:34:54","indexId":"70128076","displayToPublicDate":"2014-10-03T10:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Fatal paralytic shellfish poisoning in Kittlitz's Murrelet (Brachyramphus brevirostris) nestlings, Alaska, USA","docAbstract":"Paralytic shellfish poisoning (PSP) is an acute toxic illness in humans resulting from ingestion of shellfish contaminated with a suite of neurotoxins (saxitoxins) produced by marine dinoflagellates, most commonly in the genus Alexandrium. Poisoning also has been sporadically suspected and, less often, documented in marine wildlife, often in association with an outbreak in humans. Kittlitz's Murrelet (Brachyramphus brevirostris) is a small, rare seabird of the Northern Pacific with a declining population. From 2008 to 2012, as part of a breeding ecology study, multiple Kittlitz's Murrelet nests on Kodiak Island, Alaska, were monitored by remote cameras. During the 2011 and 2012 breeding seasons, nestlings from several sites died during mild weather conditions. Remote camera observations revealed that the nestlings died shortly after consuming sand lance (Ammodytes hexapterus), a fish species known to biomagnify saxitoxin. High levels of saxitoxin were subsequently documented in crop content in 87% of nestling carcasses. Marine bird deaths from PSP may be underreported.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Diseases","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2013-11-296","usgsCitation":"Shearn-Bochsler, V.I., Lance, E., Corcoran, R., Piatt, J.F., Bodenstein, B., Frame, E., and Lawonn, J., 2014, Fatal paralytic shellfish poisoning in Kittlitz's Murrelet (Brachyramphus brevirostris) nestlings, Alaska, USA: Journal of Wildlife Diseases, v. 50, no. 4, p. 933-937, https://doi.org/10.7589/2013-11-296.","productDescription":"5 p.","startPage":"933","endPage":"937","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049617","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":294904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294903,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.7589/2013-11-296"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.92919921875,\n 57.36801461845934\n ],\n [\n -154.62158203125,\n 57.68066002977235\n ],\n [\n -154.171142578125,\n 57.844750992891\n ],\n [\n -153.6328125,\n 58.12431960569377\n ],\n [\n -153.204345703125,\n 58.41322259056804\n ],\n [\n -152.86376953125,\n 58.642652516575964\n ],\n [\n -152.325439453125,\n 58.73400476743346\n ],\n [\n -151.962890625,\n 58.62549730245039\n ],\n [\n -151.732177734375,\n 58.34986596667874\n ],\n [\n -151.67724609374997,\n 58.12431960569377\n ],\n [\n -151.776123046875,\n 57.97315745102812\n ],\n [\n -151.776123046875,\n 57.73934950049299\n ],\n [\n -151.995849609375,\n 57.45677122453565\n ],\n [\n -152.33642578125,\n 57.249337594636835\n ],\n [\n -152.874755859375,\n 57.022794415389725\n ],\n [\n -153.643798828125,\n 56.64414704199467\n ],\n [\n -153.819580078125,\n 56.45034902929676\n ],\n [\n -154.302978515625,\n 56.35916436114856\n ],\n [\n -154.84130859375,\n 56.3409012041991\n ],\n [\n -154.97314453125,\n 56.511017504952136\n ],\n [\n -154.84130859375,\n 56.794862261400546\n ],\n [\n -154.8193359375,\n 57.11238500793404\n ],\n [\n -154.92919921875,\n 57.36801461845934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542fac89e4b092f17df61cca","contributors":{"authors":[{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":502754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lance, Ellen W.","contributorId":15946,"corporation":false,"usgs":true,"family":"Lance","given":"Ellen W.","affiliations":[],"preferred":false,"id":502756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corcoran, Robin","contributorId":29750,"corporation":false,"usgs":true,"family":"Corcoran","given":"Robin","email":"","affiliations":[],"preferred":false,"id":502759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":502760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodenstein, Barbara 0000-0001-7946-0103","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":8399,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","affiliations":[],"preferred":false,"id":502755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frame, Elizabeth","contributorId":24710,"corporation":false,"usgs":true,"family":"Frame","given":"Elizabeth","affiliations":[],"preferred":false,"id":502757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawonn, James","contributorId":28185,"corporation":false,"usgs":true,"family":"Lawonn","given":"James","email":"","affiliations":[],"preferred":false,"id":502758,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70125310,"text":"cir1404 - 2014 - Great Lakes restoration success through science: U.S. Geological Survey accomplishments 2010 through 2013","interactions":[],"lastModifiedDate":"2017-02-06T10:59:47","indexId":"cir1404","displayToPublicDate":"2014-10-02T09:02:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1404","title":"Great Lakes restoration success through science: U.S. Geological Survey accomplishments 2010 through 2013","docAbstract":"The Great Lakes (Superior, Michigan, Huron, Erie, and Ontario) are the largest group of freshwater lakes on Earth and serve as an important source of drinking water, transportation, power, and recreational opportunities for the United States and Canada. They also support an abundant commercial and recreational fishery, are crucial for agriculture, and are essential to the economic vitality of the region. The Great Lakes support a wealth of biological diversity, including over 200 globally rare plants and animals and more than 40 species that are found nowhere else in the world. However, more than a century of environmental degradation has taken a substantial toll on the Great Lakes. To stimulate and promote the goal of a healthy Great Lakes region, President Obama and Congress created the Great Lakes Restoration Initiative (GLRI) in 2009. The GLRI is an interagency collaboration that seeks to address the most significant environmental problems in the Great Lakes ecosystem. The GLRI is composed of five focus areas that address these issues:
\nAs of August 2013, the GLRI had funded more than 1,500 projects and programs of the highest priority to meet immediate cleanup, restoration, and protection needs. These projects use scientific analyses as the basis for identifying the restoration needs and priorities for the GLRI. Results from the science, monitoring, and other on-the-ground actions by the U.S. Geological Survey (USGS) provide the scientific information needed to help guide the Great Lakes restoration efforts. This document highlights a selection of USGS projects for each of the five focus areas through 2013, demonstrating the importance of science for restoration success. Additional information for these and other USGS projects that are important for Great Lakes restoration is available at http://cida.usgs.gov/glri/glri-catalog/.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1404","collaboration":"A Product of the Great Lakes Restoration Initiative","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2014, Great Lakes restoration success through science: U.S. Geological Survey accomplishments 2010 through 2013: U.S. Geological Survey Circular 1404, v, 56 p., https://doi.org/10.3133/cir1404.","productDescription":"v, 56 p.","numberOfPages":"68","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-058287","costCenters":[{"id":323,"text":"Great Lakes Restoration","active":false,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":294757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1404.jpg"},{"id":294756,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1404/pdf/circ1404.pdf","text":"Report","size":"35.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":294755,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1404/"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.13232421875,\n 49.06666839558117\n ],\n [\n -86.15478515625,\n 48.850258199721495\n ],\n [\n -84.638671875,\n 48.03401915864286\n ],\n [\n -83.8916015625,\n 46.46813299215554\n ],\n [\n -80.771484375,\n 46.042735653846506\n ],\n [\n -79.34326171875,\n 45.07352060670971\n ],\n [\n -78.7060546875,\n 44.071800467511565\n ],\n [\n -76.04736328125,\n 44.465151013519616\n ],\n [\n -74.99267578125,\n 45.042478050891546\n ],\n [\n -74.267578125,\n 45.089035564831036\n ],\n [\n -74.06982421875,\n 44.19795903948531\n ],\n [\n -75.08056640625,\n 42.5530802889558\n ],\n [\n -76.83837890625,\n 41.73852846935917\n ],\n [\n -80.4638671875,\n 40.81380923056961\n ],\n [\n -82.77099609375,\n 40.329795743702064\n ],\n [\n -87.51708984375,\n 41.09591205639546\n ],\n [\n -89.67041015625,\n 43.24520272203359\n ],\n [\n -92.87841796875,\n 46.42271253466717\n ],\n [\n -92.92236328125,\n 47.57652571374621\n ],\n [\n -89.97802734375,\n 48.879167148960214\n ],\n [\n -88.13232421875,\n 49.06666839558117\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e5b08e4b092f17df5a6af","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":544977,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70133235,"text":"70133235 - 2014 - Minimal role of eastern fence lizards in Borrelia burgdorferi transmission in central New Jersey oak/pine woodlands","interactions":[],"lastModifiedDate":"2020-12-31T19:03:20.130352","indexId":"70133235","displayToPublicDate":"2014-10-01T13:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Minimal role of eastern fence lizards in Borrelia burgdorferi transmission in central New Jersey oak/pine woodlands","title":"Minimal role of eastern fence lizards in Borrelia burgdorferi transmission in central New Jersey oak/pine woodlands","docAbstract":"The Eastern fence lizard, Sceloporus undulatus, is widely distributed in eastern and central North America, ranging through areas with high levels of Lyme disease, as well as areas where Lyme disease is rare or absent. We studied the potential role of S. undulatus in transmission dynamics of Lyme spirochetes by sampling ticks from a variety of natural hosts at field sites in central New Jersey, and by testing the reservoir competence of S. undulatus for Borrelia burgdorferi in the laboratory. The infestation rate of ticks on fence lizards was extremely low (proportion infested = 0.087, n = 23) compared to that on white footed mice and other small mammals (proportion infested = 0.53, n = 140). Of 159 nymphs that had fed as larvae on lizards that had previously been exposed to infected nymphs, none was infected with B. burgdorferi, compared with 79.9% of 209 nymphs that had fed as larvae on infected control mice. Simulations suggest that changes in the numbers of fence lizards in a natural habitat would have little effect on the infection rate of nymphal ticks with Lyme spirochetes. We conclude that in central New Jersey S. undulatus plays a minimal role in the enzootic transmission cycle of Lyme spirochetes.
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Jersey\",\"nation\":\"USA \"}}]}","volume":"100","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5465d634e4b04d4b7dbd6612","contributors":{"authors":[{"text":"Rulison, Eric L.","contributorId":90197,"corporation":false,"usgs":true,"family":"Rulison","given":"Eric L.","affiliations":[],"preferred":false,"id":524928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerr, Kaetlyn T","contributorId":127371,"corporation":false,"usgs":false,"family":"Kerr","given":"Kaetlyn","email":"","middleInitial":"T","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":524929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dyer, Megan C","contributorId":127372,"corporation":false,"usgs":false,"family":"Dyer","given":"Megan C","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":524930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Han, Seungeun","contributorId":127373,"corporation":false,"usgs":false,"family":"Han","given":"Seungeun","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":524931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burke, Russell L.","contributorId":127374,"corporation":false,"usgs":false,"family":"Burke","given":"Russell","email":"","middleInitial":"L.","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":524932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsao, Jean I.","contributorId":71466,"corporation":false,"usgs":true,"family":"Tsao","given":"Jean I.","affiliations":[],"preferred":false,"id":524933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":3204,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","email":"hginsberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":524927,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70133238,"text":"70133238 - 2014 - Accounting for false-positive acoustic detections of bats using occupancy models","interactions":[],"lastModifiedDate":"2014-11-18T09:54:06","indexId":"70133238","displayToPublicDate":"2014-10-01T01:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for false-positive acoustic detections of bats using occupancy models","docAbstract":"1. Acoustic surveys have become a common survey method for bats and other vocal taxa. Previous work shows that bat echolocation may be misidentified, but common analytic methods, such as occupancy models, assume that misidentifications do not occur. Unless rare, such misidentifications could lead to incorrect inferences with significant management implications.
\n\n
2. We fit a false-positive occupancy model to data from paired bat detector and mist-net surveys to estimate probability of presence when survey data may include false positives. We compared estimated occupancy and detection rates to those obtained from a standard occupancy model. We also derived a formula to estimate the probability that bats were present at a site given its detection history. As an example, we analysed survey data for little brown bats Myotis lucifugus from 135 sites in Washington and Oregon, USA.
\n\n
3. We estimated that at an unoccupied site, acoustic surveys had a 14% chance per night of producing spurious M. lucifugus detections. Estimated detection rates were higher and occupancy rates were lower under the false-positive model, relative to a standard occupancy model. Un-modelled false positives also affected inferences about occupancy at individual sites. For example, probability of occupancy at individual sites with acoustic detections but no captures ranged from 2% to 100% under the false-positive occupancy model, but was always 100% under a standard occupancy model.
\n\n
4. Synthesis and applications. Our results suggest that false positives sufficient to affect inferences may be common in acoustic surveys for bats. We demonstrate an approach that can estimate occupancy, regardless of the false-positive rate, when acoustic surveys are paired with capture surveys. Applications of this approach include monitoring the spread of White-Nose Syndrome, estimating the impact of climate change and informing conservation listing decisions. We calculate a site-specific probability of occupancy, conditional on survey results, which could inform local permitting decisions, such as for wind energy projects. More generally, the magnitude of false positives suggests that false-positive occupancy models can improve accuracy in research and monitoring of bats and provide wildlife managers with more reliable information.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12303","usgsCitation":"Clement, M.J., Rodhouse, T., Ormsbee, P., Szewczak, J.M., and Nichols, J., 2014, Accounting for false-positive acoustic detections of bats using occupancy models: Journal of Applied Ecology, v. 51, no. 5, p. 1460-1467, https://doi.org/10.1111/1365-2664.12303.","productDescription":"8 p.","startPage":"1460","endPage":"1467","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054795","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":296031,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.76074218749999,\n 42.00032514831621\n ],\n [\n -124.76074218749999,\n 48.99463598353408\n ],\n [\n -116.69677734375,\n 48.99463598353408\n ],\n [\n -116.69677734375,\n 42.00032514831621\n ],\n [\n -124.76074218749999,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5465d62ae4b04d4b7dbd652b","contributors":{"authors":[{"text":"Clement, Matthew J. mclement@usgs.gov","contributorId":5278,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":524943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ormsbee, Patricia C.","contributorId":127379,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia C.","affiliations":[{"id":6925,"text":"US Forest Service, retired","active":true,"usgs":false}],"preferred":false,"id":524944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szewczak, Joseph M.","contributorId":30127,"corporation":false,"usgs":false,"family":"Szewczak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6958,"text":"Department of Biological Sciences, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":524945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524946,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70127009,"text":"70127009 - 2014 - Long-term effects of seeding after wildfire on vegetation in Great Basin shrubland ecosystems","interactions":[],"lastModifiedDate":"2014-09-25T13:32:35","indexId":"70127009","displayToPublicDate":"2014-09-25T13:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term effects of seeding after wildfire on vegetation in Great Basin shrubland ecosystems","docAbstract":"1. Invasive annual grasses alter fire regimes in shrubland ecosystems of the western USA, threatening ecosystem function and fragmenting habitats necessary for shrub-obligate species such as greater sage-grouse. Post-fire stabilization and rehabilitation treatments have been administered to stabilize soils, reduce invasive species spread and restore or establish sustainable ecosystems in which native species are well represented. Long-term effectiveness of these treatments has rarely been evaluated.
\n2. We studied vegetation at 88 sites where aerial or drill seeding was implemented following fires between 1990 and 2003 in Great Basin (USA) shrublands. We examined sites on loamy soils that burned only once since 1970 to eliminate confounding effects of recurrent fire and to assess soils most conducive to establishment of seeded species. We evaluated whether seeding provided greater cover of perennial seeded species than burned–unseeded and unburned–unseeded sites, while also accounting for environmental variation.
\n3. Post-fire seeding of native perennial grasses generally did not increase cover relative to burned–unseeded areas. Native perennial grass cover did, however, increase after drill seeding when competitive non-natives were not included in mixes. Seeding non-native perennial grasses and the shrub Bassia prostrata resulted in more vegetative cover in aerial and drill seeding, with non-native perennial grass cover increasing with annual precipitation. Seeding native shrubs, particularly Artemisia tridentata, did not increase shrub cover or density in burned areas. Cover of undesirable, non-native annual grasses was lower in drill seeded relative to unseeded areas, but only at higher elevations.
\n4. Synthesis and applications. Management objectives are more likely to be met in high-elevation or precipitation locations where establishment of perennial grasses occurred. On lower and drier sites, management objectives are unlikely to be met with seeding alone. Intensive restoration methods such as invasive plant control and/or repeated sowings after establishment failures due to weather may be required in subsequent years. Managers might consider using native-only seed mixtures when establishment of native perennial grasses is the goal. Post-fire rehabilitation provides a land treatment example where long-term monitoring can inform adaptive management decisions to meet future objectives, particularly in arid landscapes where recovery is slow.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Scientific Publications","publisherLocation":"Oxford","doi":"10.1111/1365-2664.12309","usgsCitation":"Knutson, K., Pyke, D.A., Wirth, T., Arkle, R., Pilliod, D., Brooks, M.L., Chambers, J., and Grace, J.B., 2014, Long-term effects of seeding after wildfire on vegetation in Great Basin shrubland ecosystems: Journal of Applied Ecology, v. 51, no. 5, p. 1414-1424, https://doi.org/10.1111/1365-2664.12309.","productDescription":"11 p.","startPage":"1414","endPage":"1424","numberOfPages":"11","ipdsId":"IP-053579","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472743,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12309","text":"Publisher Index Page"},{"id":438742,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RMD98M","text":"USGS data release","linkHelpText":"Vegetation and fuels data collected in 2010 and 2011 from historical emergency stabilization and rehabilitation seedings (1990 - 2003) on BLM lands within the Great Basin"},{"id":294537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294515,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12309"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.2,36.46 ], [ -121.2,45.0 ], [ -110.61,45.0 ], [ -110.61,36.46 ], [ -121.2,36.46 ] ] ] } } ] }","volume":"51","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-07-17","publicationStatus":"PW","scienceBaseUri":"5425208ee4b0e641df8a6dbd","contributors":{"authors":[{"text":"Knutson, Kevin C. kevin_knutson@usgs.gov","contributorId":3646,"corporation":false,"usgs":true,"family":"Knutson","given":"Kevin C.","email":"kevin_knutson@usgs.gov","affiliations":[],"preferred":true,"id":502251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":502250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wirth, Troy A.","contributorId":27837,"corporation":false,"usgs":true,"family":"Wirth","given":"Troy A.","affiliations":[],"preferred":false,"id":502252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert S.","contributorId":55679,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","affiliations":[],"preferred":false,"id":502253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S.","contributorId":101760,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[],"preferred":false,"id":502255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":502248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chambers, Jeanne C.","contributorId":75889,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne C.","affiliations":[],"preferred":false,"id":502254,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":502249,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70121118,"text":"sir20105070L - 2014 - Deposit model for heavy-mineral sands in coastal environments","interactions":[],"lastModifiedDate":"2020-07-01T19:49:29.216529","indexId":"sir20105070L","displayToPublicDate":"2014-09-17T11:33:00","publicationYear":"2014","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":"2010-5070","chapter":"L","title":"Deposit model for heavy-mineral sands in coastal environments","docAbstract":"This report provides a descriptive model of heavy-mineral sands, which are sedimentary deposits of dense minerals that accumulate with sand, silt, and clay in coastal environments, locally forming economic concentrations of the heavy minerals. This deposit type is the main source of titanium feedstock for the titanium dioxide (TiO2) pigments industry, through recovery of the minerals ilmenite (Fe2+TiO3), rutile (TiO2), and leucoxene (an alteration product of ilmenite). Heavy-mineral sands are also the principal source of zircon (ZrSiO4) and its zirconium oxide; zircon is often recovered as a coproduct. Other heavy minerals produced as coproducts from some deposits are sillimanite/kyanite, staurolite, monazite, and garnet. Monazite [(Ce,La,Nd,Th)PO4] is a source of rare earth elements as well as thorium, which is used in thorium-based nuclear power under development in India and elsewhere.
\nThe processes that form coastal deposits of heavy-mineral sands begin inland. High-grade metamorphic and igneous rocks that contain heavy minerals weather and erode, contributing detritus composed of sand, silt, clay, and heavy minerals to fluvial systems. Streams and rivers carry the detritus to the coast, where they are deposited in a variety of coastal environments, such as deltas, the beach face (foreshore), the nearshore, barrier islands or dunes, and tidal lagoons, as well as the channels and floodplains of streams and rivers in the coastal plain. The sediments are reworked by waves, tides, longshore currents, and wind, which are effective mechanisms for sorting the mineral grains on the basis of differences in their size and density. The finest-grained, most dense heavy minerals are the most effectively sorted. The result is that heavy minerals accumulate together, forming laminated or lens-shaped, heavy-mineral-rich sedimentary packages that can be several meters and even as much as tens of meters thick. Most economic deposits of heavy-mineral sands are Paleogene, Neogene, and Quaternary in age; some are modern coastal deposits.
\nSuperimposed on these basic processes of ore formation are a multitude of contributing and modifying factors, such as the following:
\nThe resulting deposits of heavy-mineral sands can be voluminous. Individual bodies of heavy mineral-rich sands are typically about 1 kilometer wide and more than 5 kilometers long. Many heavy-mineral sands districts extend for more than 10 kilometers and contain several individual deposits that are spread along an ancient or modern strandline. Reported thicknesses of economic deposits range from 3 to 45 meters. Individual ore deposits typically comprise at least 10 megatonnes of ore (the total size of the individual sand-silt body), whose overall heavy-mineral content is 2 to greater than 10 percent.
\nHeavy-mineral sands deposits are relatively easy to mine because they are weakly to poorly consolidated, and they are relatively easy to process. From a geoenvironmental standpoint, mining of heavy mineral-sands generates little or no acid or solubilized metals. However, environmental and human health concerns related to such mining include potential effects on indigenous flora and fauna, effects on local hydrology, and issues related to processing and storing thorium-bearing monazite, owing to its radioactivity.
\nRegional exploration for deposits of heavy-mineral sands can utilize the analyses of stream sediment samples for Ti, Hf, the rare earth elements, Th, and U, and geophysical surveys, particularly radiometric (gamma-ray spectrometry for K, U, and Th) and magnetic methods. Geophysical anomalies may be small, and surveys are generally more successful when conducted close to sources of interest.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070L","issn":"2328-0328","usgsCitation":"Van Gosen, B.S., Fey, D.L., Shah, A.K., Verplanck, P.L., and Hoefen, T.M., 2014, Deposit model for heavy-mineral sands in coastal environments: U.S. Geological Survey Scientific Investigations Report 2010-5070, viii, 51 p., https://doi.org/10.3133/sir20105070L.","productDescription":"viii, 51 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053206","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":294045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070L.jpg"},{"id":294044,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/l/"},{"id":294046,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/l/pdf/sir2010-5070l.pdf","text":"Report","size":"15.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541a948be4b01571b3d4cc21","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":498804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":498805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":498803,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70128747,"text":"70128747 - 2014 - A synopsis of short-term response to alternative restoration treatments in sagebrush-steppe: the SageSTEP project","interactions":[],"lastModifiedDate":"2017-11-22T10:37:14","indexId":"70128747","displayToPublicDate":"2014-09-15T13:11:41","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"A synopsis of short-term response to alternative restoration treatments in sagebrush-steppe: the SageSTEP project","docAbstract":"The Sagebrush Steppe Treatment Evaluation Project (SageSTEP) is an integrated long-term study that evaluates ecological effects of alternative treatments designed to reduce woody fuels and to stimulate the herbaceous understory of sagebrush steppe communities of the Intermountain West. This synopsis summarizes results through 3 yr posttreatment. Woody vegetation reduction by prescribed fire, mechanical treatments, or herbicides initiated a cascade of effects, beginning with increased availability of nitrogen and soil water, followed by increased growth of herbaceous vegetation. Response of butterflies and magnitudes of runoff and erosion closely followed herbaceous vegetation recovery. Effects on shrubs, biological soil crust, tree cover, surface woody fuel loads, and sagebrush-obligate bird communities will take longer to be fully expressed. In the short term, cool wet sites were more resilient than warm dry sites, and resistance was mostly dependent on pretreatment herbaceous cover. At least 10 yr of posttreatment time will likely be necessary to determine outcomes for most sites. Mechanical treatments did not serve as surrogates for prescribed fire in how each influenced the fuel bed, the soil, erosion, and sage-obligate bird communities. Woody vegetation reduction by any means resulted in increased availability of soil water, higher herbaceous cover, and greater butterfly numbers. We identified several trade-offs (desirable outcomes for some variables, undesirable for others), involving most components of the study system. Trade-offs are inevitable when managing complex natural systems, and they underline the importance of asking questions about the whole system when developing management objectives. Substantial spatial and temporal heterogeneity in sagebrush steppe ecosystems emphasizes the point that there will rarely be a “recipe” for choosing management actions on any specific area. Use of a consistent evaluation process linked to monitoring may be the best chance managers have for arresting woodland expansion and cheatgrass invasion that may accelerate in a future warming climate.","language":"English","publisher":"Society for Range Management","publisherLocation":"Lakewood, CO","doi":"10.2111/REM-D-14-00084.1","usgsCitation":"McIver, J., Brunson, M., Bunting, S., Chambers, J., Doescher, P., Grace, J., Hulet, A., Johnson, D., Knick, S.T., Miller, R., Pellant, M., Pierson, F., Pyke, D., Rau, B., Rollins, K., Roundy, B., Schupp, E., Tausch, R., and Williams, J., 2014, A synopsis of short-term response to alternative restoration treatments in sagebrush-steppe: the SageSTEP project: Rangeland Ecology and Management, v. 67, no. 5, p. 584-598, https://doi.org/10.2111/REM-D-14-00084.1.","productDescription":"15 p.","startPage":"584","endPage":"598","numberOfPages":"15","ipdsId":"IP-058346","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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Eugene","contributorId":84682,"corporation":false,"usgs":true,"family":"Schupp","given":"Eugene","affiliations":[],"preferred":false,"id":503192,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tausch, Robin","contributorId":43290,"corporation":false,"usgs":true,"family":"Tausch","given":"Robin","affiliations":[],"preferred":false,"id":503180,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, Jason jason@usgs.gov","contributorId":3397,"corporation":false,"usgs":true,"family":"Williams","given":"Jason","email":"jason@usgs.gov","affiliations":[],"preferred":true,"id":503177,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70132473,"text":"70132473 - 2014 - Estimates of annual survival, growth, and recruitment of a white-tailed ptarmigan population in Colorado over 43 years","interactions":[],"lastModifiedDate":"2020-12-31T20:36:58.905875","indexId":"70132473","displayToPublicDate":"2014-09-13T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimates of annual survival, growth, and recruitment of a white-tailed ptarmigan population in Colorado over 43 years","docAbstract":"Long-term datasets for high-elevation species are rare, and considerable uncertainty exists in understanding how high-elevation populations have responded to recent climate warming. We present estimates of demographic vital rates from a 43-year population study of white-tailed ptarmigan (Lagopus leucura), a species endemic to alpine habitats in western North America. We used capture-recapture models to estimate annual rates of apparent survival, population growth, and recruitment for breeding-age ptarmigan, and we fit winter weather covariates to models in an attempt to explain annual variation. There were no trends in survival over the study period but there was strong support for age and sex effects. The average rate of annual growth suggests a relatively stable breeding-age population (
Fisheries targeting mixtures of populations risk the over utilization of minor stock constituents unless harvests are monitored and managed. We evaluated stock composition and exploitation of Atlantic salmon in a subsistence fishery in coastal Labrador, Canada using genetic mixture analysis and individual assignment with a microsatellite baseline (15 loci, 11 829 individuals, 12 regional groups) encompassing the species western Atlantic range. Bayesian and maximum likelihood mixture analyses of fishery samples over six years (2006-2011; 1 772 individuals) indicate contributions of adjacent stocks of 96-97%. Estimates of fishery associated exploitation were highest for Labrador salmon (4.2-10.6% per year) and generally < 1% for other regions. Individual assignment of fishery samples indicated non-local contributions to the fishery (e.g., Quebec, Newfoundland) were rare and primarily in southern Labrador, consistent with migration pathways utilizing the Strait of Belle Isle. This work illustrates how genetic analysis of mixed stock Atlantic salmon fisheries in the northwest Atlantic using this new baseline can disentangle exploitation and reveal complex migratory behaviours.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Fisheries and Aquatic Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2014-0058","usgsCitation":"Bradbury, I.R., Hamilton, L.C., Rafferty, S., Meerburg, D., Poole, R., Dempson, J.B., Robertson, M.J., Reddin, D.G., Bourret, V., Dionne, M., Chaput, G.J., Sheehan, T.F., King, T., Candy, J.R., and Bernatchez, L., 2014, Genetic evidence of local exploitation of Atlantic salmon in a coastal subsistence fishery in the Northwest Atlantic: Canadian Journal of Fisheries and Aquatic Sciences, https://doi.org/10.1139/cjfas-2014-0058.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055626","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":295708,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295707,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/cjfas-2014-0058"}],"otherGeospatial":"Atlantic Ocean","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544b6a21e4b03653c63fb1d2","contributors":{"authors":[{"text":"Bradbury, Ian R.","contributorId":20676,"corporation":false,"usgs":true,"family":"Bradbury","given":"Ian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":503878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamilton, Lorraine C.","contributorId":74317,"corporation":false,"usgs":true,"family":"Hamilton","given":"Lorraine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":503885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rafferty, Sara","contributorId":107214,"corporation":false,"usgs":true,"family":"Rafferty","given":"Sara","email":"","affiliations":[],"preferred":false,"id":503891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meerburg, David","contributorId":94992,"corporation":false,"usgs":true,"family":"Meerburg","given":"David","email":"","affiliations":[],"preferred":false,"id":503889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poole, Rebecca","contributorId":21882,"corporation":false,"usgs":true,"family":"Poole","given":"Rebecca","email":"","affiliations":[],"preferred":false,"id":503879,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dempson, J. Brian","contributorId":25882,"corporation":false,"usgs":true,"family":"Dempson","given":"J.","email":"","middleInitial":"Brian","affiliations":[],"preferred":false,"id":503880,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robertson, Martha J.","contributorId":98659,"corporation":false,"usgs":true,"family":"Robertson","given":"Martha","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":503890,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reddin, David G.","contributorId":86707,"corporation":false,"usgs":true,"family":"Reddin","given":"David","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":503887,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bourret, Vincent","contributorId":87080,"corporation":false,"usgs":true,"family":"Bourret","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":503888,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dionne, Melanie","contributorId":62157,"corporation":false,"usgs":true,"family":"Dionne","given":"Melanie","email":"","affiliations":[],"preferred":false,"id":503883,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Chaput, Gerald J.","contributorId":81823,"corporation":false,"usgs":true,"family":"Chaput","given":"Gerald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":503886,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sheehan, Timothy F.","contributorId":26640,"corporation":false,"usgs":true,"family":"Sheehan","given":"Timothy","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":503881,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"King, Tim L.","contributorId":10736,"corporation":false,"usgs":true,"family":"King","given":"Tim L.","affiliations":[],"preferred":false,"id":503877,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Candy, John R.","contributorId":66616,"corporation":false,"usgs":true,"family":"Candy","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":503884,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bernatchez, Louis","contributorId":34066,"corporation":false,"usgs":true,"family":"Bernatchez","given":"Louis","affiliations":[],"preferred":false,"id":503882,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70120245,"text":"ofr20141173 - 2014 - Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014","interactions":[],"lastModifiedDate":"2014-09-09T16:13:46","indexId":"ofr20141173","displayToPublicDate":"2014-09-09T08:53:00","publicationYear":"2014","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":"2014-1173","title":"Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014","docAbstract":"Kaloko-Honokōhau National Historical Park (KAHO) on western Hawaiʻi was established in 1978 to preserve, interpret, and perpetuate traditional Native Hawaiian culture and activities, including the preservation of a variety of culturally and ecologically significant water resources that are vital to this mission. KAHO water bodies provide habitat for 1 threatened, 11 endangered, and 3 candidate threatened or endangered species. These habitats are sustained by, and in the case of ʻAimakapā Fishpond and the anchialine pools, entirely dependent on, groundwater from the Keauhou aquifer system. Development of inland impounded groundwater in the Keauhou aquifer system may affect the coastal freshwater-lens system on which KAHO depends, if the inland impounded-groundwater and coastal freshwater-lens systems are hydrologically connected. This report documents water-chemistry results from a U.S. Geological Survey study that collected and analyzed water samples from 2012 to 2014 from 25 sites in and near KAHO to investigate potential geochemical indicators in water that might indicate the presence or absence of a hydrologic connection between the inland impounded-groundwater and coastal freshwater-lens systems in the area. Samples were collected under high-tide and low-tide conditions for KAHO sites, and in dry-season and wet-season conditions for all sites. Samples were collected from two ocean sites, two fishponds, three anchialine pools, and three monitoring wells within KAHO. Two additional nearshore wells were sampled on property adjacent to and north of KAHO. Additional samples from the freshwater-lens system were collected from six inland wells located upslope from KAHO, including three production wells. Seven production wells in the inland impounded-groundwater system also were sampled. Water samples were analyzed for major ions, selected trace elements, rare-earth elements, strontium-isotope ratio, and stable isotopes of water. Precipitation samples from five sites were collected roughly along a transect upslope from KAHO. All precipitation samples were analyzed for stable isotopes of water and some precipitation samples were analyzed for rare-earth and selected trace elements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141173","collaboration":"Prepared in cooperation with the Hawaiʻi Commission on Water Resource Management and the National Park Service","usgsCitation":"Tillman, F., Oki, D.S., and Johnson, A.G., 2014, Water-chemistry data collected in and near Kaloko-Honokohau National Historical Park, Hawaii, 2012–2014: U.S. Geological Survey Open-File Report 2014-1173, Report: v, 14 p.; Tables, https://doi.org/10.3133/ofr20141173.","productDescription":"Report: v, 14 p.; Tables","numberOfPages":"24","onlineOnly":"Y","temporalStart":"2012-01-01","temporalEnd":"2014-09-01","ipdsId":"IP-057290","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":293481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141173.jpg"},{"id":293477,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1173/pdf/ofr2014-1173.pdf"},{"id":293478,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1173/downloads/ofr2014-1173_tables.xlsx"},{"id":293469,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1173/"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kaloko-honokohau National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.045925,19.665068 ], [ -156.045925,19.693891 ], [ -156.016629,19.693891 ], [ -156.016629,19.665068 ], [ -156.045925,19.665068 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54100634e4b07ab1cd980825","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":1629,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred D.","email":"ftillman@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":498048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498050,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70124942,"text":"70124942 - 2014 - Geophysical expression of a buried niobium and rare earth element deposit: the Elk Creek carbonatite, Nebraska, USA","interactions":[],"lastModifiedDate":"2017-06-30T13:40:13","indexId":"70124942","displayToPublicDate":"2014-09-01T14:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical expression of a buried niobium and rare earth element deposit: the Elk Creek carbonatite, Nebraska, USA","docAbstract":"The lower Paleozoic Elk Creek carbonatite is a 6–8-km-diameter intrusive complex buried under 200 m of sedimentary rocks in southeastern Nebraska. It hosts the largest known niobium deposit in the U.S. and a rare earth element (REE) deposit. The carbonatite is composed of several lithologies, the relations of which are poorly understood. Niobium mineralization is most enriched within a magnetite beforsite (MB) unit, and REE oxides are most concentrated in a barite beforsite unit. The carbonatite intrudes Proterozoic country rocks. Efforts to explore the carbonatite have used geophysical data and drilling. A high-resolution airborne gravity gradient and magnetic survey was flown over the carbonatite in 2012. The carbonatite is associated with a roughly annular vertical gravity gradient high and a subdued central low and a central magnetic high surrounded by magnetic field values lower than those over the country rocks. Geophysical, borehole, and physical property data are combined for an interpretation of these signatures. The carbonatite is denser than the country rocks, explaining the gravity gradient high. Most carbonatite lithologies have weaker magnetic susceptibilities than those of the country rocks, explaining why the carbonatite does not produce a magnetic high at its margin. The primary source of the central magnetic high is interpreted to be mafic rocks that are strongly magnetized and are present in large volumes. MB is very dense (mean density 3200 kg/m3) and strongly magnetized (median 0.073 magnetic susceptibility), producing a gravity gradient high and contributing to the aeromagnetic high. Barite beforsite has physical properties similar to most of the carbonatite volume, making it a poor geophysical target. Geophysical anomalies indicate the presence of dense and strongly magnetized rocks at depths below existing boreholes, either a large volume of MB or another unknown lithology.","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/INT-2014-0002.1","usgsCitation":"Drenth, B.J., 2014, Geophysical expression of a buried niobium and rare earth element deposit: the Elk Creek carbonatite, Nebraska, USA: Interpretation, v. 2, no. 4, p. SJ169-SJ179, https://doi.org/10.1190/INT-2014-0002.1.","productDescription":"11 p.","startPage":"SJ169","endPage":"SJ179","numberOfPages":"11","ipdsId":"IP-053233","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":294877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294876,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1190/INT-2014-0002.1"}],"country":"United States","state":"Nebraska","otherGeospatial":"Elk Creek","volume":"2","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e6960e4b092f17df5a879","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":501028,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70186706,"text":"70186706 - 2014 - Mineral resource of the month: Arsenic","interactions":[],"lastModifiedDate":"2017-04-07T12:56:08","indexId":"70186706","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1419,"text":"Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mineral resource of the month: Arsenic","docAbstract":"Arsenic is a gray metal rarely encountered as a free element, but is widely distributed in minerals and ores that contain copper, iron and lead. Arsenic is often found in groundwater as a result of the natural weathering of rock and soil.
","language":"English","publisher":"AGI","usgsCitation":"Bedinger, G.M., 2014, Mineral resource of the month: Arsenic: Earth, v. September 2014, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-057264","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":339435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339420,"type":{"id":15,"text":"Index Page"},"url":"https://www.earthmagazine.org/article/mineral-resource-month-arsenic"}],"volume":"September 2014","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e8a545e4b09da6799d63b5","contributors":{"authors":[{"text":"Bedinger, George M. gbedinger@usgs.gov","contributorId":4567,"corporation":false,"usgs":true,"family":"Bedinger","given":"George","email":"gbedinger@usgs.gov","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":690320,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137437,"text":"70137437 - 2014 - Survival of surf scoters and white-winged scoters during remigial molt","interactions":[],"lastModifiedDate":"2015-01-08T10:55:09","indexId":"70137437","displayToPublicDate":"2014-09-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Survival of surf scoters and white-winged scoters during remigial molt","docAbstract":"Quantifying sources and timing of variation in demographic rates is necessary to determine where and when constraints may exist within the annual cycle of organisms. Surf scoters (Melanitta perspicillata) and white-winged scoters (M. fusca) undergo simultaneous remigial molt during which they are flightless for >1 month. Molt could result in reduced survival due to increased predation risk or increased energetic demands associated with regrowing flight feathers. Waterfowl survival during remigial molt varies across species, and has rarely been assessed for sea ducks. To quantify survival during remigial molt, we deployed very high frequency (VHF) transmitters on surf scoters (n = 108) and white-winged scoters (n = 57) in southeast Alaska and the Salish Sea (British Columbia and Washington) in 2008 and 2009. After censoring mortalities potentially related to capture and handling effects, we detected no mortalities during remigial molt; thus, estimates of daily and period survival for both scoter species during molt were 1.00. We performed sensitivity analyses in which mortalities were added to the dataset to simulate potential mortality rates for the population and then estimated the probability of obtaining a dataset with 0 mortalities. We found that only at high survival rates was there a high probability of observing 0 mortalities. We conclude that remigial molt is normally a period of low mortality in the annual cycle of scoters. The molt period does not appear to be a constraint on scoter populations; therefore, other annual cycle stages should be targeted by research and management efforts to change population trajectories.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.774","usgsCitation":"Uher-Koch, B.D., Esler, D., Dickson, R.D., Hupp, J.W., Evenson, J.R., Anderson, E.M., Barrett, J., and Schmutz, J.A., 2014, Survival of surf scoters and white-winged scoters during remigial molt: Journal of Wildlife Management, v. 78, no. 7, p. 1189-1196, https://doi.org/10.1002/jwmg.774.","productDescription":"8 p.","startPage":"1189","endPage":"1196","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051189","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":297083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Washington","otherGeospatial":"Salish Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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D.","contributorId":138554,"corporation":false,"usgs":false,"family":"Dickson","given":"Rian","email":"","middleInitial":"D.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":537820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":537821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evenson, Joseph R.","contributorId":138555,"corporation":false,"usgs":false,"family":"Evenson","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":537822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Eric M.","contributorId":138556,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric","email":"","middleInitial":"M.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":537823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barrett, Jennifer","contributorId":138557,"corporation":false,"usgs":false,"family":"Barrett","given":"Jennifer","email":"","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":537824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":537825,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70148500,"text":"70148500 - 2014 - The offshore benthic fish community","interactions":[],"lastModifiedDate":"2017-06-09T15:00:18","indexId":"70148500","displayToPublicDate":"2014-08-28T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"The offshore benthic fish community","docAbstract":"Lake Ontario’s offshore benthic fish community includes primarily slimy sculpin, lake whitefish, rainbow smelt, lake trout, burbot, and sea lamprey. Of these, lake trout have been the focus of an international restoration effort for more than three decades (Elrod et al. 1995; Lantry and Lantry 2008). The deepwater sculpin and three species of deepwater ciscoes (Coregonus spp.) that were historically important in the offshore benthic zone became rare or were extirpated by the 1960s (Christie 1973; Owens et al. 2003; Lantry et al. 2007b; Roth et al. 2013). Ecosystem changes continue to influence the offshore benthic fish community, including the effects of dreissenid mussels, the near disappearance of burrowing amphipods (Diporeia spp.) (Dermott et al. 2005; Watkins et al. 2007), and the increased abundance and expanded geographic distribution of round goby (see Nearshore Fish Community chapter) (Lantry et al. 2007b). The fish-community objectives for the offshore benthic fish community, as described by Stewart et al. (1999), are:\nThe offshore benthic fish community will be composed of self-sustaining native fishes characterized by lake trout as the top predator, a population expansion of lake whitefish from northeastern waters to other areas of the lake, and rehabilitated native prey fishes.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The state of Lake Ontario in 2008","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Lantry, B.F., Lantry, J.R., Weidel, B., Walsh, M., Hoyle, J., Schaner, T., Neave, F.B., and Keir, M., 2014, The offshore benthic fish community, 19 p.","productDescription":"19 p.","startPage":"23","endPage":"41","ipdsId":"IP-056191","costCenters":[{"id":324,"text":"Great Lakes Science 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bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Maureen 0000-0001-7846-5025 mwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-7846-5025","contributorId":3659,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"mwalsh@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":548450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":" Hoyle, James A.","contributorId":141108,"corporation":false,"usgs":false,"family":" Hoyle","given":"James A.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural 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Canada","active":true,"usgs":false}],"preferred":false,"id":548457,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70119959,"text":"ds876 - 2014 - Dissolved pesticide concentrations entering the Sacramento-San Joaquin Delta from the Sacramento and San Joaquin Rivers, California, 2012-13","interactions":[],"lastModifiedDate":"2014-08-26T08:54:44","indexId":"ds876","displayToPublicDate":"2014-08-26T08:47:00","publicationYear":"2014","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":"876","title":"Dissolved pesticide concentrations entering the Sacramento-San Joaquin Delta from the Sacramento and San Joaquin Rivers, California, 2012-13","docAbstract":"Surface-water samples were collected from the Sacramento and San Joaquin Rivers where they enter the Sacramento–San Joaquin Delta, and analyzed by the U.S. Geological Survey for a suite of 99 current-use pesticides and pesticide degradates. Samples were collected twice per month from May 2012 through July 2013 and from May 2012 through April 2013 at the Sacramento River at Freeport, and the San Joaquin River near Vernalis, respectively. Samples were analyzed by two separate laboratory methods by using gas chromatography with mass spectrometry or liquid chromatography with tandem mass spectrometry. Method detection limits ranged from 0.9 to 10.5 nanograms per liter (ng/L).
\nA total of 37 pesticides and degradates were detected in water samples collected during the study (18 herbicides, 11 fungicides, 7 insecticides, and 1 synergist). The most frequently detected pesticides overall were the herbicide hexazinone (detected in 100 percent of the samples); 3,4-dichloroaniline (97 percent), which is a degradate of the herbicides diuron and propanil; the fungicide azoxystrobin (83 percent); and the herbicides diuron (72 percent), simazine (66 percent), and metolachlor (64 percent). Insecticides were rarely detected during the study. Pesticide concentrations varied from below the method detection limits to 984 ng/L (hexazinone).
\nTwenty seven pesticides and (or) degradates were detected in Sacramento River samples, and the average number of pesticides per sample was six. The most frequently detected compounds in these samples were hexazinone (detected in 100 percent of samples), 3,4-dichloroaniline (97 percent), azoxystrobin (88 percent), diuron (56 percent), and simazine (50 percent). Pesticides with the highest detected maximum concentrations in Sacramento River samples included the herbicide clomazone (670 ng/L), azoxystrobin (368 ng/L), 3,4-dichloroaniline (364 ng/L), hexazinone (130 ng/L), and propanil (110 ng/L), and all but hexazinone are primarily associated with rice agriculture.
\nIn addition to the twice monthly sampling, surface-water samples were collected from the Sacramento River on 5 consecutive days following a rainfall event in the Sacramento urban area. Samples collected following this event contained an average of 11 pesticides. The insecticides carbaryl, fipronil, and imidacloprid; the herbicide DCPA; and the fungicide imazalil were only detected in the Sacramento River during this storm-runoff event, and two detections of fipronil during this period exceeded the U.S. Environmental Protection Agency Aquatic Life Benchmark (11 ng/L) for chronic toxicity to invertebrates in freshwater.
\nIn San Joaquin River samples, 26 pesticides and (or) degradates were detected, and the average number detected per sample was 9. The most frequently detected compounds in these samples were hexazinone and metolachlor (detected in 100 percent of samples); diuron (96 percent); the fungicide boscalid (96 percent); the degradates 3,4-dicloroaniline (92 percent) and NN-(3,4-Dichlorophenyl)-N’-methylurea (DCPMU; 83 percent); simazine (83 percent); and azoxystrobin (75 percent). The pesticides with the highest detected maximum concentrations were hexazinone (984 ng/L), diuron (695 ng/L), simazine (524 ng/L), the herbicide prometryn (155 ng/L), metolachlor (127 ng/L), boscalid (112 ng/L), DCPMU (111 ng/L), and the herbicide pendimethalin (108 ng/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds876","collaboration":"Prepared in cooperation with the San Luis and Delta Mendota Water Authority","usgsCitation":"Orlando, J., McWayne, M., Sanders, C., and Hladik, M., 2014, Dissolved pesticide concentrations entering the Sacramento-San Joaquin Delta from the Sacramento and San Joaquin Rivers, California, 2012-13: U.S. Geological Survey Data Series 876, viii, 28 p., https://doi.org/10.3133/ds876.","productDescription":"viii, 28 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-052843","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":293014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds876.jpg"},{"id":293013,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0876/pdf/ds876.pdf"},{"id":293009,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0876"}],"projection":"Albers Equal Area Projection","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Sacramento�san Joaquin Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.00,36.00 ], [ -124.00,40.00 ], [ -120.00,40.00 ], [ -120.00,36.00 ], [ -124.00,36.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53fd912fe4b0adaeea6c1730","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":497873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McWayne, Megan 0000-0001-8069-6420","orcid":"https://orcid.org/0000-0001-8069-6420","contributorId":36038,"corporation":false,"usgs":true,"family":"McWayne","given":"Megan","affiliations":[],"preferred":false,"id":497870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanders, Corey 0000-0001-7743-6396","orcid":"https://orcid.org/0000-0001-7743-6396","contributorId":39682,"corporation":false,"usgs":true,"family":"Sanders","given":"Corey","affiliations":[],"preferred":false,"id":497871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":45990,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","affiliations":[],"preferred":false,"id":497872,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156823,"text":"70156823 - 2014 - Sub-decadal turbidite frequency during the early Holocene: Eel Fan, offshore northern California","interactions":[],"lastModifiedDate":"2015-08-31T10:03:37","indexId":"70156823","displayToPublicDate":"2014-08-15T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3877,"text":"Geology Today","active":true,"publicationSubtype":{"id":10}},"title":"Sub-decadal turbidite frequency during the early Holocene: Eel Fan, offshore northern California","docAbstract":"Remotely operated and autonomous underwater vehicle technologies were used to image and sample exceptional deep sea outcrops where an ∼100-m-thick section of turbidite beds is exposed on the headwalls of two giant submarine scours on Eel submarine fan, offshore northern California (USA). These outcrops provide a rare opportunity to connect young deep-sea turbidites with their feeder system. 14C measurements reveal that from 12.8 ka to 7.9 ka, one turbidite was being emplaced on average every 7 yr. This emplacement rate is two to three orders of magnitude higher than observed for turbidites elsewhere along the Pacific margin of North America. The turbidites contain abundant wood and shallow-dwelling foraminifera, demonstrating an efficient connection between the Eel River source and the Eel Fan sink. Turbidite recurrence intervals diminish fivefold to ∼36 yr from 7.9 ka onward, reflecting sea-level rise and re-routing of Eel River sediments.
","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/G35768.1","usgsCitation":"Paull, C.K., McGann, M., Sumner, E., Barnes, P.M., Lundsten, E.M., Anderson, K., Gwiazda, R., Edwards, B.D., and Caress, D., 2014, Sub-decadal turbidite frequency during the early Holocene: Eel Fan, offshore northern California: Geology Today, v. 42, no. 10, p. 855-858, https://doi.org/10.1130/G35768.1.","productDescription":"4 p.","startPage":"855","endPage":"858","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055990","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g35768.1","text":"Publisher Index Page"},{"id":307714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e57ab1e4b05561fa2086b4","contributors":{"authors":[{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":570706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGann, Mary L. 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":147188,"corporation":false,"usgs":true,"family":"McGann","given":"Mary L.","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":570705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sumner, Esther J.","contributorId":147189,"corporation":false,"usgs":false,"family":"Sumner","given":"Esther J.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":570707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnes, Philip M","contributorId":147190,"corporation":false,"usgs":false,"family":"Barnes","given":"Philip","email":"","middleInitial":"M","affiliations":[{"id":16802,"text":"National Institute of Water and Atmospheric Research, Wellington, New Zealand","active":true,"usgs":false}],"preferred":false,"id":570708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lundsten, Eve M.","contributorId":147191,"corporation":false,"usgs":false,"family":"Lundsten","given":"Eve","email":"","middleInitial":"M.","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":570709,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Krystle","contributorId":147192,"corporation":false,"usgs":false,"family":"Anderson","given":"Krystle","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":570710,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gwiazda, Roberto","contributorId":147193,"corporation":false,"usgs":false,"family":"Gwiazda","given":"Roberto","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":570711,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Brian D. bedwards@usgs.gov","contributorId":3161,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":570712,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caress, David W","contributorId":147194,"corporation":false,"usgs":false,"family":"Caress","given":"David W","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":570713,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70115925,"text":"sir20145125 - 2014 - A precipitation-runoff model for simulating natural streamflow conditions in the Smith River watershed, Montana, water years 1996-2008","interactions":[],"lastModifiedDate":"2014-08-08T12:44:08","indexId":"sir20145125","displayToPublicDate":"2014-08-08T11:55:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5125","title":"A precipitation-runoff model for simulating natural streamflow conditions in the Smith River watershed, Montana, water years 1996-2008","docAbstract":"This report documents the construction of a precipitation-runoff model for simulating natural streamflow in the Smith River watershed, Montana. This Precipitation-Runoff Modeling System model, constructed in cooperation with the Meagher County Conservation District, can be used to examine the general hydrologic framework of the Smith River watershed, including quantification of precipitation, evapotranspiration, and streamflow; partitioning of streamflow between surface runoff and subsurface flow; and quantifying contributions to streamflow from several parts of the watershed.
\nThe model was constructed by using spatial datasets describing watershed topography, the streams, and the hydrologic characteristics of the basin soils and vegetation. Time-series data (daily total precipitation, and daily minimum and maximum temperature) were input to the model to simulate daily streamflow. The model was calibrated for water years 2002–2007 and evaluated for water years 1996–2001. Though water year 2008 was included in the study period to evaluate water-budget components, calibration and evaluation data were unavailable for that year. During the calibration and evaluation periods, simulated-natural flow values were compared to reconstructed-natural streamflow data. These reconstructed-natural streamflow data were calculated by adding Bureau of Reclamation’s depletions data to the observed streamflows. Reconstructed-natural streamflows represent estimates of streamflows for water years 1996–2007 assuming there was no agricultural water-resources development in the watershed. Additional calibration targets were basin mean monthly solar radiation and potential evapotranspiration.
\nThe model estimated the hydrologic processes in the Smith River watershed during the calibration and evaluation periods. Simulated-natural mean annual and mean monthly flows generally were the same or higher than the reconstructed-natural streamflow values during the calibration period, whereas they were lower during the evaluation period. The shape of the annual hydrographs for the simulated-natural daily streamflow values matched the shape of the hydrographs for the reconstructed-natural values for most of the calibration period, but daily streamflow values were underestimated during the evaluation period for water years 1996–1998.
\nThe model enabled a detailed evaluation of the components of the water budget within the Smith River watershed during the water year 1996–2008 study period. During this study period, simulated mean annual precipitation across the Smith River watershed was 16 inches, out of which 14 inches evaporated or transpired and 2 inches left the basin as streamflow. Per the precipitation-runoff model simulations, during most of the year, surface runoff rarely (less than 2 percent of the time during water years 2002–2008) makes up more than 10 percent of the total streamflow. Subsurface flow (the combination of interflow and groundwater flow) makes up most of the total streamflow (99 or more percent of total streamflow for 71 percent of the time during water years 2002–2008).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145125","collaboration":"Prepared in cooperation with the Meagher County Conservation District","usgsCitation":"Chase, K.J., Caldwell, R.R., and Stanley, A.K., 2014, A precipitation-runoff model for simulating natural streamflow conditions in the Smith River watershed, Montana, water years 1996-2008: U.S. Geological Survey Scientific Investigations Report 2014-5125, vi, 29 p., https://doi.org/10.3133/sir20145125.","productDescription":"vi, 29 p.","numberOfPages":"40","onlineOnly":"Y","temporalStart":"1995-10-01","temporalEnd":"2008-09-30","ipdsId":"IP-055228","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":291909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145125.jpg"},{"id":291908,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5125/pdf/sir2014-5125.pdf"},{"id":291906,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5125/"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Montana","otherGeospatial":"Smith River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,46.25 ], [ -112.0,47.5 ], [ -110.5,47.5 ], [ -110.5,46.25 ], [ -112.0,46.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53e5d62ee4b0b6c2798a65b1","contributors":{"authors":[{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":495698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":495699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanley, Andrea K.","contributorId":61353,"corporation":false,"usgs":true,"family":"Stanley","given":"Andrea","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":495700,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}